2027 BEACoN Research Projects

Quantifying Soil Erosion to Aid Restoration Monitoring in Coastal Grasslands 

Yamina Pressler (she/her)

Natural Resources Management & Environmental Sciences

ypressle@calpoly.edu

Research Project Description

Coastal grasslands provide habitat for biodiversity and key ecosystem services, yet are vulnerable to degradation from climate change, invasive species such as feral pigs, and overgrazing. As California experiences climate-whiplash and increasing intensity of precipitation events, coastal soils are susceptible to accelerated erosion. Loss of soils from erosion can lead to problems such as loss of fertility, greater land instability, higher flooding risks, and loss of habitat for native species. Grassland restoration practitioners and land managers will benefit from accessible approaches to assess and monitor erosion on their properties. To support this need, we are evaluating methods to quantify soil erosion rates on marine terraces at Ranch Marino Reserve in Cambria, CA. Monitoring methods include photo monitoring, erosion pins, mesh trap bags, and geospatial modeling techniques. In this project, we will conduct repeated measurements at established erosion monitoring sites to assess the efficacy and accessibility of these methods. We will evaluate these methods during and after rain events throughout the wet season to understand how weather patterns impact the reliability of erosion measurements. We will evaluate the benefits and limitations of each method and determine appropriate use cases for restoration goals. We will then share our findings with restoration practitioners to aid restoration decision-making and inform possible interventions to minimize erosion risk in coastal grasslands.

Research Scholar's role in the Project

The BEACoN research scholar will be involved in methodological development, field assessment, data collection, data analysis and interpretation, and science communication for the research project by:

• conducting a literature review of soil erosion methods to identify benefits, limitations, and potential applications for restoration

• developing a photo-based erosion monitoring framework

• collecting soil erosion pin measurements before and after rain events

• conducting photo monitoring of erosion sites before and after rain events  

• analyzing soil erosion pin and photo-based datasets to quantify soil losses over time

• participating in results dissemination by developing a research poster and an erosion monitoring guide for restoration practitioners

Skills the Research Scholar will Gain

The BEACoN research scholar will gain skills in soil science, ecological restoration, field research, observational study design, and data analysis and interpretation. The scholar will develop field observational skills by learning how to interpret landforms, erosion features, and soil properties in coastal grasslands. The scholar will develop data collection and management skills through soil sampling, erosion measurements, and photo monitoring. They will gain experience with data management and analysis in R (statistical programming language). The scholar will learn how to interpret soil and ecological data to inform restoration decision-making. The scholar will also gain skills in science communication by engaging with practitioners and developing materials to support the implementation of erosion monitoring around California.
 

Required Courses/Experience

No prior research experience or coursework is required

Preferred Courses/Experience

Prior experience in soil science is preferred: Introductory Soil Science (SS 120/SS 1120) and Soil Morphology (SS 321/SS 3321)

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Making Sense of Phenomenon-Driven Instruction in Agriscience: Teacher Perspectives Across Levels of Self-Efficacy

Nicole Ray (she/her/hers)

Agricultural Education and Communication

nray04@calpoly.edu

Research Project Description

This project will examine how secondary agriculture teachers develop and sustain confidence in using phenomenon-driven instruction in agriscience classrooms. Agriculture offers a powerful context for science learning because students can investigate real-world systems, local problems, and observable events connected to food, fiber, natural resources, animals, plants, and environmental systems. When implemented well, phenomenon-driven instruction can support culturally relevant, rigorous learning by connecting content to students' lived experiences, leveraging community and cultural assets, and helping students use their own questions and observations to make sense of complex agricultural and scientific ideas. However, many teachers need support moving from recognizing an interesting agricultural example to using a phenomenon to drive learning activities, sensemaking, and assessment. Understanding how teachers build confidence with this approach matters because phenomenon-driven instruction can make agriscience more relevant, support student curiosity, and connect classroom content to students' communities and future careers.

Building on existing survey data and course feedback from teachers who completed the Foundations of Phenomenon professional leanring course, this mixed-methods follow-up study will explore what contributes to teachers' phenomenon-driven instruction self-efficacy over time. Teachers who agreed to participate in follow-up research may be asked to complete the phenomenon-driven instruction self-efficacy instrument again so the research team can examine changes from the previous year. Follow-up interviews will explore what teachers have tried since the course, what helped them feel more capable, what barriers limited implementation, and what assets or supports helped them continue developing their practice. Findings will contribute to a research manuscript and will also inform professional learning and practical resources that help agriculture teachers design more relevant, student-centered agriscience learning experiences.

Research Scholar's role in the Project

The BEACoN Research Scholar will lead, with support, key components of a mixed-methods follow-up study focused on agriculture teachers' confidence and implementation of phenomenon-driven instruction. The scholar will be expected to:

Conduct a literature review on phenomenon-driven instruction, teacher self-efficacy, NGSS-aligned agriscience instruction, and culturally relevant teaching practices
Review existing project data, including teachers' prior phenomenon-driven instruction self-efficacy scores and feedback from the Foundations of Phenomenon course
Help identify interview participants from teachers who previously agreed to participate in follow-up research
Develop research instruments, including the follow-up self-efficacy survey and teacher interview protocol
Collaborate on a modification to the existing approved IRB protocol to add the follow-up survey and related data collection procedures
Assist with administering the follow-up self-efficacy survey to examine how teacher confidence has changed over the past year
Conduct or co-conduct teacher interviews, with training and support
Organize and manage project data, including survey results, interview recordings or transcripts, course feedback, and analytic memos
Analyze interview data through qualitative coding, including developing codes, identifying patterns, comparing interpretations, and refining themes
Connect qualitative findings with survey results to better understand how teachers' confidence and practice have changed over time
Prepare and present findings at the BEACoN Symposium
Contribute, as appropriate, to a research manuscript, conference proposal, or practitioner-facing resource for agriculture teachers

Skills the Research Scholar will Gain

The BEACoN Research Scholar will gain applied social science research skills through a mixed-methods study of agriculture teachers' confidence and implementation of phenomenon-driven instruction. These skills are useful for graduate study, education, extension, nonprofit work, industry, program evaluation, and other careers that require evidence-based decision-making.

The scholar will gain experience with:

• Literature review: Identifying, reading, and synthesizing research on teacher self-efficacy, phenomenon-driven instruction, NGSS-aligned agriscience instruction, and culturally relevant teaching practices.

• Research instrument development: Developing and refining a follow-up survey and interview protocol that align with the study's research questions.

• Human subjects research and IRB processes: Collaborating on a modification to an existing approved IRB protocol, including learning how research questions, instruments, recruitment, consent, and data protection are documented.

• Mixed-methods research design: Learning how quantitative survey data and qualitative interview data can be used together to understand changes in teacher confidence and classroom practice over time.

• Descriptive statistics: Comparing teachers' current self-efficacy scores with their prior scores from the Foundations of Phenomenon course to identify changes over the past year.

• Interview methods: Conducting or co-conducting semi-structured teacher interviews, including asking follow-up questions, taking field notes, and documenting participants' experiences.

• Qualitative coding and analysis: Coding interview transcripts, developing a codebook, identifying themes, comparing interpretations across coders, and using evidence from participant responses to support findings.

• Data management: Organizing survey responses, interview recordings or transcripts, course feedback, coding documents, and analytic memos in a secure and ethical way.

• Program evaluation: Using data to understand what teachers gained from the Foundations of Phenomenon course, what changed after the course, and what additional supports may help teachers implement phenomenon-driven instruction.

• Research communication: Preparing findings for the BEACoN Symposium and, as appropriate, contributing to a conference proposal, research manuscript, or practitioner-facing resource.

Through this project, the scholar will learn how social science research can be used to understand professional learning, improve educational programs, and support more relevant and rigorous learning experiences in agriscience classrooms.

Required Courses/Experience

No prior research experience is required.

Preferred Courses/Experience

Preferred experiences or coursework include:

• Interest in education, agriculture, agriscience, science education, teacher preparation, or community-connected learning

• Coursework in agricultural education, education, psychology, sociology, communication, research methods, or statistics

• Experience with teaching, tutoring, coaching, mentoring, youth programs, FFA, 4-H, outreach, or curriculum development

• Interest in learning about qualitative research, interviews, survey data, and program evaluation

• Strong communication, organization, and follow-through

• Willingness to read scholarly literature, collaborate during mentoring meetings, and engage respectfully with teacher participants

Students do not need to be agriculture majors. A good fit would be a student who is curious about how people learn, how teachers develop confidence, and how research can be used to improve educational programs.

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Creating Better Reduced-Lactose Mexican Fresh Cheese

Milena Ramirez-Rodrigues (she/her/hers)

Food Science and Nutrition
Dairy Products Technology Center

mrami217@calpoly.edu

Research Project Description

Lactose intolerance affects more than one-third of the U.S. population, creating a growing demand for dairy products that are easier to digest without compromising quality. At the same time, the dairy industry is seeking innovative processing technologies that improve product quality, extend shelf life, and reduce food waste. This project will investigate how reducing the lactose content of milk through diafiltration, an advanced membrane filtration technology, influences the composition, quality, flavor, and storage stability of Mexican fresh cheese. Because diafiltration removes lactose while concentrating proteins, it has the potential to produce a cheese with improved nutritional value and functional properties. However, these changes may also affect texture, flavor, and shelf life, making it essential to understand how the technology influences the final product before it can be adopted by the dairy industry.
The project will compare Mexican fresh cheeses produced from milk with different lactose concentrations using pilot-scale cheesemaking at the Cal Poly Dairy Products Technology Center. The student will help manufacture cheeses from four milk treatments and evaluate how lactose reduction affects cheese composition, protein concentration, shelf life, texture, color, aroma, flavor, and overall quality. Laboratory analyses will include physicochemical measurements, microbial testing, instrumental texture and color analysis, and volatile compound analysis, followed by sensory evaluation to determine consumer acceptance. By integrating dairy processing, food chemistry, microbiology, and sensory science, this research will provide valuable information for developing high-quality reduced-lactose cheeses while contributing to more sustainable dairy manufacturing practices.

Research Scholar's role in the Project

The BEACoN Research Scholar will be actively involved in multiple stages of the project, from cheese manufacture to product evaluation and data interpretation. The student will assist with pilot-scale production of reduced-lactose Mexican fresh cheese using milk treatments with different lactose concentrations, including control milk, diafiltered milk, and lactose-free milk produced through enzymatic hydrolysis. During cheese manufacture, the student will help prepare milk treatments, monitor processing conditions, assist with coagulation, curd cutting, whey drainage, salting, molding, packaging, and refrigerated storage.

The student will also participate in laboratory analyses to evaluate how lactose reduction affects cheese quality and shelf life. These activities may include measuring cheese composition, pH, water activity, color, texture, microbial quality, and storage stability over time. In addition, the student will assist with sample preparation for volatile compound analysis and sensory evaluation to better understand how lactose reduction influences aroma, flavor, texture, and consumer perception. Throughout the project, the scholar will learn basic principles of experimental design, data organization, statistical analysis, laboratory safety, and scientific communication. By the end of the project, the student is expected to contribute to data interpretation and presentation of results through a poster presentation and written research report.

Skills the Research Scholar will Gain

The BEACoN Research Scholar will develop a broad range of technical, analytical, and professional skills through hands-on participation in an applied food science research project. The student will gain experience in dairy processing by manufacturing pilot-scale Mexican fresh cheese and will learn laboratory techniques commonly used to evaluate food quality, including measurements of composition, pH, water activity, texture, color, and microbial quality. The student will also be introduced to analytical methods used to characterize volatile flavor compounds and will participate in sensory evaluation to assess consumer perception of cheese quality. These experiences will provide practical training in food chemistry, microbiology, and sensory science while exposing the student to the operation of pilot-scale food processing equipment and modern analytical instrumentation.

Beyond laboratory methods, the student will develop essential research skills, including experimental design, sample preparation, accurate record keeping, and data management. The scholar will learn how to organize and analyze experimental data using appropriate statistical methods to compare treatments and determine whether observed differences are statistically significant. They will also gain experience interpreting scientific results, troubleshooting experimental challenges, and communicating research findings through laboratory meetings, presentations, and a final poster and written report. Together, these experiences will strengthen the student's critical thinking, problem-solving, teamwork, and scientific communication skills while providing a strong foundation for future academic and professional opportunities.

Required Courses/Experience

Candidates should have an interest in food science, dairy products, and laboratory work, as well as proficiency in reading, writing, speaking, organization, and the ability to carefully follow laboratory protocols and work effectively as part of a research team.

Preferred Courses/Experience

Preferred preparation includes coursework or experience in food science, dairy science, food chemistry, microbiology, sensory evaluation, statistics, or basic laboratory techniques.

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Toward Structure-Informed Design: An Open Source Platform for Form, Material, and Fabrication

Hua Chai (he/him)

Department of Architecture

huchai@calpoly.edu

Research Project Description

Every structure has to stand up, but the choices that decide how efficiently it does so are usually made late, after the shape is already locked in. This project starts from a different question: what if a designer could explore structurally efficient forms from the very first sketch, and immediately see how those forms could actually be built with real materials and real connections? We are developing a free, web-based tool that lets designers "find" efficient structural shapes using a visual, geometry-based method, then links those shapes directly to material choices and fabrication-ready details for tools like CNC routers, welders, and 3D printers. The goal is to bring form, material, and fabrication together from the start, instead of treating them as separate steps.

A BEACoN Research Scholar on this project will help build and test the platform at the intersection of architecture, engineering, and computation, work that spans 3D geometry, hands-on prototyping and fabrication in the CAED shops, structural load-testing, and coding. Powerful structural design software is usually expensive and hard to access. Hence, part of our aim is to make these capabilities available in a free tool that runs in any browser, something any student or small practice can use, wherever they are. Students drawn to sustainable design, digital fabrication, structural engineering, programming, or the growing overlap between them will find real work to contribute to, and skills they can carry forward.

Research Scholar's role in the Project

The BEACoN Research Scholar will be a hands-on contributor to the phases, including the design, fabrication, and structural testing of physical joint specimens, and the documentation of that work into a publicly shared catalog. Their involvement spans the full research cycle, from making things in the shop to interpreting data, and is structured to grow in independence over the year.

Because the scholar joins in late October, the fall serves as an onboarding and design-and-build ramp. The scholar will help design and begin fabricating structural joint specimens across three materials: timber, steel, and concrete, using CAED's fabrication infrastructure. This means translating digital joint geometries into physical parts, preparing stock and formwork, and producing specimens with the geometric precision required to match the platform's computational outputs, while maintaining a careful fabrication log of each specimen's geometry, materials, and preparation. Some of this design and fabrication work will carry into the spring, giving the scholar continuity across the two semesters rather than a hard handoff.

In the spring, the scholar will complete the remaining fabrication and enter the empirical and dissemination phases of the project. They will participate in load-testing specimens to failure on a universal testing machine, helping set up test fixtures, running monotonic loading, and capturing the resulting data: force-displacement curves, peak capacity, initial stiffness, and failure mode. A significant part of this work is disciplined documentation: photographing and categorizing each failure, and organizing results in a material-joint catalog and a structured dataset used to train the project's machine-learning models. Scholars with interest can also assist with structuring that dataset and reviewing model predictions against the physical results. Alongside the testing, the scholar will provide structured usability feedback on the web platform from a student designer's perspective, testing whether the form-finding and joint-generation tools are actually understandable and useful to someone learning them, and help prepare the open-access catalog and project materials for public release. Scholars will be encouraged and supported to co-author or present this work, for example at a student research showcase or through the conference.

Throughout, the scholar will meet with me regularly for direct mentorship and work alongside the undergraduate research assistants, providing them with an embedded peer group. Over the year, the scholar can expect to: (1) fabricate and document physical joint specimens, (2) execute and record structural load tests, (3) organize experimental data for analysis and machine-learning use, (4) evaluate and give feedback on the design platform, and (5) participate in disseminating results. The role is designed so a motivated student builds these skills through the work itself.

Skills the Research Scholar will Gain

• Experimental methods. The scholar will learn the full workflow of a destructive materials experiment: preparing standardized specimens, mounting them in a universal testing machine (a standard laboratory instrument that applies controlled, measured force until a material fails), running a consistent loading protocol, and recording the response. This is hands-on training in controlled experimentation, defining a procedure and holding conditions consistent so results are comparable across specimens, the same fundamentals used across the physical sciences and engineering. Along the way, they will also gain digital fabrication skills (CNC router, laser cutter, welding, concrete casting) and learn to translate a digital 3D model into a physically accurate object within real material tolerances.

• Quantitative analysis and basic statistics. Each test produces a force-displacement curve, from which the scholar will extract quantitative metrics: peak load capacity, initial stiffness (the slope of the curve's linear region), and energy absorbed. They will learn to compare outputs across specimens and materials and to reason about measurement variability and uncertainty.

• Research data management. A core deliverable is a structured, reusable dataset, so the scholar will learn to organize experimental records systematically: consistent naming and metadata for each specimen (material, joint type, geometry, test conditions), version-controlled documentation, and the discipline of recording sufficient context so that another researcher can interpret the data later. They will see why the same results must be structured differently for a human-readable catalog versus a machine-readable dataset.

• Qualitative categorization. Not all of the data is numeric. The scholar will photograph and classify failure modes, the distinct ways a joint gives way, into a consistent categorical scheme. This is genuine qualitative analysis: developing and applying a coding framework, making reliable judgments about which category an observation belongs to, and documenting the visual evidence for each call.

• Beyond these, the scholar will also practice usability evaluation (producing structured, actionable feedback on the research software) and scientific communication (contributing to an open-access catalog and potentially presenting or co-authoring the work).

Required Courses/Experience

The project is a natural fit for students in Architecture (ARCH) or Architectural Engineering (ARCE), but is open to students from other majors, including Computer Science, Mechanical or Civil Engineering, or others, who are drawn to the making, testing, or computational sides of the work. Students who have completed a design studio, an introductory structures course, or any hands-on fabrication or shop experience will find some of the tasks familiar, and students with any programming or data experience may take on more of the dataset and platform-evaluation work. What matters most is genuine interest in structural design, digital fabrication, computation, or their overlap, along with reliability, curiosity, and a willingness to learn hands-on in shop and lab settings.

Preferred Courses/Experience

• Completion of an introductory structures or statics course, which gives useful grounding in how forces move through a structure.

• A design studio or any hands-on fabrication, shop, or making experience such as woodworking, welding, 3D printing, model-building, or similar, since much of the work is physical.

• Familiarity with fabrication equipment, such as CNC routers, laser cutters, woodshops, or concrete labs.

• Any programming or data experience (e.g., Python, spreadsheets, or basic scripting) that would enable the scholar to take on more of the dataset organization and platform evaluation work.

• Interest in sustainable design, structural engineering, computational design, or digital fabrication.

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Drawing Collective Practice: Recovering Inclusive Histories of Participatory Urbanism

Gonzalo José López Garrido (he/him)

Architecture

golopezg@calpoly.edu

Research Project Description

How can drawings help make participation more visible, inclusive, and actionable? D"rawing Collective Practice" explores how visual methods can be used to document, analyze, and communicate participatory design practices.

Rather than treating architectural drawing only as a way to represent buildings, the project investigates drawing as a research tool that can reveal relationships between communities, institutions, designers, resources, and systems of power.

This research is supported by a 2026–27 CAED Teacher-Scholar Award, which funds the development of the book manuscript, under contract, and its visual research framework. The BEACoN Research Scholar will join this larger research initiative alongside another funded student researcher, becoming part of a collaborative team investigating participatory urbanism through archival research, interviews, historical mapping, and diagrammatic representation.

The project focuses on community design, collective agency, and the role of women and historically underrepresented actors in shaping participatory practices in the built environment. Students interested in architecture, planning, urban studies, representation, design justice, community engagement, or visual storytelling are encouraged to apply.

Research Scholar's role in the Project

The BEACoN Research Scholar will work collaboratively with another undergraduate researcher supported through the CAED Teacher-Scholar Award.

Together, they will contribute to the project's visual and archival research while assuming complementary responsibilities. The BEACoN student will focus on archival research, literature review, interview preparation, transcription, and the development of diagrams and historical maps, while collaborating on the synthesis of research findings and preparation of materials for publication and public presentation.

Working within a small research team will expose the student to collaborative research practices, peer learning, and interdisciplinary workflows that mirror professional and academic research environments. By joining an active research project already under contract for publication, the student will gain first-hand experience of the complete research lifecycle—from archival investigation and visual analysis to manuscript development, editorial revision, and scholarly dissemination.

Skills the Research Scholar will Gain

The student will gain experience in design-based research, archival research, qualitative analysis, and visual communication. They will learn how to organize and interpret historical material, synthesize interview content, and translate complex social and institutional processes into diagrams and maps. They will also develop skills in visual storytelling, research documentation, and critical analysis of participatory design practices.

In addition, the student will gain experience with research workflows such as source management, annotation, diagram iteration, and preparing material for public presentation. Depending on their background, they may use tools such as Adobe Illustrator, InDesign, Photoshop, GIS-based mapping platforms, or other visual production software. More broadly, the student will learn how design research can engage questions of equity, community agency, and inclusive knowledge production.

Required Courses/Experience

No prior research experience is required. The student should have an interest in design, cities, representation, community engagement, or social equity in the built environment. They should be willing to work independently, participate in regular meetings, and develop visual and written research materials over time.

Preferred Courses/Experience

Preferred experience includes coursework or interest in architecture, planning, landscape architecture, ethnic studies, geography, urban studies, history/theory, or design representation.

Familiarity with visual communication tools such as Adobe Illustrator, InDesign, Photoshop, GIS, Rhino, or mapping software would be helpful, but is not required. Experience with archival research, interviews, community engagement, or design justice topics would also be valuable.

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Who Feels Like an Engineer? A Quantitative Analysis of Engineering Identity and Sense of Belonging Across Academic Majors and Demographic Groups

Puneet Agarwal (he/him/his)

Industrial and Manufacturing Engineering

pagarw05@calpoly.edu

Research Project Description

Engineering is about more than solving technical problems, it is also about developing the confidence to see yourself as an engineer and feeling that you belong within the engineering community. Research has shown that students who develop a strong engineering identity and a sense of belonging are more likely to persist in their degree programs and pursue engineering careers. However, these experiences can vary across academic majors, class standing, gender, and other demographic backgrounds. This project investigates how engineering students experience identity and belonging, with the goal of understanding the factors that foster student success, retention, and inclusion across engineering disciplines.

Students working on this project will gain hands-on experience with educational research by analyzing survey data collected from engineering students, performing statistical analyses, and exploring qualitative responses about students' experiences. They will learn how to use data visualization, statistical methods, and AI-assisted text analysis to identify patterns in student experiences and evaluate the effectiveness of programs such as student organizations, faculty mentoring, and academic support services. The findings will help inform strategies for creating more inclusive and supportive engineering environments, ultimately contributing to improved student success, retention, and the development of a stronger and more diverse engineering workforce. A major objective of this project is to produce high-quality, publishable research and submit the findings to the Journal of Engineering Education, the flagship journal of the American Society for Engineering Education (ASEE) and one of the world's most prestigious journals in engineering education research. Students will have the opportunity to contribute to all phases of the research process, including data analysis, manuscript preparation, and publication.

Research Scholar's role in the Project

The BEACoN Research Scholar will play an active role in this engineering education research project by investigating how engineering students develop a sense of engineering identity and belonging, and how these experiences vary across majors, academic levels, gender, race/ethnicity, and other demographic groups. The student will help clean and organize survey data, conduct descriptive and statistical analyses, create tables and data visualizations, and interpret research findings. The student will also analyze open-ended survey responses to identify themes related to belonging, inclusion, faculty support, peer relationships, student organizations, and departmental culture.

The student will work closely with the faculty mentor through regular meetings to learn research methods, data analysis techniques, and academic writing skills. A primary goal of the project is to prepare and submit a manuscript to the Journal of Engineering Education, the flagship journal of the American Society for Engineering Education (ASEE). As part of this effort, the student will contribute to the publication by conducting literature reviews, coding qualitative data, creating publication-quality figures and tables, summarizing research findings, and assisting with drafting and revising the journal manuscript.

Skills the Research Scholar will Gain

The BEACoN Research Scholar will develop a broad set of research, analytical, programming, and communication skills. The student will gain experience in:

1. Research Design: Understanding survey-based research, study design, ethical research practices (IRB protocols), and data collection methods.

2. Data Management: Cleaning, organizing, and preparing real-world survey data for analysis using spreadsheets, Python, and statistical software.

3. Data Analysis with Python: Using Python libraries (e.g., Pandas, NumPy, Matplotlib, Seaborn, SciPy, and Statsmodels) for data cleaning, statistical analysis, visualization, and reproducible research workflows.

4. Quantitative Data Analysis: Applying descriptive statistics and exploratory data analysis to summarize and understand complex survey data.

5. Statistical Analysis: Performing statistical significance testing (e.g., t-tests, chi-square tests, and ANOVA), post hoc comparisons, and regression analyses to identify significant relationships and differences among student groups.

6. Data Visualization: Creating clear, publication-quality figures, tables, and charts that effectively communicate research findings.

7. Qualitative Data Analysis: Coding and analyzing open-ended survey responses, identifying recurring themes, and interpreting qualitative data using established research methods.

8. AI-Assisted Research: Learning how to use generative AI tools responsibly to assist with qualitative coding, theme identification, literature synthesis, and research productivity while maintaining rigorous human oversight.

9. Literature Review: Conducting comprehensive reviews of engineering education literature to understand current research, identify knowledge gaps, and place findings in context.

10. Scientific Writing: Writing and revising sections of a peer-reviewed journal manuscript, including the introduction, methods, results, discussion, and conclusion.

11. Research Communication: Presenting research findings in written and visual formats suitable for academic conferences and journal publications.

Required Courses/Experience

Applicants should have completed at least one undergraduate course in statistics, data analytics, programming (preferably Python), or a related quantitative subject. Students should have basic computer skills, be comfortable working with data, and demonstrate strong analytical thinking, attention to detail, and a willingness to learn new research methods and software. An interest in engineering education, data analysis, and writing a peer-reviewed research paper is required, as the student will actively contribute to the preparation of a journal manuscript.

Preferred Courses/Experience

Preference will be given to students who have completed coursework in statistics, data science, machine learning, or data analytics. Experience using Python (e.g., Pandas, NumPy, Matplotlib, SciPy, and Statsmodels) for data analysis, as well as familiarity with statistical software (e.g., R, SPSS, or JMP), is desirable. Experience with survey research, qualitative data analysis, literature reviews, scientific writing, or data visualization is also beneficial.

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Using Data Science and Network Analysis to Model an Engineering Curriculum

Megan Chan (she/her/hers)

Industrial and Manufacturing Engineering

mchan54@calpoly.edu

Research Project Description

Have you ever tried to plan your courses using a flowchart that doesn't match your reality? Maybe a required course was full, you came in with AP credits, or you switched majors — and suddenly the "official" four-year plan didn't fit. You're not alone: most students' actual paths through their degree look different from the path on paper, and those detours can cost real time and money. Yet universities have surprisingly few tools for seeing how students actually move through their programs, or for using that knowledge to help the next student.

This project builds edSPARK, a tool that maps a curriculum as a network — courses as nodes, prerequisites as connections — to visualize how a degree program fits together. Because Cal Poly just converted to semesters, every flowchart, prerequisite chain, and course number changed at once. As a BEACoN Scholar, you'll build the first network map of the new semester curriculum for an engineering program, working with Cal Poly's course catalogs, learning how to wrangle messy real-world data, and using network analysis to find bottleneck courses and hidden constraints in the new design. You'll practice data visualization skills (Python, network analysis, interactive visualization) and present at a research venue. Your work will become the foundation for a larger research effort to make degree pathways clearer and fairer for the students who come after you.

Research Scholar's Role in the Project

The BEACoN Research Scholar will take ownership of building a curriculum data pipeline and network representation for one Cal Poly degree program, progressing through four phases: (1) data extraction and standardization, (2) network construction, (3) visualization, and (4) documentation and dissemination. Phases 1–2 will occupy the final five weeks of fall semester; phases 3–4 will span spring semester.

1. Extracting and standardizing data: Using public course catalogs, curriculum flowcharts, and schedules, the scholar will extract course, prerequisite, and scheduling data and standardize it into a documented data model — including mapping quarter-system courses to their new semester equivalents.

2. Constructing the curriculum network: The scholar will represent the curriculum as a directed graph (courses as nodes, prerequisites as edges) and compute structural measures such as centrality, density, and clustering.

3. Building a visualization: The scholar will co-develop an interactive visualization of the curriculum network and simulated or aggregated student trajectories using tools such as R Shiny, gathering informal design feedback from the faculty mentor and departmental colleagues.

4. Documentation and dissemination: The scholar will produce documented, reproducible code and a reusable dataset, and will present their work at a campus research venue (e.g., the Cal Poly Student Research Conference), with a pathway to co-authorship on resulting publications.

Skills the Research Scholar will Gain

Data management: The scholar will extract, clean, and standardize curricular data from public catalogs and schedules using tools such as the Python pandas library, learning reproducible data-preparation practices including documentation and version control (i.e., Git).

Network analysis: The scholar will learn to represent a curriculum as a directed graph and apply methods from network science, such as measuring centrality or shortest paths, to characterize program structure. This is the project's core analytic skill and one rarely available to undergraduates.

Data modeling: The scholar will design a data model handling real-world messiness: course renumbering across the quarter-to-semester transition, cross-listings, substitutions, and catalog versioning — directly transferable to database and analytics roles.

Software development and visualization: The scholar will co-develop an interactive visualization in software such as R Shiny, learning to translate network data into interpretable interactive graphics and iterate on design in response to feedback.

Required Courses/Experience

Completion of at least one programming course, in any language — e.g., CSC 1001 (Fundamentals of Computer Science), CSC 1032 (Programming for Scientists and Engineers), or equivalent. Comfort writing and debugging basic scripts.

Preferred Courses/Experience

Experience manipulating tabular data (e.g., data frames in Python or R), such as through IME 2212 (Introduction to Enterprise Analytics and Database Systems) or CSC 2600 (Computing with Data). Interest or coursework in networks, data visualization, human-computer interaction, or building interactive dashboards.

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Explaining Bounded-Suboptimal Search Through Heuristic Error Landscapes

Kirk Duran(he/him)

Computer Science & Software Engineering

kduran02@calpoly.edu

Research Project Description

Heuristic search algorithms are used in artificial intelligence to solve problems with many possible paths, such as puzzles, planning, navigation, scheduling, and robotics. These algorithms rely on heuristics, or educated guesses, to decide which paths are worth exploring. In this project, the student will create a detailed "heuristic error map" for the 3x3 sliding tile puzzle by comparing the Manhattan distance heuristic to the true optimal distance from each puzzle state to the goal. This map will help show when the heuristic is accurate, when it underestimates difficulty, and when it may mislead a search algorithm.

The student will then use Fast Downward, a widely used planning system, to study how A*, Weighted A*, and Greedy Best-First Search perform using the same heuristic. Rather than simply comparing which algorithm is fastest, the project asks why the algorithms behave differently by connecting their performance to the underlying heuristic error. The project also highlights a resource-conscious side of AI: instead of relying on larger models and more computing power, it studies how careful algorithm design can make search more efficient, interpretable, and accessible.

Research Scholar's role in the Project

The BEACoN Research Scholar will help carry out the project's experimental workflow from setup through final presentation. The student will use Python to represent 3x3 sliding tile puzzle states, generate valid puzzle configurations, compute Manhattan distance values, and organize the true optimal distance to the goal for each state. The student will use these values to build a heuristic error dataset, where each puzzle state is labeled with its true distance, Manhattan distance, and heuristic error.

The student will use Fast Downward to run A*, Weighted A*, and Greedy Best-First Search on selected puzzle instances. They will run Weighted A* with multiple weight values so the project can compare how different levels of heuristic weighting affect search behavior. For each algorithm and puzzle instance, the student will record node expansions, runtime, solution cost, optimal cost, and suboptimality.

The student will use Python, spreadsheets, and/or Jupyter notebooks to clean, organize, and analyze the experiment results. They will create graphs and tables comparing algorithm behavior against heuristic error. These analyses will be used to answer the project's main question: how does the accuracy or inaccuracy of a heuristic help explain the performance of different search algorithms?

The student will meet regularly with the faculty mentor to review progress, troubleshoot issues, interpret results, and prepare final research materials. The student will contribute to a final poster, report, and/or presentation for the BEACoN Research Symposium.

Skills the Research Scholar will Gain

The BEACoN Research Scholar will gain practical research skills in artificial intelligence, algorithm analysis, experimental design, data analysis, and technical communication.

The student will learn how heuristic search algorithms such as A*, Weighted A*, and Greedy Best-First Search make decisions, and how Manhattan distance can be used to estimate progress toward a goal. They will also learn how to measure heuristic error by comparing that estimate to the true optimal distance.

The student will gain experience running controlled computational experiments, recording results such as node expansions, runtime, solution cost, and suboptimality. They will organize results into structured datasets, clean and validate the data, calculate summary measures, and create graphs and tables to identify patterns.

The student will also develop communication skills by documenting methods, explaining results, preparing figures, and presenting the project at the BEACoN Research Symposium. These skills will prepare the student for future research, graduate study, or technical work involving data, algorithms, and AI systems.

Required Courses/Experience

Interest in artificial intelligence, algorithms, or problem solving
Completion of, or current enrollment in, CSC 480 or equivalent AI-related coursework
Experience programming in Python and C++
Familiarity with Git for version control
Willingness to learn new software tools and work carefully with experimental results

Preferred Courses/Experience

Experience in artificial intelligence research
Completion of CS 480 and CS349
Fluency Python and C++
Fluency with Git for version control

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Using Deep Learning Models to Reveal Insights into Understudied Diseases

Borislav Hristov (he/him/his)

Computer Science and Software Engineering

bhristov@calpoly.edu

Research Project Description

The rapid advancement of artificial intelligence and deep learning has dramatically reshaped the way biomedical research is conducted. Today, billion-parameter deep learning models are being trained to predict protein binding sites, identify functional genomic elements, and evaluate the efficacy of synthetic drugs. Yet, this technological progress has not been equitably distributed. Malaria, for example, is a mosquito-borne infectious disease caused by Plasmodium parasites and is responsible for more than half a million deaths each year, the vast majority of which occur in sub-Saharan Africa. Despite this burden, research on malaria remains underfunded, while many computational resources continue to be concentrated on medical challenges most relevant to North America and Europe.

In this project, we aim to address this disparity by developing a novel deep learning framework to generate new insights into understudied diseases. Specifically, our model will investigate the role of three-dimensional DNA architecture in the onset and progression of malaria. We will computationally integrate several large-scale public datasets and use autoencoder-based models to extract informative vector representations of RNA-DNA binding changes. Ultimately, our goal is to develop a model that can relate changes in DNA structure to the expression of virulence genes used by Plasmodium parasites to evade the host immune system. We hope this work will lay the foundation for broader use of advanced deep learning technologies in the study of understudied diseases.

Research Scholar's role in the Project

The student will play a pivotal role in multiple phases throughout the entire research process. Their responsibilities will include:

• Data Collection and Analysis: processing and integrating several large biological datasets, preparing statistics, and eliminating data bias. The insights gathered here will directly guide the next iteration of the project, making the student's work integral to the project success

• Design and Implementation of the Bioinformatics Pipeline and ML Model: developing the PyTorch code of the machine learning deep model as well as designing scripts to convert the data into input vectors for the model. A critical step is the implementation of evaluation metrics/functions that assess in a rigorous and unbiased way the performance of the model

• Training and Optimization of the Deep Learning Model: training the model using the UC San Diego Supercomputer, performing hyperparameter search, evaluating performance according to the metrics developed

• Drafting a Project Report: writing a comprehensive draft that presents the project's findings. This involves articulating the research problem, methodology, results, and conclusions in a clear and organized manner. This experience is designed to hone the student's scientific communication skills, a key skill for any research career.

This role will provide the student with valuable hands-on experience in the entire research cycle, from initial development and data collection to the presentation of results, thereby equipping them with essential skills for future research endeavors.

Skills the Research Scholar will Gain

Undergraduate participants will gain hands-on experience in key areas of bioinformatics research, such as:

• Data Collection & Curation: Gathering, integrating and managing data using both large public repositories (i.e GenBank, 4DN consortium) as well as small RNA-specific experiments

• Bioinformatics Software Development: Understanding the inner workings of bioinformatics computational pipelines and how to execute them in a dedicated large-scale computing facility (UCSD Expanse Supercomputer)

• Algorithmic Design & Implementation: Designing and implementing a novel machine learning models

• Research & Collaboration: Building the communication and technical reading skills essential for successful academic collaboration

Through this project, students will gain practical expertise in programming and running large scale computational pipelines, working with massive biological datasets, and utilizing debugging tools in a supercomputer. By implementing and refining deep learning algorithms for modeling the effects of 3D DNA changes in disease, they will engage in effective research techniques. Furthermore, collaboration via GitHub and regular practice presentations will enhance their ability to work effectively in a team and communicate results clearly.

Required Courses/Experience

• Python (significant coding experience)

• No prior biological experience required (curiosity about how computer science models can illuminate biological processes at a cellular level)

• Strong critical thinking skills

Students with experience in quantitative research methods, data analysis, or academic writing will be well-positioned to succeed, but I am also open to mentoring motivated students eager to develop these skills throughout the project. The scholar should also be comfortable engaging with academic literature, communicating thoughtfully, and working both independently and collaboratively.

Preferred Courses/Experience

• PyTorch (or TensorFlow) as well as working with unix-based systems

Preferred coursework or gained experience in areas related to deep learning, artificial intelligence, bioinformatics and data analysis.

Because this research is interdisciplinary in nature, students from a wide range of academic backgrounds are encouraged to apply, particularly those who are passionate to learn how machine learning can be applied to study diseases at a molecular level.

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Interactive Building Energy Explorer: Evaluating Accessible Visualizations for Energy Literacy

Irene Humer 

Computer Science and Software Engineering

ihumer@calpoly.edu

Research Project Description

Buildings use energy in ways that are often difficult to see directly. Choices about insulation, windows, shading, foundation type, heating, cooling, and everyday use patterns can affect both indoor comfort and energy demand, but these relationships are often hidden behind technical models or engineering calculations. This project will develop and evaluate an Interactive Building Energy Explorer: a web-based visualization tool that helps students and non-expert users explore how building choices affect comfort, efficiency, and responsible energy use.

The research goal is to study whether interactive scientific visualizations can improve energy literacy and help users reason more clearly about building-energy tradeoffs. The BEACoN Research Scholar will help develop the prototype, create guided scenarios, and prepare a classroom user study to evaluate whether the tool supports users’ understanding of concepts such as heat flow, insulation, shading, and heating/cooling demand. Possible study measures include pre/post concept questions, scenario-based prediction tasks, usability feedback, and short written reflections. The final outcome will include a working prototype, documented code, guided scenarios, preliminary user-study results, and a BEACoN research poster.

Research Scholar's role in the Project

The BEACoN Research Scholar(s) will contribute to the design, implementation, testing, and evaluation of an interactive scientific-computing tool for energy literacy. The project has two major technical components: a simplified building-energy simulation model and an interactive web-based visualization interface.

If two students are matched to the project, one student will focus primarily on the scientific-computing and modeling side. This student will help develop a simplified computational model for indoor temperature behavior and basic energy-demand comparisons. The model will be designed to be physically meaningful but lightweight, with the goal of supporting scenario-based exploration rather than serving as a detailed engineering calculator. This student may work on modeling heat flow, insulation effects, shading effects, heating or cooling choices, parameter selection, numerical implementation, and validation of whether the simulation behaves in reasonable and interpretable ways.

The second student will focus primarily on the interactive website and visualization side. This student will help translate the simulation results into a web-based prototype with user-adjustable controls for insulation, window placement, shading, foundation type, and heating or cooling choices. They may create visual outputs such as heat maps, side-by-side scenario comparisons, comfort and energy summary indicators, and guided prompts that help users reason about building-energy tradeoffs. This student will also help refine the interface for clarity, accessibility, and usability.

If only one student is matched to the project, the scope will be narrowed to a smaller prototype with a limited set of building features, guided scenarios, and evaluation materials. In that case, the student will still gain experience with both the simulation/modeling and visualization/interface components, but the technical scope will be adjusted to fit the available time.

A central research component of the project will be evaluating whether the tool helps users better understand building-energy concepts. The student(s) will help prepare study materials for use in a Spring course, such as guided activities, pre/post concept questions, usability questions, and short reflection prompts. If formal data collection is pursued for dissemination or publication, IRB approval will be obtained before research data are collected. During Spring, the student(s) will help organize and analyze pilot data, summarize usability feedback, create figures, and prepare results for the BEACoN Research Symposium. Depending on progress, the work may also contribute to a future conference paper or educational research publication.

Skills the Research Scholar will Gain

The BEACoN Research Scholar(s) will gain experience in scientific computing, numerical modeling, web-based visualization, interface design, user-study design, data analysis, and research communication. Depending on the student’s role, one student may focus more deeply on the computational modeling side, while another may focus more deeply on the visualization and web-development side. If only one student is matched, the project will be scaled so that the student gains experience with a manageable combination of these skills.

On the modeling side, the student will learn how simplified computational models can represent physical processes such as heat flow, energy loss, indoor comfort, insulation effects, shading, and heating or cooling demand. They will learn how to make modeling choices, test whether a simulation behaves reasonably, document assumptions, and distinguish between an exploratory educational model and a detailed engineering prediction.

On the visualization and interface side, the student will learn how technical simulation results can be translated into interactive visualizations that are understandable to broad audiences. Technical skills may include Python programming, JavaScript or web development, Jupyter notebooks, numerical modeling, data visualization, interface design, version control, code documentation, and basic usability testing.

The student(s) will also gain experience with research design by helping develop pre/post concept questions, scenario-based tasks, usability questions, and written reflection prompts. They will practice data management and analysis by organizing pilot user-study responses, summarizing quantitative survey or quiz results, and interpreting qualitative written feedback. They will also develop communication skills by preparing clear figures, explaining technical results to non-expert audiences, and presenting their work in a final research poster. These skills are transferable to computer science, software engineering, engineering, sustainability, data science, human-computer interaction, computing education, and scientific visualization.

Required Courses/Experience

No prior research experience is required. The student should have completed at least one introductory programming course, or have equivalent experience with basic programming concepts such as variables, loops, functions, conditionals, and working with data. The student should also have an interest in computing, visualization, sustainability, scientific modeling, education, or public-facing technology, and a willingness to learn new technical skills. The project will include structured onboarding and can be adapted to the student’s preparation.

Preferred Courses/Experience

Preferred but not required experiences include coursework or experience in Python, JavaScript, web development, data visualization, numerical methods, physics, engineering, environmental studies, sustainability, human-computer interaction, software engineering, or statistics. Coursework in data structures, scientific computing, object-oriented programming, front-end development, or human-centered design would be useful, but is not required. Experience with Jupyter notebooks, plotting libraries, surveys, usability testing, or basic heat-transfer and energy concepts would also be helpful.

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Support Structures for Equitable Student Success: Evaluating the Effectiveness of an Engineering Pre-Calculus Lab Course on First-Year Engineering Student Success

Nicole Johnson-Glauch (she/her/hers)

Materials Engineering

njohns66@calpoly.edu

Research Project Description

We invite you to join a project that helps Cal Poly support engineering students in their first year by evaluating the effectiveness of an Engineering Pre-Calculus Lab course (ENGR 2271) designed to support students enrolled in pre-calculus. Engineering programs are designed with the assumption that students will start in Calculus I. However, students enter with different levels of mathematics preparation. These differences in preparation can create additional barriers for students in their first year that may lead to delayed graduation, especially for first-generation students. To address these challenges, the College of Engineering developed ENGR 2271 to help students become more confident in math, develop self-regulated learning techniques to perform better in their first-year math courses, and increase their sense of belonging at Cal Poly.

As part of this project, you'll collect and analyze data related to students' experience in the Engineering Math lab course. You'll administer surveys and conduct interviews with students. You will analyze the surveys using statistical analysis techniques and the interviews using qualitative data analysis. We will then combine these findings together to understand how and why this course benefits students. We are particularly interested in exploring the ways this course serves first-generation students and identifying ways to strengthen its impact. Your work will contribute to creating tools and policies that help ensure that all aspiring engineering students have the support they need to thrive at Cal Poly.

BEACoN Scholar's role in the Project

The student on this project will engage in all aspects of the research process, including:

1. Conducting a literature review on research related to engineering math readiness interventions and their effectiveness, mathematics confidence, sense of belonging, and self-regulated learning strategies.

2. Collect data by administering surveys and conducting interviews in ENGR 2271 in Fall 2026 and in their calculus course in Spring 2027.

3. Analyze survey data using appropriate statistical techniques such as t-tests, ANOVA, Chi-Square Tests for Independence, and regression analysis.

4. Analyze interview data to identify themes related to how ENGR 2271 promotes mathematics confidence, sense of belonging, and self-regulated learning techniques for students from different backgrounds.

5. Present their work at a local engineering education research conference. This conference will most likely be the Pacific Southwest Zone Conference of the American Society for Engineering Education.

Skills the BEACoN Scholar will Gain

Students will gain the following skills:

1. Writing a literature review

2. Developing research questions

3. Conducting structured interviews

4. Administering research surveys

5. Qualitative analysis methods for interview data: thematic analysis

6. Quantitative analysis methods for survey data and mathematics course grades data: t-tests, ANOVA, Chi-Square Tests for Independence, and regression analysis as appropriate to their research question.

7. Data management as related to IRB and human subjects research requirements

8. Technical communication: research poster for BEACoN and ASEE conference, research paper for ASEE conference, and presentation to ENGR 2271 instructor Dr. Eric Ocegueda and Associate Dean Zoe Wood

Required Courses/Experience

None

Preferred Courses/Experience

The following are preferred:

1. Experience with programs supporting first-generation students

2. Experience conducting and analyzing interviews with human subjects

3. Experience with statistical analysis techniques for survey data

4. Desire to pursue a career related to STEM education or STEM education research (engineering education research, K-12 STEM teaching, STEM outreach non-profits, etc…)

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Designing Interactive Extended Reality Visualizations for Safety and Accessibility Guidance

Fahim Khan (He/him/his)

Computer Science and Software Engineering

fkhan19@calpoly.edu

Research Project Description

Extended reality (XR), including augmented reality (AR) and mixed reality (MR), is transforming how people interact with digital information in the real world. Instead of looking at a phone screen, users can receive important information directly within their field of view through devices such as XR headsets (Such as Meta Quest 3) and wearable XR glasses. This project explores how artificial intelligence (AI) and computer vision can be combined with XR to create interactive visual guidance for real-world safety and accessibility applications.

The project builds upon existing AI systems that detect coastal hazards such as rip currents, as well as accessibility-related infrastructure including curb ramps, crosswalks, sidewalk conditions, and obstacles. Rather than developing new AI models, this project focuses on designing immersive visualization techniques for XR interfaces that effectively communicate AI-generated information to users. The goal is to determine how spatial visualizations, interactive cues, and context-aware overlays can help people better understand their surroundings and make informed decisions.

Students will develop interactive prototypes using Unity and industry-standard XR development tools for XR headsets and wearable XR glasses (all devices will be provided). The project combines computer graphics, AI/ML, computer vision, and scientific visualization, giving students the opportunity to contribute to emerging technologies with applications in public safety, accessibility, environmental monitoring, and assistive computing. The resulting prototypes may serve as foundations for future research, conference publications, and real-world deployments.

Research Scholar's role in the Project

The Research Scholar will participate in multiple stages of the research process. Their responsibilities will include:

Literature Review and Design Exploration: Review prior research, including my previous work, on extended reality (XR), AI-assisted visualization, accessibility technologies, and safety guidance to understand existing approaches and identify opportunities for improvement.

XR Software Development: Design and implement interactive XR interfaces using Unity and OpenXR for Meta Quest headsets and wearable XR glasses. The student will develop visualization components that display information generated by existing AI and computer vision systems, building upon codebases and datasets developed in my previous research.

Prototype Development: Integrate AI-generated detections (such as rip current hazards or accessibility-related infrastructure) into immersive visualizations, experiment with different interaction techniques, and refine interface designs through iterative development. The student will have access to all necessary hardware and computing resources, including Meta Quest 3 headsets, XR glasses, smartphones, edge computing devices, and GPU-enabled workstations.

Documentation and Evaluation: Document software development, maintain project notes, evaluate visualization designs through demonstrations and informal usability testing, and contribute to project reports.

Research Communication: Prepare a research poster and demonstration for the BEACoN Symposium. Depending on project progress, the student may also contribute to conference papers, open-source software releases, or future research publications.

Through these activities, the scholar will gain experience across the complete research lifecycle from understanding a research problem and reviewing prior literature to building software prototypes and communicating research outcomes.

Skills the Research Scholar will Gain

• XR Software Development: Building immersive applications using technologies such as Unity, OpenXR, Meta Quest headsets, and wearable XR glasses.
• Artificial Intelligence Integration: Learning how outputs from computer vision and AI systems can be incorporated into interactive XR applications. This includes dataset curation, machine learning model training and evaluation, model deployment, and integration with XR interfaces.
• Computer Graphics and Visualization: Designing effective spatial (3D/4D) visualizations and interactive user interfaces that communicate safety and accessibility information.
• Software Engineering: Developing larger software systems using version control, debugging techniques, testing, documentation, and collaborative software development practices.
• Research Skills: Reading scientific literature, designing research prototypes, documenting technical work, and communicating research findings through presentations and posters.
• Professional Development: Strengthening project planning, technical communication, teamwork, and problem-solving skills while working closely with a faculty mentor.
• By the end of the project, the scholar will understand how AI-powered perception systems and XR technologies can work together to create intelligent, human-centered applications for public safety and accessibility.

Required Courses/Experience

This project is well suited for students interested in artificial intelligence, machine learning, computer vision, computer graphics, or extended reality. Previous research experience is not required.

Students should have completed introductory programming coursework (or have equivalent programming experience) and possess basic familiarity with programming concepts. Exposure to artificial intelligence or computer vision through coursework, personal projects, or independent learning is helpful, but students primarily need curiosity, motivation, and a willingness to learn new technologies.

Preferred Courses/Experience

Coursework or project experience in one or more of the following areas is beneficial but not required:

• Artificial Intelligence/Machine Learning/Computer Vision
• Computer Graphics
• Unity, C#, or game development
• Mobile (iOS, Android) or XR application development

Students who are excited about immersive technologies and AI applications are encouraged to apply, even if they have limited experience in these areas.

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Developing an Affordable Passive Thermosyphon Cooling System for Climate-Vulnerable Communities

Hyun Jin Kim (she/her/hers)

Department of Mechanical Engineering

jkim812@calpoly.edu

Research Project Description

Extreme heat is one of California's most pressing and rapidly growing climate challenges, disproportionately impacting low-income households that often lack air conditioning or cannot afford its operation. As a result, many residents face unsafe indoor temperatures during prolonged heat waves and power outages. This project will develop an affordable, portable, and energy-efficient cooling system that provides safe indoor thermal conditions when conventional air conditioning is unavailable or fails. The proposed technology is based on a passive thermosyphon that transfers heat through the natural circulation of liquid and vapor, eliminating the need for a compressor—the most energy-intensive component of traditional cooling systems. Combined with a compact indoor heat exchanger and an outdoor water-cooled condenser, the system is designed to deliver approximately 4,000 BTU/hr of cooling while consuming minimal electricity, requiring only a small fan and low-power controls. The target performance is to maintain a 120 ft² room below 90°F and 50% relative humidity for up to 72 hours during power outages, or below 80°F and 60% relative humidity during primary air-conditioning failure. By achieving a coefficient of performance (COP) greater than 4 and a projected cost below $300, the system is intended to provide an accessible cooling solution for communities facing the greatest heat and energy burdens.

BEACoN Scholar's role in the Project

The BEACoN Research Scholar will assist with the hands-on development and evaluation of the proposed passive thermosyphon cooling system. The student's primary responsibilities will include supporting prototype fabrication, such as assembling tube-fin evaporator and condenser components, reservoir systems, and related test hardware. The student will also help prepare the laboratory setup by installing thermocouples, humidity sensors, power meters, and data acquisition equipment. During testing, the student will run routine experiments under simulated heat-wave and air-conditioning failure conditions, monitor indoor temperature and humidity profiles, record system power consumption, and document transient cooling performance. The student will also organize experimental results, enter data into spreadsheets, generate basic plots, and assist with quality checks.

In addition to these technical tasks, the student will participate in regular project meetings, maintain laboratory notes, contribute to troubleshooting discussions, and help prepare figures or summaries for presentations and reports. These activities will allow the student to make meaningful contributions to prototype development, experimental validation, and dissemination while gaining experience in a real-world engineering project focused on climate resilience and energy equity.

Skills the BEACoN Scholar will Gain

Through this project, the BEACoN Research Scholar will develop foundational skills in thermal-fluid science, experimental research, instrumentation, and engineering data analysis. The student will learn how heat transfer, phase change, and gravity-driven fluid circulation are used in passive cooling systems. They will gain practical experience with laboratory methods such as sensor placement, calibration, uncertainty analysis, experimental repeatability, and safe operation of thermal systems. The student will also learn to use data acquisition tools, including thermocouples, humidity sensors, power measurement devices, and National Instruments hardware, while developing troubleshooting skills for wiring, signal quality, and equipment setup.

The student will also strengthen data management and communication skills by organizing experimental datasets, creating time-series plots, checking data quality, interpreting temperature, humidity, and power trends, and summarizing results for a non-specialist audience. Beyond technical training, the project will introduce the student to human-centered engineering design by connecting laboratory performance metrics to the needs of low-income households affected by extreme heat. The student will gain experience in teamwork, research documentation, technical communication, and potentially coauthoring presentations or publications, while also reflecting on the broader equity and climate adaptation goals of the work.

Required Courses/Experience

Thermodynamics
Engineering Measurement and Data Analysis

Preferred Courses/Experience

Heat Transfer
Introduction to Sustainable Energy Usage in Buildings
Thermal System Design
Heating, Ventilating, and Air Conditioning
Engineering, Design, and Social Justice
Environmentally Efficient and Sustainable Refrigeration Systems

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Hidden Connections: Exploring Ecological Networks Through Network Science

Theresa Migler (she/hers)

Computer Science and Software Engineering

tmigler@calpoly.edu

Research Project Description

Ecological systems are sustained by complex networks of interactions among species, and understanding these relationships is essential for addressing some of today's most pressing environmental challenges. Pollinator decline, biodiversity loss, invasive species, and climate change all have the potential to disrupt ecological communities in ways that are difficult to predict. Network science provides a powerful framework for studying these systems because it captures not only the presence of individual species but also the intricate web of interactions that underlie ecosystem stability and resilience. In this project, we will investigate three important classes of ecological interaction networks: Pollinator–Plant Networks, in which vertices represent plants and their pollinators and edges represent pollination interactions; Food Webs, in which vertices represent species and directed edges represent predator–prey relationships; and Host–Parasite Networks, in which vertices represent hosts and parasites and edges represent host–parasite interactions. By comparing these diverse ecological systems, students will explore how network structure influences ecosystem function and how different types of biological interactions give rise to common organizational principles.

This project provides an outstanding opportunity for undergraduate researchers to engage in interdisciplinary research at the intersection of computer science, mathematics, ecology, and data science. Students will work with publicly available ecological datasets and apply modern network analysis techniques to quantify structural properties such as centrality, modularity, nestedness, robustness, and community organization. They will investigate questions such as which species play disproportionately important roles in maintaining ecosystem stability, how resilient ecological networks are to species loss, and whether common structural patterns emerge across different ecological systems. Through this work, students will gain experience in data collection, computational analysis, scientific visualization, statistical reasoning, and the communication of research results. The project will provide a strong foundation in computational research while demonstrating how network science can be used to better understand and help protect the biodiversity upon which healthy ecosystems depend.

BEACoN Scholar's role in the Project

The undergraduate researcher will participate in all phases of the project, from an extensive review of the scientific literature to computational analysis and dissemination of results. During the first 5–10 weeks of the project, the student will immerse themselves in the current research literature on ecological interaction networks, reading and discussing seminal and recent papers on pollinator–plant networks, food webs, host–parasite networks, and network science methods. Through regular meetings with the faculty mentor, the student will develop an understanding of the major research questions, analytical techniques, and open challenges in the field. This foundation will enable the student to formulate meaningful research questions and place their work within the broader scientific context.

Building on this literature review, the student will identify and curate publicly available ecological datasets, construct network representations, and apply computational methods to analyze structural properties such as centrality, modularity, nestedness, and network robustness. Throughout the project, the student will gain experience in scientific programming, data analysis, visualization, and the interpretation of research findings. The student will communicate results through a written report and poster presentation, developing the technical and communication skills necessary for future research or graduate study.

Skills the BEACoN Scholar will Gain

The undergraduate researcher will develop skills in scientific literature review, computational programming, network analysis, data visualization, and scientific communication. Through the project, the student will gain experience conducting independent research, analyzing real-world ecological datasets, and presenting findings through written reports and poster presentations.

Required Courses/Experience

CSC 248 or MATH 248 or the equivalent.

Preferred Courses/Experience

CSC 349 (but the student could definitely take this course in the fall).

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Engineered Tissue Models for Sex-Specific Variations in Cardiac Tissue Matrix Remodeling

Luke Perreault (he/him/his)

Biomedical Engineering

lperreau@calpoly.edu

Research Project Description

There is a wealth of evidence that biological sex of study subjects such as cells, tissues, and animals can affect experimental results, and therefore sex cannot be ignored as a biological variable when designing a biomedical study. This is explicitly relevant in cardiac health and pathophysiology, with sex-related differences in cardiac structure, function, post-injury repair, and aging being reported in  multiple clinical studies, animal models, and cell-based studies. Despite this evidence, and efforts by national entities like the National Institutes of Health and scientific organizations like the American Physiological Society to standardize sex as a biological variable (SABV) in biomedical research, there remains a longstanding bias towards using male-only models in cardiac research.

The goal of this project is therefore twofold: (1) to leverage preexisting frameworks for engineered cardiac tissues toward development of sex-specific cardiac tissue models that can accurately recapitulate the mechanics and composition of biological male and female cardiac tissue, helping to advance the study of cardiovascular disease and pursue patient-specific treatment modalities. And (2) to develop recommendations and protocols to translate this research toward upper-level coursework and laboratory activities, and integrate SABV considerations into a Learn-by-Doing environment. In doing so, this project will help improve cardiac health equity and provide a foundation to educate the next generation of biomedical innovators with a sex-inclusive mindset.
 

Research Scholar's role in the Project

The BEACoN Research Scholar will contribute to both the experimental and educational goals of this project. Experimentally, the student will support isolation, expansion, and characterization of sex-specific cardiac fibroblasts from mice, which are necessary to culture physiologically-relevant engineered cardiac tissues. Further, the student will perform literature review and investigate methods to modify cardiac hydrogel (synthesized from either silk fibroin or fibrin) mechanics to mimic native cardiac tissue. The student will be trained in laboratory safety, biomaterial preparation, laboratory record keeping, and scientific literature review.

Careful record keeping and protocol development, in addition to investigation and reflection on male-sex bias in cardiac tissue research, will be crucial. The student will assist in leveraging this information to develop student facing course content and laboratory activities with SABV-specific learning objectives. By the end of the BEACoN experience, the student will have contributed to both engineered cardiac tissue research and educational translation and communication, two immensely valuable skills for both graduate school (research/teaching) and industry (discovery/translation/broad communication). 

Skills the Research Scholar will Gain

The research scholar will gain technical skills in biomaterials preparation and characterization, cell culture and analysis, biological assay development and implementation, statistical analysis, data management, and science communication. I emphasize development of data literacy and scientific writing skills like citation management, literature review, and reflection, and will encourage the student to arrange a time to work with library staff to start their data management and research for the project. While not an integral part of this research project, the student will engage with other members of my team working on cardiac tissue bioreactor development in my lab, and be encouraged to utilize R or Python-based coding for data analysis, statistics, and graph/figure generation: these experiences will provide valuable exposure to computational tools for biomedical research.  

Required Courses/Experience

BMED 2420

Preferred Courses/Experience

An understanding of human biology consistent with AP Biology or an anatomy/physiology course at Cal Poly.

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AI-Enabled Human–Robot Collaboration through Brain–Computer Interfaces

Javier Gonzalez Sanchez (he/him)

Computer Science and Software Engineering (CENG)

javiergs@calpoly.edu

Rafael Guerra Silva (he/him)
Industrial Technology & Packaging (OCOB)

rguerras@calpoly.edu

Research Project Description

Brain–computer interfaces (BCIs) and artificial intelligence (AI) are opening new possibilities for how humans and robots can work together. This project provides students with opportunities to collect electroencephalography (EEG) data (brainwave measurements) and explore its application to human–robot collaboration. Students will work with diverse commercial BCI devices to investigate how brain activity reflects user intent, attention, and cognitive workload, and how these signals can support more adaptive interactions between humans and robots in industrial and assistive settings.

Through this project, students will contribute to research in human-centered robotics while gaining exposure to signal processing, AI, software engineering, and interdisciplinary collaboration. They will participate in the development of experimental prototypes, analysis of EEG data, and dissemination of results, while gaining perspectives from neuroscience, human–computer interaction, engineering, and business. The experience also emphasizes project planning, documentation, teamwork, and reflection on potential career pathways in research, industry, and technology innovation.

As participants in this project, students will:

• Gain hands-on experience with commercial brain–computer interface devices and EEG data acquisition.

• Develop software components and AI models that support adaptive human–robot collaboration.

• Produce technical documentation and curated datasets for future stages of the research.

• Design and evaluate prototypes involving robotic systems and intelligent decision-making.

• Create a poster and video demonstration to showcase their results, with the potential to contribute to a conference presentation or paper.

• Build practical skills in signal processing, machine learning/time-series analysis, software engineering, and human-centered system design.

• Collaborate in a multidisciplinary team and gain exposure to engineering and business perspectives on emerging technologies.

BEACoN Scholar’s Role in the Project

Students will be contributing to both the technical and experimental parts of the project. The student will help set up and use commercial brain–computer interface (BCI) devices, collect electroencephalography (EEG) data from study activities, and maintain organized records of device settings, participant tasks, and data collection procedures.

The student will also assist with preparing and running experimental sessions related to human–robot collaboration. This may include testing BCI devices, checking signal quality, organizing EEG files, documenting procedures, and helping identify patterns related to user intent, attention, and cognitive workload. As the project progresses, the student will contribute to software components that support data collection, analysis, or prototype evaluation.

In addition, the student will participate in regular research meetings, share progress updates, maintain technical documentation, and help prepare project outcomes (including poster and video demonstration). The goal is for the student to have a clear, hands-on role in moving the project forward while also contributing to research communication and dissemination.

Skills the BEACoN Scholar will Gain

Students will gain experience with methods commonly used in neurotechnology and AI research. This includes EEG data acquisition using commercial brain–computer interface devices, data organization and management, and the application of machine learning techniques to identify patterns related to user intent, attention, and cognitive workload.

Students will also gain an appreciation for big data challenges, as EEG systems can generate hundreds of signals per second from multiple sensors simultaneously, requiring efficient software solutions for real-time processing and decision-making. The project will introduce students to time-series analysis and robotic systems.

In addition, students will develop software engineering skills relevant to data-intensive applications, including multithreading, distributed systems, prototype development, and data visualization. They will learn how to document and communicate research findings and system development.

The aim is for these experiences to provide insight into the intersection of AI, robotics, neurotechnology, and human-centered computing.

Required Courses/Experiences

Recommended preparation includes courses in (1) programming (Java, Python, or C/C++), (2) data structures.

Preferred Courses/Experiences

It is a plus: (1) software engineering (familiarity with agile software development methods) and (2) computer networking (protocols, ports, etc.) 

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Revolutionizing Engineering Departments: Computer Engineering's Breaking the Binary

Andrea Schuman(She/her) 

Jane Lehr (She/her), Lynne Silvovsky (She/her),

Sachiko Matsumoto (She/her)
John Oliver (He/him)

Carlos Diaz Alvarenga (He/him), Bruce DeBruhl (He/him),

Andrew Danowitz (He, him)

Computer Engineering
Ethnic Studies, and Women’s, Gender, and Queer Studies

anschuma@calpoly.edu

Research Project Description

This project is part of a larger research project called, "Breaking the Binary". Breaking the Binary is a revolutionary project will involve both students and faculty in a process of transforming the Computer Engineering (CPE) department at Cal Poly, San Luis Obispo, and potentially engineering education as a whole, through rejecting binaries or dualisms commonly used to create hierarchies in engineering thought and practice. The activities in this project ask faculty and students to actively engage in dismantling the binaries by identifying and breaking down oppressive norms. Instead, they will embrace a complex coexistence; develop new skills in co-creation of holistic learning experiences and inclusive cultures; and evolve personal and professional identities that are constantly challenged and often in flux. The work is based on a "Critical Collaborative Educational Change" model which maps individual and group change to critical consciousness, values and beliefs, actions, and collective well-being in order to break the binaries in our culture, policies, and curriculum. We are seeking colleagues to work on two projects of our overall Breaking the Binary grant.

Project 1 continues our work in a multi-year sociotechnical curricular reform for Computer Engineering. Sociotechnical course materials explore how technology and society shape each other in intended and non-intended ways. As part of this work, we use a variety of frameworks. The Civics of Technology framework asks us "Technologies are not neutral, and neither are the societies they are introduced. As technology continues encroaching on our lives, how can we advance technology education for just futures?". The Technoskeptical Framework asks 1) what does society give up for the benefits of the technology?  2) who is harmed and who benefits? 3) what does the technology need?, 4) what are the unintended consequences of the technology and 5) why is it difficult to imagine our world without the technology? Students in this project will be working alongside mentors who have developed sociotechnical course materials in the Computer Engineering curriculum and collected data on instructor and student responses to sociotechnical content in their computer engineering courses. Students will also be asked to analyze existing survey data and student-created artifacts as well as write and co-author conference publications.

Project 2 contributes to our work in answering our overarching research questions for the project:  As we engage in our change process, will the CPE department culture reject binaries that commonly create hierarchies in engineering thought and practice, and embrace a culture that is holistic and integrated? To what extent does the Critical Collaborative Education Change Model help students, staff, and faculty navigate, respond to, and engage in critical organizational change? Students will be working with mentors and our external evaluator to co-develop research protocols, engage in data collection and analysis, and write and co-author conference publications.

Research Scholar's role in the Project

We are looking for two (2) BEACoN Research Scholars to join an active engineering education research group with professors Andrea Schuman (CPE), Jane Lehr (ES/WGQS), John Oliver (CPE), Sachiko Matsumoto (CPE), Carlos Diaz Alvarenga (CPE), Lynne Slivovsky (CPE), and Andrew Danowitz (CPE). The project has collected IRB-approved qualitative and quantitative data from students and faculty 1. engaged in Computer Engineering courses with sociotechnical lesson threads and 2. Co-defining and experiencing the overall department change process. The next stage of the project is a student researcher continuing to analyze and disseminate data. They will have additional opportunities to prepare training materials for faculty to deliver sociotechnical content and a voice in the design of a unified sociotechnical curriculum. On the research side, students will gain experience in research methods and design, quantitative analysis, qualitative analysis, communication skills, and research paper writing. This will include learning about IRB processes, participating in additional literature review, developing qualitative and quantitative data analysis skills, contributing to research team meetings and meeting facilitation and finally co-author conference papers and/or journal articles.  

Skills the Research Scholar will Gain

This project will be an exceptional opportunity for a BEACoN Research Scholar to gain expertise in engineering education research. Anticipated skills our mentees will gain are related to: research methods and design, quantitative analysis, qualitative artifact and survey analysis, data presentation and data management, and written and oral communication. They will have the opportunity to develop skills and capacities related to leadership, self-efficacy, team collaboration, knowledge of personal strengths and assets, and confidence in their future career plans. We hope to be able to support them to attend and present their work at an engineering education conference.

Required Courses/Experience

Applicants must have an open mind about exploring social issues such as racism, sexism, and other forms of discriminatory practices, biases, and inequalities that influence both society and the development, use, and impact of technology.
 
Our project is unfortunately not open to undocumented participants, as it is supported through federal funding sources that require specific eligibility criteria.

Preferred Courses/Experience

Students with interest in qualitative or quantitative research methods
Interest and prior experience with perspectives and frameworks utilized in areas including Science & Technology Studies, Ethnic Studies, Women’s, Gender & Queer studies, or related areas. Interest and prior experience may be demonstrated by course work, club or other co-curricular participation and/or knowledge gained via lived experiences.
Passionate about and committed to the co-creation of more just, diverse, and inclusive STEM learning environments and cultures.
Self-motivated and active learner
We are looking to hire students who are interested in each of the two project threads

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Cardiovascular Disease (CVD) Health Care Disparities and the Importance of Early Detection of CVD

Michael Whitt (he/him/his)

Biomedical Engineering

mdwhitt@calpoly.edu

Research Project Description

Cardiovascular disease is the leading cause of death in the United States (US) and the world where health care disparities exist across gender and within communities of color. Some of the gender disparity facts include: 1) More women than men died because of cardiovascular disease between 1984 and 2011 and 2) Although the current gender disparity is that more men die of CVD, the number of deaths for both genders has been increasing since 2011. Additionally, recent data from the PANACHE (Pacific Islander, Native Hawaiian, and Asian American Cardiovascular Epidemiology) Study documents that Native Hawaiian and Pacific Islanders have the second highest cardiovascular death rate in the US, second only to African Americans.
The ideal goal of this proposal would be to have a duo from Public Health and Engineering where the team would increase the knowledge base within the communities leveraging an already approved IRB while also gathering data modifying a recently approved IRB protocol that uses a novel non-invasive method that measures endothelial dysfunction.

BEACoN Scholar's role in the Project

1. Give presentations within the local community about endothelial dysfunction (*Already IRB approved.)

2. Tabulate data from presentation pre/post surveys (*Already IRB approved.)

3. Modify IRB to gather new endothelial dysfunction data.

4. Perform data analysis.

5. Communication with partner and potential partners (e.g. American Heart Association, Association of Black Cardiologists, clinicians, and potential subjects).

6. Play a role in publications

Skills the BEACoN Scholar will Gain

1. Presentation skills.

2. Fundamental data analysis skills

3. Fundamental hardware and signal processing knowledge

4. Writing skills

Required Courses/Experience

Combined experiences of a student currently taking at minimum 1st year public health courses and 1st year engineering courses.

Preferred Courses/Experience

Combined experiences of a student currently taking at minimum 1st year public health courses and 1st year engineering courses.

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Neural and Physiological Effects of Parlay Bets in Sports

James Antony (he/him/his)

Psychology & Child Development

jwantony@calpoly.edu

Research Project Description

In 2018, the US Supreme Court decided in Murphy vs. the NCAA to end a national ban on sports gambling. As a result, 38 states and Washington DC now allow sports gambling, including 33 online, and the proportion of individuals reporting addictive behavior related to sports exploded from 3% to 17% from 2018-2022. Sports gambling has similarly skyrocketed as a business, going from $4.9B to $121B from in wagers placed in 2017-2023. This is problematic for multiple reasons, including that sports gamblers place bets more frequently and have higher rates of problem gambling than other types, and sports gambling has been linked to adverse economic outcomes like higher credit card debts and overdraft fees. This bleak picture is worsened by online sportsbooks finding ways to massively increase their revenues by expanding the types of bets available to the bettor. Critically, parlays are bets that can be placed on any combination of game outcomes and/or propositions, in which one can win more money if two or more events all successfully occur. For instance, rather than just betting on the Celtics to win, one could combine that with a bet that LeBron James will score more than 30 points in the same game. Because both events are less likely to occur in combination, the betting platforms offer higher payouts for the same amount of money wagered, which seems appealing to the bettor; however, parlay bets also compound the negative expected value of individual bets, meaning that they result in even worse long-term outcomes for bettors. This is no secret to betting platforms, who have a much higher profit margin on parlay bets (18.2% versus 4.9% on traditional bets), and who now push them aggressively on users, resulting in a 65% increase in the total proportion of all bets since 2019 and now amounting to ~70% of all NFL and NBA bets.

Despite the rapid increase in this behavior, it is unclear what drives sports gambling behaviors and how gambling heightens or alters the experience for the gambler. This proposal aims to understand the behavioral, physiological, and neural mechanisms underlying parlay bets. To do so, participants will watch the last 5 minutes of 9 different NCAA basketball games while undergoing electrophysiological (EEG) and eye-tracking measurements. While watching, they will bet on games involving two-leg parlays on consecutive basketball possessions or games with only single bets (on the second possession). In all cases, bets will be determined by whether the team scores on that possession. Behaviorally, we predict that participants placing two-leg parlays will enjoy the games more than those placing only single bets, supporting the idea that parlays make games more engaging and rewarding (independent of bet outcomes). To support this, we hypothesize that arousal for the second possession, as measured using larger pupil size and reduced alpha (8-12 Hz) power in the EEG, will be highest for two-leg parlays in which the first bet was successful, next highest for one-leg (only) bets, and lowest two-leg parlays in which the first bet was unsuccessful (because the bet would be unsuccessful regardless of the second leg). Altogether, this study will make substantial in-roads into understanding sports betting and has profound implications for addressing this rising epidemic.

BEACoN Scholar's role in the Project

The BEACoN Scholar would be involved in the following:

1. Reading relevant literature and discussing it with me in our weekly meetings (in addition to discussing the research project and professional development topics), to provide a strong overview of the prior work motivating this project;

2. Data collection, including being present and setting up the EEG and eye tracker when the subjects watch the basketball clips, coordinating with participants, sending reminder emails, learning to administer and troubleshoot the EEG and eye tracker, giving participants instructions, facilitating questionnaires and the computer program used to run the study;

3. Data organization & entry, including learning the importance of file structure within directories and how that becomes critical for automating computer coding analyses;

4. Learning to analyze EEG and pupil dilation data from me, including learning with me in coding sessions and off-line from prior tutorials for EEG workshops I ran (supported by 2023-24 and 2024-25 Teacher Scholar Model grants);

5. Analyzing the data, including computer programming to assess how the anticipation and outcome of placed bets affects neural activity and pupil size;

6. Designing and creating a poster to be presented at the year-end BEACoN symposium;

7. Submitting an abstract for a poster presentation at a professional conference (should they be interested – this may occur after BEACoN concludes); and

8. Potentially work on drafting a manuscript for publication (pending results – this may occur after BEACoN concludes).

Skills the BEACoN Scholar will Gain

The scholar(s) will gain excellent hands-on skills in psychological and neuroscientific research methods, data entry and management, and computer programming. Regarding neuroscientific research methods (specifically, collecting and measuring brain activity), being able to directly set up EEG (and eyetracking) experiments is a rare opportunity for an undergraduate to gain hands-on access to complex measurements. Regarding data management, they will learn how to create basic file and data structures and how these interface with later analytical tools like computer coding, so that in any future project, they can arrange data according to how they will use it. Regarding computer programming, it will introduce them to basic if-then logic, loops, data cleaning, data filtering and selection, time-series functions like temporal filtering, down-sampling, time-frequency decompositions, and interpolation, and multivariate statistics like independent component analysis and multiple regression, and they will apply inferential statistics to make conclusions about their hypotheses. In total, the student(s) will learn how to transform complex, multivariate datasets into insights about mental function.

These skills are integral in preparing them for graduate school and a wide variety of careers. For instance, should the BEACoN Research Scholar not continue into academia, knowing how to code and organize data will open doors immediately upon graduating. Additionally, they will gain skills in thinking critically about psychological theories and how to infuse data analysis with inferences we can make about mental processes. They will learn how to ask questions, pursue efforts to tackle answers, and communicate their findings in a manner that applies to daily life and across disciplines. Lastly, the student(s) will gain experience writing and abstract and creating and presenting a poster, both for the BEACoN Research Symposium and a professional psychology conference.

Required Courses/Experience

Strong time management and organizational skills; initiative and eagerness to learn; an interest in cognitive neuroscience.

Preferred Courses/Experience

Prior computer programming experience (MATLAB/Python/R) is preferred. Also, given that our stimuli will be basketball games, an interest in basketball is desired. Lastly, the BEACoN Scholar would ideally have some knowledge of psychology (e.g., PSY 2201, General Psychology, or AP Psychology from high school). Other preferred courses include Research Methods (PSY 2229), Cognition (PSY 3357), Cognitive Neuroscience (PSY 4480), Memory (PSY 4440), and Neuroscience (offered in BCSM).

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Negotiating Race and Ethnicity in K-pop

Alison Cheung (she/her)

Communication Studies

acheun33@calpoly.edu

Research Project Description

K-pop has become increasingly prominent in U.S. popular culture, and its global rise has transformed not only the music industry but also conversations about race, ethnicity, and representation. In particular, the emergence of panethnic and multiracial K-pop groups is reshaping notions of idols, music, and fashion. For instance, panethnic groups Blackpink and Katseye feature members from various Asian backgrounds, while groups such as Girlset and Blackswan include members from diverse racial and ethnic backgrounds. This project investigates the evolving landscape of K-pop and examines broader shifts in U.S. media and cultural production. By drawing from research on transnational media, popular culture, and rhetorical analysis, the project investigates how K-pop serves as a site where race and identity are continually negotiated.

BEACoN Scholar's role in the Project

The BEACoN research scholar will play an integral role in the project by working with the mentor to identify K-pop groups for the media text, select artifacts for analysis, and conduct media criticism. They will create and apply concepts from an in-depth literature review by drawing from scholarship on media and cultural studies. The scholar will engage in humanistic inquiry and sharpen analytical and writing skills.

Skills the BEACoN Scholar will Gain

Through this project, the scholar will develop the skills to 1) conduct media criticism, 2) engage with literature on race, ethnicity, and transnationalism, 3) organize cultural artifacts, 4) synthesize scholarly concepts and articles, and 5) strengthen their critical lens and analytical skills.

Required Courses/Experience

Completion of Area 1 (1A, 1B, and 1C) and strong writing skills. Familiarity with K-pop is a plus, but detailed knowledge is not necessary.

Preferred Courses/Experience

Prior coursework in popular culture or ethnic studies is welcome. Current enrollment in or completion of a rhetoric/criticism course in COMS such as Media Criticism, Rhetorical Criticism, or Race & Rhetoric is preferred.

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The Dangerous Gatherings Project: Black Musical Performance, Public Memory, and Racial Violence

Dallas Donnell (he/him/his)

Ethnic Studies

dtdonnel@calpoly.edu

Research Project Description

In 2012, 17-year-old Jordan Davis was shot and killed by a white motorist after an argument over the volume of rap music playing from his car. Eleven years later, 28-year-old O'Shae Sibley, a Black gay dancer, was murdered in a homophobic attack after voguing to Beyoncé outside a New York gas station. Separated by more than a decade, these tragedies raise a striking question: Why have Black musical performance and gathering repeatedly become flashpoints for racial violence in American life?

This research project investigates Black musical performance cultures—from churches and juke joints to concert halls, festivals, neighborhood celebrations, and contemporary public spaces—as spaces where Black communities have forged relationships, cultivated joy, expressed political ideas, mourned collectively, and imagined freedom. Yet these same spaces have also become recurring targets of racial surveillance, criminalization, and violence.

The BEACoN Research Scholar will help launch a long-term research initiative examining these histories through archival research. Together, we will investigate historical and contemporary case studies—including the 1940 Rhythm Club Fire in Natchez, Mississippi; attacks on performers such as Nat King Cole and Prince; the policing of hip-hop culture; and the gendered, racialized pressures surrounding Black women performers. Drawing on newspapers, photographs, oral histories, legal documents, and other primary sources, we will investigate how spectacular acts of violence and more subtle forms of structural and discursive violence have shaped Black musical life, public memory, and the ongoing struggle over who has the right to gather, perform, and belong in American public life.

BEACoN Scholar's role in the Project

The BEACoN Research Scholar will serve as an active collaborator throughout the research process. Responsibilities will include conducting archival research using newspaper databases and digital collections; locating, organizing, and evaluating primary and secondary sources; creating annotated bibliographies and research summaries; constructing historical timelines; identifying photographs and other visual materials; and helping organize digital research files.

As the project develops, the student will gradually develop ownership over one or more historical case studies by interpreting primary sources, identifying emerging research questions, and synthesizing historical findings. Throughout the year, the student will participate in regular discussions about historical interpretation, Black Studies scholarship, and public memory while contributing to a final research presentation at the BEACoN Research Symposium. Depending on the project's progress, the student may also contribute to conference presentations, digital humanities initiatives, or future public-facing research materials associated with The Dangerous Gatherings Project.

Skills the BEACoN Scholar will Gain

The BEACoN Research Scholar will gain experience with historical and archival research methods, including the use of digital newspaper databases, archival finding aids, government documents, photographs, oral histories, and legal records. They will learn how humanities scholars formulate research questions, evaluate primary sources, synthesize secondary scholarship, and organize long-term research projects using annotated bibliographies and citation management software.

In addition, the student will develop skills in qualitative analysis, historical writing, public humanities, scholarly communication, project organization, and collaborative research. They will gain experience translating archival research for broader audiences through conference presentations and public-facing scholarship while learning how faculty research develops from archival discovery to publication.

Required Courses/Experience

No prior research experience is required. Students should demonstrate intellectual curiosity, reliability, strong communication skills, and a willingness to learn historical research methods. Because the project involves reading historical documents, synthesizing evidence, and working independently, careful attention to detail and consistent engagement are essential.

Preferred Courses/Experience

Coursework or demonstrated interest in African American Studies, Ethnic Studies, History, Sociology, Music, English, Journalism, Media Studies, Anthropology, or related fields is preferred but not required. Students with an interest in archival research, Black expressive culture, public history, or cultural studies are especially encouraged to apply.

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Examining the Efficacy of a Public Mental Health Education and Suicide Prevention Program in Adolescents and Young Adults

Natasha Duell (she/her/hers)

Psychology and Child Development

nduell@calpoly.edu

Research Project Description

The project is in collaboration with the Transitions-Mental Health Association (TMHA) of San Luis Obispo. Recent trends in the frequency of prolonged mental health challenges across all age groups have grown. Since 2015, signs of depression have grown by about 60%, and about 40% of people with depression older than 12 have received counseling in the last 12 months. Trends show that these numbers are especially high for adolescents, suggesting that age may be associated with different rates of depression (CDC 2025). Suicide and suicidal ideation are symptoms of poor mental health (Hofstra et al., 2019). Suicide prevention and mental health education have been shown to effectively prevent suicide completion (Hill et al., 2025).

Over the past couple years, TMHA led an intervention aimed at adding mental health education to the high school health class curriculum in San Luis Obispo County, which has a higher rate of teens expressing suicidal ideation compared to the average in California (SLO Health Counts, 2026). The intervention included a two-part youth mental health education and suicide prevention course given to high school students. Students were given surveys at the beginning and end of the courses asking them to report on their understanding of mental health topics and acceptance of those struggling with mental illness. The purpose of this study is to organize and analyze those survey data to determine the efficacy of the intervention across various demographic characteristics including county, age, gender identity, and ethnicity.

BEACoN Scholar's role in the Project

Students will be working with Transitions Mental Health Association (TMHA), a local non-profit aimed at reducing stigma surrounding mental health and providing free, equitable, and trauma-informed care to people across all age groups in San Luis Obispo and Northern Santa Barbara County. With the supervision of Dr. Duell, students will aid TMHA employees with entering survey data, developing research questions, conducting statistical analyses, and reporting/disseminating the results for grant-writing and funding purposes. Hours can be flexible to accommodate other student demands.

Skills the BEACoN Scholar will Gain

Students will gain hands-on experience in doing mental health research within the non-profit world with practical and immediate relevance and impact. Students will learn how to design a research study using secondary (already-collected) data, organize and analyze longitudinal data in Excel and SPSS using syntax (coding). Students will also be exposed to the ins and outs of non-profit work and see the immediate relevance of research to designing programs and writing grants to acquire funds for such programs. This experience will be a truly interdisciplinary and cross-industry collaboration.

Required Courses/Experience

• Introductory course in statistics or research methods

• Course related to mental health and/or public health

• Demonstrated history of being dependable, organized, and having strong time management

• Comfortable communicating with people in-person, over zoom, and via e-mail

Preferred Courses/Experience

Developmental psychology course (especially any coursework related to adolescent development)

• Experience working in a social sciences research lab (e.g., psychology, sociology, public health)

• Experience working with or analyzing quantitative data

• Experience or interest in coding or data analysis

• Geographic information systems software experience

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Collaborative Curatorial Practice for Community-Based Mutual Aid

Elizabeth Folk (she/her)

Art and Design

efolk@calpoly.edu

Marco Polo Juárez Cruz (he/him)

Art and Design

mjuarezc@calpoly.edu

Research Project Description

Over the course of this project, the student researcher(s) will assist in the research, curation, and production of a community art event featuring an evening of social justice–focused performance and video art. The event will also include a silent art auction benefiting UndocuFund, raising mutual aid funds for Central Coast families impacted by immigration enforcement. Artists will be selected through an open call to present emerging local artists alongside those with established careers, creating opportunities for networking, mentorship, and artistic exchange. The project will work closely with local arts and community organizers in Santa Maria, including Allan Hancock College faculty and Alan Hancock to Cal Poly transfer alumni, one of whom will serve as a co-curator, to cultivate cross-campus dialogue and broaden access to exhibition opportunities for students and artists across the Central Coast.

Through this process, the student researcher(s) will investigate collaborative curatorial practice as a model for community engagement, examining how partnerships between a university, community college, nonprofit organizations, and local artists can strengthen connections across institutions while supporting mutual aid. Blending art, activism, and community organizing, the project seeks to expand access to curatorial practice, create pathways for mentorship between emerging and established artists, and demonstrate how public art events can serve as sites of civic engagement, artistic exchange, and community care.

BEACoN Scholar's role in the Project

The student researcher(s) will participate in all phases of the project, including researching community-engaged curatorial practices, developing the open call, conducting artist outreach, communicating with participating artists and community partners, assisting with artwork selection, and supporting exhibition planning and installation. They will also help document the curatorial process, collect and analyze feedback from artists and attendees, and reflect on how collaborative exhibition-making can foster community engagement, mentorship, and mutual aid. The student researcher(s) will present their research findings through the BEACoN Research Symposium and contribute to project documentation that can inform future cross-campus collaborations.

Skills the BEACoN Scholar will Gain

Collaborative research methods, visual and material research, exhibition and dissemination practices, qualitative analysis, project management, creative problem-solving, professional communication, documentation and digital asset management, professional development

Required Courses/Experience

• Demonstrated interest or experience in community organizing, civic engagement, or social justice initiatives (including student clubs or volunteer work)

• Introductory knowledge of contemporary art history or contemporary art practice

• Strong organizational, communication, and collaborative skills

• Interest in community-engaged curatorial practice and public programming

Preferred Courses/Experience

• Experience in exhibition curation or gallery work

• Experience planning events or coordinating public programs

• Experience communicating with community organizations or multiple project partners

• Experience creating or working with time-based media (video, performance, sound, installation, etc.)

• Familiarity with open-call processes or artist outreach

• Spanish language proficiency

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Barriers to Civic Participation in San Luis Obispo County: Understanding Access, Representation and Community Engagement

Annie Aguiñiga Frew (She/her)

Political Science

aaguinig@calpoly.edu

Research Project Description

Civic participation is a cornerstone of democratic governance, yet many residents face barriers that limit their ability to engage in local decision-making processes. While traditional measures of participation often focus on voting, meaningful civic engagement also includes attending public meetings, serving on boards and commissions, participating in community organizations, contacting elected officials, and contributing to local policy discussions. Grounded in community-based and participatory research principles, this mixed methods research project seeks to better understand the factors that encourage or inhibit civic participation among residents of San Luis Obispo County, with particular attention to busy working families, young adults, renters, low-income residents, and historically underrepresented populations. By centering community voices and lived experiences, the project aims to better understand how residents perceive opportunities for participation and identify barriers that may limit engagement. Through surveys and community focus groups or interviews, the project will examine how factors such as time constraints, access to information, trust in government, feelings of efficacy, representation, and community belonging influence participation.

Using an explanatory sequential mixed methods design, the project will combine quantitative survey data with qualitative interviews or focus groups to provide a more comprehensive understanding of participation barriers and opportunities. The project will draw upon community-based and participatory frameworks that recognize residents as important contributors to the research process and emphasize the co-creation of knowledge that can inform local action. Undergraduate researchers will play an active role in all phases of the project, including instrument development, community outreach, data collection, coding, analysis, and dissemination of findings. The goal is not only to identify barriers, but also to generate practical recommendations for local governments, nonprofit organizations, educational institutions, and community leaders seeking to create more accessible and inclusive opportunities for civic engagement. Ultimately, this project aims to contribute to a stronger understanding of how communities can build civic systems that are responsive to the needs of diverse residents, strengthen trust and belonging, and foster greater participation in public life.

BEACoN Scholar's role in the Project

The student researcher will be involved throughout the research process, including conducting literature reviews, assisting with survey and interview protocol development, IRB application submission, recruiting participants, collecting data, coding qualitative interviews, conducting preliminary analyses, and helping prepare presentations and reports. Students will gain hands-on experience in community-based participatory research, mixed methods research design, data analysis, and public-facing dissemination of findings. The project is designed to provide mentorship in community based research in a way that benefits the local San Luis Obispo community.

Skills the BEACoN Scholar will Gain

The research scholar will gain skills in mixed methods research design, quantitative and qualitative analysis, participatory and community based research, policy analysis, public presentations and writing accessible reports for various audiences.

Required Courses/Experience

There are no specific course prerequisites required for this position. However, students should have a strong interest in civic engagement, public policy, local government, community-based research, and/or issues related to participation. The student should also be willing to engage respectfully with community members, work collaboratively, and participate in all stages of the research process.

Preferred Courses/Experience

Preferred experiences include prior coursework in research methods, political science, public policy, ethnic studies, sociology, or related fields. Students who have taken POLS 112 or another course focused on American, California, local, or state government would be especially well prepared for this project. A working knowledge of local and state government, civic participation, community engagement, or policy advocacy would also be helpful. Prior experience with surveys, interviews, focus groups, qualitative coding, data analysis, or community outreach is welcome but not required.

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"mah tongue is in mah friend’s mouf": Exploring Black Friendship at Cal Poly & Beyond

Maya Hislop (she/her/her's)

English

mshislop@calpoly.edu

Research Project Description

In her foundational 1937 novel, Their Eyes Were Watching God, Zora Neale Hurston uses Black female friendship to frame the story of Janie, a Black woman coming of age in the early 1900s Southern United States. Janie returns to town after years away and begins to tell her old friend Phoeby the story of her travels. Before beginning, Phoeby warns that Janie must be prepared to tell the entire story to the townspeople lest they make up their own stories. Janie, however, has no interest and requests that Phoeby serve as medium, "You can tell ‘em what Ah say if you wants to. Dat’s just de same as me ‘cause mah tongue is in mah friend’s mouf" (38). Scholars often cite this moment as a pivotal representation of the power and necessity of Black female friendship as a strategy for surviving white supremacy and patriarchy. For Black women, friendship can function as a form of resistance not only against white supremacist violence, but also to survive gender-based and other forms of intracommunal violence. Phoeby’s agreement to serve as Janie’s proxy is an agreement to defend her from the ageist and sexist lies the townspeople have already begun to spin about her. Since Hurston’s novel, many other contemporary Black artists (writers, TV/film producers, content creators, etc.) have turned to Black friendship as a medium through which to explore a number of themes key to Black life. Black friendship on the college campus has garnered a special kind of attention in TV and film as seen on classic series like A Different World as well as a more recent series like Insecure. In this research project, we will investigate a few key questions: What does an in-depth analysis of the contemporary representations of Black friendship tell us about its continued status as a tool of resistance? Has the role of Black friendship changed from the early 1900s to today? If so, how? Additionally, how might students and faculty work together to better understand the role of Black friendship at a predominantly white institution like Cal Poly? What complexities and nuances of Black friendship in its lived embodiment do the media representations fail to capture? How do other points of identity outside of race (class, ethnicity, gender, sex/sexuality, ability, etc.) work or not work within Black friendship? Not only will it be key to think about friendships between Black people here, but it will also be important to consider cross-cultural/cross-racial friendships in which Black people participate.

The initial stage of the research project will be data collection as we read, and watch representations of Black friendship to learn more about tropes, themes, patterns, and shifts over time with a focus on the 20th and 21st century. Broadly defined, "Black friendship" will refer to any friendship or platonic relationship in which a Black person exists, inclusive of both intra- and interracial friendships. Key texts to examine will likely be Their Eyes Were Watching God by Zora Neale Hurston, Sula by Toni Morrison, Passing by Nella Larsen,Symptomatic by Danzy Senna, Lena by Jacqueline Woodson, Insecure (2016, TV), Girlfriends (2000, TV), Moesha (1996, TV) Living Single (1993, TV), Harlem (2021, TV), Survival of the Thickest (2023, TV), Zola (2020, film) dir. Janicza Bravo. Examples of the "black best friend" trope (a white protagonist’s sidekick) which proliferated in 1990s Hollywood teen comedies will also be useful to examine as counter-examples, such as She’s All That (1999) and 10 Things I Hate About You (1999). In addition to collecting primary sources (literary, televised, filmic, etc.), the initial stage will involve the collection of scholarly work on Black friendship both representational and as a lived experience. The second stage of the project will be data collection of lived experiences which will involve surveying and forming small group discussions with Black students at Cal Poly.  

BEACoN Scholar's role in the Project

The student will be expected to work as a collaborator on nearly every vital stage of the research project: careful reading/watching and note-taking of literature, film, and television, survey creation and advertising, small group discussion facilitation, participating in one-on-one meetings to discuss data, the formulation and writing of a conference presentation, journal article or equivalent.
 

Skills the BEACoN Scholar will Gain

The BEACoN Research Scholar will gain skills around literature review, various forms of data collection (involving media and interview participants), data management, and qualitative analysis. This project is a combination of methodologies from a variety of disciplines: literature/film studies, Black studies, Black feminist studies, and sociology.

Required Courses/Experience

The BEACoN Research Scholar must have some advanced ability in the areas of reading comprehension, analysis, and writing. The scholar must have taken at least one introductory level course that involved critical race studies or ethnic studies (ideally Black Studies or African American Studies was at the center) and one advanced course that involved critical race studies or ethnic studies. I’m making a distinction between courses involving race and an introductory or advanced Ethnic Studies course because there are several courses in other departments in which race/ethnicity are central to the course that could qualify. The BEACoN Research Scholar must also have some experience with creating a survey, running a small group discussion, presenting in front of others and/or they have taken a sociology or psychology course in which such data collection methods were discussed.

The BEACoN Research Scholar must be someone with strong time management skills and attention to detail.
 

Preferred Courses/Experience

It is preferred that the BEACoN Research Scholar has experience (either lived or other) with the African diaspora in some way. The BEACoN Research Scholar preferably has taken courses or done their own independent research that center other points of identity outside of race: gender and/or queer studies, disability studies, etc. It is preferred that the Scholar be a first or second year so that this project may be one that can continue over a few years, possibly culminating in their senior project. It is preferred that the Scholar have a major in the College of Liberal Arts, most useful may be English, History, Ethnic Studies, Sociology, Psychology, Gender/Queer Studies, Political Science or Art and Design. It is preferred that the Scholar has undertaken their own research project or a project involving the finding and implementation of secondary source material prior to this one (in high school and/or at Cal Poly).

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The Global AI Opportunity Gap: Access, Equity, and Environmental Cost Across Higher Education Systems

Alexa Loken (she/her)

Industrial Technology, Packaging and Entrepreneurship (OCOB); Management, Human Resources, and Information Systems (OCOB); and Communications (CLA)

aloken@calpoly.edu

Research Project Description

As AI tools become as foundational as the internet, a critical question emerges around who actually gets to benefit, and who pays the price. This research project investigates the growing gap between universities and countries that are meaningfully preparing students to engage with AI and those that are not. Using publicly available data- university course catalogs, national education policy documents, international reports, and sustainability assessments- the student researcher will compare how institutions in the United States, Singapore, Thailand, and Kenya are building AI literacy across their student populations, with reference to emerging EU regulatory frameworks. These four countries represent a deliberate spectrum: from a national mandate requiring all students to develop AI skills (Singapore), to a teaching-focused university system navigating institutional variation without a national standard (U.S.), to emerging economies with strong aspirations but significant infrastructure and access barriers (Thailand, Kenya). The project asks: which students and institutions are gaining genuine AI readiness, and which are being left behind? And critically, how does that answer change for students at under-resourced institutions, in low-income communities, or in countries with limited digital infrastructure?

Woven into this access and equity analysis is an environmental lens. The AI systems that higher education increasingly depends on carry real costs: data centers powering AI now rival entire countries in energy consumption, and those infrastructure costs are disproportionately borne by communities, often in lower-resource contexts, that gain the least AI benefit. The student researcher will examine this "who benefits, who pays" dynamic across the four countries studied, connecting global equity patterns to what it means for Cal Poly students navigating AI in their own education and careers. Outputs include an institutional AI Access Heat Map, a four-country equity and environmental cost spectrum visualization, and a student-facing guide to assessing AI readiness, materials directly applicable to Cal Poly's curriculum, career preparation programming, and BUS 270: AI Literacy for Business.

BEACoN Scholar's role in the Project

The BEACoN Research Scholar will serve as co-investigator across two semesters of structured, phased research. In Fall semester (5 weeks, November- December), the student will: conduct a systematic literature review of AI literacy frameworks from UNESCO, Stanford HAI, and WCET; build a scoring rubric across five institutional dimensions (AI courses offered, institutional policy, equity/access initiatives, faculty support, and career readiness integration); begin primary data collection on U.S. institutions using public course catalogs and policy documents; and draft an annotated bibliography and project methodology document.

In Spring semester (15 weeks, end of January- May), the student will: expand the institutional analysis to Singapore, Thailand, and Kenya; compile and synthesize environmental cost data from IEA, UN University, MIT, and Brookings reports; build two core visual deliverables (an AI Access Heat Map across institutions/countries and a spectrum visualization mapping AI access against environmental cost by country); draft the AI Equity and Impact Framework policy brief; and present findings at the BEACoN Research Symposium on May 19th. The exact scope and country emphasis may be refined collaboratively with the student based on their background, interests, and emerging findings.

The student will also have 1–2 structured conversations with Cal Poly faculty or professionals in environmental studies or sustainability to deepen the environmental cost dimension, as needed. This faculty mentor has a direct professional stake in the Southeast Asia context, including an upcoming teaching appointment in Thailand through Cal Poly's Global Programs in summer 2027, which brings personal motivation and regional attentiveness to the project's analysis of Thai higher education.

Skills the BEACoN Scholar will Gain

• Systematic literature review: Identifying, evaluating, and synthesizing peer-reviewed research, institutional reports, and international policy documents- a foundational research competency across disciplines
• Comparative document analysis: Building and applying a structured coding rubric to institutional artifacts (course catalogs, policy pages, syllabi) across four national contexts- a core qualitative research method in education, social science, and policy research
• Secondary data compilation and analysis: Locating, assessing, and organizing publicly available quantitative data (energy consumption statistics, AI readiness indices, national education reports) into structured datasets
• Cross-cultural and international research literacy: Navigating sources across four national contexts and understanding how policy environment, infrastructure, and culture shape educational outcomes — a globally relevant professional competency
• Data visualization and science communication: Translating complex findings into two portfolio-ready visual formats (institutional heat map; access-vs.-cost spectrum graphic) using tools such as Canva, Flourish, or Google Sheets
• Policy and research writing: Drafting an executive summary, contributing to a student-facing guide, and preparing a research poster and symposium presentation- all transferable professional writing skills
• Research design literacy: Understanding why this project is built around publicly available secondary data, what ethical considerations apply to international comparative research, and how to scope a research question for a defined timeline- foundational skills for graduate school or applied research careers

Required Courses/Experience

No specific courses required. Student should demonstrate: genuine curiosity about technology/AI, equity, sustainability, and/or global issues; reading and synthesizing written sources in English; and basic proficiency with digital tools like Google Suite

Preferred Courses/Experience

Coursework in communications, business, environmental studies, international studies, political science, sociology, or a related field preferred. As is:
-Interest in AI, future-of-work, sustainability, or education policy
-Experience with research or academic writing at any level
-Students who have studied, lived, or worked internationally (particularly in Southeast Asia or East Africa) are strongly encouraged to apply; cross-cultural lived experience meaningfully enriches this research
-Students from backgrounds underrepresented in technology and research fields are especially welcome; this project is explicitly designed to connect equity research to the researcher's own lived context

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Advancing Today's Movements by Learning from the Late 20th Century: The Life and Legacy of Merle Woo

Maggie Mang

Interdisciplinary Studies in Liberal Arts (ISLA)

mamang@calpoly.edu

Research Project Description

This BEACoN project will focus on researching, organizing, and analyzing relevant archival materials to support a public exhibition around the release of the first in-depth zine about the life and work of activist Merle Woo (1941-present). Born and raised in the Bay Area, Merle is a Chinese-Korean American, lesbian, socialist feminist organizer, and educator whose essay ‘Letter to Ma' was published in the seminal 1981 women of color anthology, "This Bridge Called My Back." As a student, Merle participated in the Third World Liberation Front strikes at San Francisco State University (SFSU) and later was one of the first generation of educators to teach at UC Berkeley in the newly formed Asian American studies program. As a member of Radical Women and the Freedom Socialist Party, she ran for Governor of California as an independent candidate in 1990. She co-founded Unbound Feet, a feminist Asian American literary and performance collective. Yet despite her life's work and immense contributions to Asian American history, knowledge of Merle is still unknown, even within Asian American curriculum.

With a team of collaborators engaging in participatory archival methods, including Merle and her family, and with the support of BEACoN 2024-2025 and the CLA SURP 2025, Merle's personal archives have been organized and sold to the Schlesinger Library at the Harvard Radcliffe Institute to be fully digitized and available to the public in the next two years. A 44-page zine detailing Merle's life, work, and the process of collectively archiving Merle's papers has been created by a past BEACoN 2024-2025 student, Mariajose Bazan-Barreda. This BEACoN project will focus on the research, organization, and writing to support supplementary teaching materials for the zine, as well as an on-campus public exhibition-style zine-release party currently slated for May 2027. The BEACoN student researcher will be expected to find, organize, and synthesize relevant archival information contextualizing Merle's work in the late 20th century and connecting her life, and late 20th century struggles, to present-day concerns over DEI, freedom of speech, growing wealth inequity, and more.  

BEACoN Scholar’s Role in the Project

The priority for the BEACoN Research Scholar is to focus on best practices on making accessible publicly facing exhibits and teaching materials based upon pre-existing research and historiography. The student Research Scholar is expected to:

• Research literatures, archival materials, examples, and networks of people and projects related to the context of Merle Woo's life, such as Unbound Feet, the history of Ethnic Studies, and/or the Third World Liberation Front student protests

• Research examples of exhibition-style projects and synthesize notes regarding best practices of making research and history more accessible for the public

• Contribute to the research project's evolving practices of collaborative decision-making, transparency, accountability, and feminist and inclusive praxis

• Research, synthesize, and implement pedagogical materials to support the Merle Woo zine (e.g. creating teaching materials; pairing readings together; writing discussion questions)

• Support the translation of existing history and research into an exhibit (e.g. choosing relevant archival materials to showcase; thinking about the spatial implementation of relevant materials; understanding decision-making in crafting an exhibit as an example of research methodology)

Skills the BEACoN Scholar will Gain

The BEACoN Research Scholar will gain and/or strengthen the following skills:

• Reading, analyzing, synthesizing, and annotating existing literature on critical university studies, women of color feminisms, late 20th century student protests, and late 20th century social movements

• Learning and practicing dynamic data management skills, which involve managing a diverse number of documents and how to store them physically and/or digitally

• Learning and practicing critical pedagogical skills, including how to translate research into classroom curriculum and how to translate existing research into an accessible, public exhibit

• Learning how to use open-source archival management software such as Tropy to annotate, organize, and sort primary archival documents 

• Exercising verbal and written skills in summarizing and presenting questions and findings, as well as in writing introductions for exhibit materials to help contextualize Merle Woo's life 

• Exercising self-advocacy and clear communication skills

• Engaging in research in reciprocal, transparent, joyful, and accountable ways

Required Courses/Experiences

• Interest and/or experience in social movements and organizing both presently and historically; high emphasis on interest in the Third World Student Strikes and other women-of-color organizing of the 1980s and beyond

• Basic familiarity and engagement with concepts such as racism, capitalism, imperialism, and women-of-color feminism

• Interest and/or experience in translating research into concrete pedagogy (e.g. reading guides, discussion questions) and/or public exhibitions (e.g. how to select primary documents and photographs; how to spatially organize relevant archival materials)

• Experience and/or strong interest in developing project management skills, given that this research project is about conducting research, synthesizing research, and then translating said research into a publicly facing exhibition

Preferred Courses/Experiences

• Some experience or working familiarity with the politics of history, public history projects, critical pedagogy, and/or exhibitions

• Introductory experiences related to conducting a literature review and how to find relevant literature

• Working familiarity with basic technological platforms, such as Zoom, Microsoft Office, Google Suite, and Adobe Acrobat

California Heritage Virtual Museum – Community Input and User Experience (UX) Assessment

Elizabeth Minor (she/hers)

Social Sciences

elminor@calpoly.edu

Research Project Description

The mission of the California Heritage Virtual Museum is to preserve and share California's heritage and history, broadly defined; to celebrate the state's diverse histories and communities; and to enable public audiences to make connections between the past and the present. Museums throughout the State of California hold artifacts that can tell multi-layered and engaging stories about our past, but many do not have the resources or platform to share this cultural heritage with wide public audiences. Small, local museums also hold important collections that are overlooked due to their limited hours of operation and small staff. Underrepresented community groups have perspectives and histories that enrich public conceptions of California heritage. Created for public audiences, the virtual museum will also be of use for California educators, especially in 4th grade California history curricula. Participating in the Digital California Heritage Lab, student research assistants will take ownership of developing 3D capture workflows, managing collaborative relationships with museums and community stakeholder groups, and designing UX assessment research.

We are moving out of our initial prototyping phase and will solicit community input on future directions of the Virtual Museum development. We will combine the methods of User Experience research (UX) and community-based participatory research, where community collaborators can test out the current prototype and then give us input on how to best incorporate and represent new facets of California heritage. The BEACoN Research Scholar will work closely with me to design and implement this public outreach and assessment program, along with taking a leadership role as they are helped by other students in the Digital California Heritage Lab.

BEACoN Scholar’s Role in the Project

The BEACoN Research Scholar will act as the lead in the student research group to design the next iteration of the Digital California Heritage Lab's User Experience (UX) assessment program. The Scholar will create a plan for assessing the Virtual Museum prototype using surveys, interview questions, A/B testing, and user observations. The Scholar will research and identify potential diverse community collaborators in the San Luis Obispo area, contact them, and perform UX testing with them. In the process of UX assessment, the student will also gather input from potential community collaborators including: perspectives on what should be included in the museum as ‘California Heritage', leads on museum/historical society/archive collections that should be 3D modeled, assessment of accessibility of the virtual galleries for visitors of diverse backgrounds/ages/abilities, and advisory input on ethics of representing cultural heritage in digital form. The Scholar will perform mixed-methods data analysis and create data visualizations of the results, with assistance from the Digital California Heritage Lab research group. The final outcome will be an action plan for the future development of the Virtual Museum that represents diverse community input.

Skills the BEACoN Scholar will Gain

• Research design skills – How to integrate ethnographic interviews/observation, UX-specific assessments (A/B testing, empathy mapping, etc), and community-based participatory research. The student will begin with background readings on each of these three methods, then will evaluate related case studies, and then collaboratively design the project's research plan.

• Public Outreach experience – How to identify interested community groups, organize sessions with them, perform active listening and interviewing, build communication and establishing bidirectional collaborative relationships. I will coach the student on best practices, set-up practice sessions with already established community groups, and then collaboratively implement public outreach sessions with new potential community partners.

• Mixed-Methods Analysis – How to use qualitative and quantitative data from outreach sessions to create data-driven action plan for future virtual museum development. The student will begin with background readings about specific applied methods, then will evaluate related case studies, and then collaboratively analyze our collected data, resulting in data visualization and an action plan.

• Digital Interactive Skills – Although this BEACoN project is primarily focused on community input and UX assessment, the Research Scholar will also receive training in 3D model capture, editing, and virtual gallery design.

Required Courses/Experiences

• At least one Social Sciences methods course,

• Familiarity with museum studies and/or digital interactives

• Experience with interviewing and/or outreach.

Preferred Courses/Experiences

• Preferred courses: Digital Anthropology, UX Research for Social Sciences, Museum Anthropology, or other similar courses

• Preferred experience: At least one previous ethnographic/mixed-methods analysis research project.

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"Is Life Precious Here?" Relational Embodiment of Care as a Transformative Change Practice in Care Work Settings

Daniel Rodriguez (he/they)

Psychology & Child Development

drodr212@calpoly.edu

Research Project Description

Embodying care practices is essential for transformative change, meaning efforts that collectively address the systemic roots of social issues (Kivell et al., 2022). Many transformative change actors identify themselves as organizers or care workers. Though impactful, transformative work can be demanding, sometimes leading to burnout and decreased engagement in organizing (Hayes & Kaba, 2023). Yet co-creating a culture of care within social change contexts may plant seeds of equity that blossom into sustainable transformative change work and the embodiment of just futures. We will analyze ~15 interviews with care workers, using a critical and relational approach to consensus qualitative research (Braun & Clarke, 2013; Hill et al., 2012), examining how participants integrate care-based practices, embodying the relational world we strive toward (Tebes & Thai, 2018).

In previous analyses, two teams of two student researchers trained in qualitative research, including Relational Consensus Analysis, grounded this work in reflexivity practices drawing on anti-racism, decolonial feminisms, Queer solidarities, and class awareness, and collaboratively developed and applied a codelist to eleven interviews. This foundational work clarified both the analytic process and the time required to conduct ethical, rigorous, and reflexive qualitative social justice research in a PWI context. BEACoN scholars will join this active workflow: after refresher training in interview, transcription, and qualitative analysis, they will help identify and schedule remaining interviews, transcribe new interviews, apply the codelist to analyze interviews, and participate in team debriefs to finalize cross-case synthesis and generate themes for future results dissemination. Scholars will also receive mentorship in professional development and career planning for future transformative change work, grounded in the same care-based practices we study. By conducting research on reciprocal care, we aim to amplify knowledge to promote transformative social change work.

BEACoN Scholar’s Role in the Project

• Reading peer-reviewed journal articles and book chapters on the research topic,  reflexivity, qualitative analysis, and other topics related to the study.

• Qualitative analysis of interviews with a critical epistemology, with attention to power, privilege, and oppression.

• Early thematic analysis of the data to prepare it for dissemination.

Skills the BEACoN Scholar will Gain

• Reflexivity of power, privilege, and oppression shaping our research and actions.

• Data management and qualitative analysis: Identifying participants, scheduling, transcribing, and analyzing interviews, and maintaining analysis materials within a structured existing system.

• Consensus-based decision-making and collaborative teamwork: participating in structured team debriefs to move past disagreements and reach shared analytic insights, a skill relevant for any collaborative research project or social change project.

• Social change insights: Learning from impactful social change-making organizational practices that sustain their transformative change work.

Required Courses/Experiences

1. Interest in social-community psychology research

2. Passion for social justice, social change, and/or care work (including non-profit work, counseling, clinical-community psychology, legal services, and other areas).

3. Critical thinking, analytical skills, and teamwork abilities

4. Social awareness of one's privileges and societal power inequities

5. Demonstrated readiness for reflexive, social justice-oriented qualitative research in psychology within a PWI context, evidenced by completion of one or more of the following: PSY 360 Applied Social Psychology; PSY 470 Qualitative Research Methods; PSY 448/449 Research Internship with Dr. R

Preferred Courses/Experiences

1. Strong writing and research skills

2. Experience working with care work (ABA counseling, childcare, eldercare, tutoring, teaching), nonprofit service organizations, or community organizing and activism.

3. Willingness to engage in critical reflexivity training (anti-racism, intersectional feminisms, Queer solidarities, and class awareness).

4. Prior coursework or experience in qualitative research methods

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Creativity Within Reason: Developing a Tool to Probe Children's Evaluation of Creative Ideas

Julie Vaisarova (she/her)

Psychology and Child Development

jvaisaro@calpoly.edu

Research Project Description

Having innovative ideas that make it out of the creator's mind into the world requires not just generating out-of-the-box possibilities but also taking a step back to reflect and assess whether these ideas will truly be effective. However, our understanding of how this aspect of creative thinking develops in early childhood remains unclear due to a lack of child-appropriate measures. This project will aim to validate a newly developed measure of 4- to 7-year-old children's capacity for evaluating creative ideas – the Object Evaluation Task. Rather than asking children to brainstorm many ideas, as in the divergent thinking tasks that are commonly used to study children's creativity, the Object Evaluation Task will ask children to choose from four different tools to solve an everyday problem. The extent to which children successfully select the tool that best fits the physical constraints of the problem will help us assess their capacity pause, reflect, and evaluate each possible solution. The Object Evaluation Task is meant to be a methodological tool that can support future research probing how interactions between children's developing cognitive skills and the social contexts they inhabit give rise to creativity across early childhood. A better understanding of these mechanisms has the potential to help caregivers, teachers, and early childhood programs target their strategies for nurturing creativity.

BEACoN Scholar’s Role in the Project

The BEACoN Research Scholar will join a collaborative team of student researchers and contribute to the following aspects of this ongoing project: 

• Sharing information about our study with families to facilitate participant recruitment. This will include attending on- or off-campus events to talk about our research and reaching out to interested families via email.

• Collecting data with children and families. This will involve meeting with families on campus, explaining the study to children and caregivers, obtaining appropriate consent and assent, and conducting a series of game-like tasks (including the Object Evaluation Task) with the child according to a consistent research protocol.

• Processing study data. This will include transcribing children's responses to open-ended questions from video recordings and scoring these responses on different characteristics (e.g., creativity).

• Conducting quantitative data analyses, creating data visualizations, and helping to develop research presentations (based on interest).

The BEACoN scholar will also read relevant empirical articles and participate in regular lab meetings, during which we discuss current research, reflect on project progress, and give each other feedback (e.g., on upcoming presentations). There will be opportunities to lead a team discussion and/or share work for feedback (e.g., prior to the BEACoN symposium).

Skills the BEACoN Scholar will Gain

The BEACoN scholar will gain hands-on experience with the process of conducting empirical, quantitative research in developmental psychology. They will…

• Become more familiar with contemporary research questions and findings in the scientific study of childhood creativity and cognitive development.

• Develop a deeper understanding of research methodology in developmental science (e.g., measure selection, reliability, types of data, data coding).

• Expand their understanding of ethical considerations when working with children and families, including learning to appropriately obtain informed consent and assent from families and becoming familiar with the IRB review process.

• Learn to manage and store participant data in accordance with ethical principles and research management best practices.

• Build collaboration, communication, and organizational skills by working as part of a research team.

• Gain experience working with and visualizing quantitative data, and have the opportunity to develop familiarity with the statistical software R if desired.

• Develop research communication skills by speaking about our study with potential participants and contributing to research presentations.

• Participate in lab discussions and one-on-one mentorship regarding potential career pathways in psychology and preparation for graduate school.

Required Courses/Experiences

• Strong attention to detail, time management, and reliability

• Strong communication skills

Preferred Courses/Experiences

• Previous experience working with children and families (e.g., as a babysitter, camp counselor, preschool aide, etc.)

• Completion of one or more of the following courses: Introductory Psychology, Research Methods in Psychology, Developmental Psychology

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Postsecondary Pathways of the "Two or More Races" Population: A Critical Multiracial Spatial Analysis

Jacob Campbell (he/him)

Higher Education Counseling and Student Affairs

jcampb47@calpoly.edu

Research Project Description

This project is rooted in Critical Race Spatial Analysis and Critical Multiracial Theory, which collectively consider how geography compounds educational inequities impacting multiracial college students. The 2000 U.S. Census was the first to allow respondents to self-report more than one race, and the "Two or More Races" category has since served as a proxy for the nation’s multiracial population. As of 2010, "Two or More Races" has been a required category in federal reporting to the U.S. Department of Education’s Integrated Postsecondary Education Data System (IPEDS). However, limited quantitative research exists mapping the educational trajectories of college students in the "Two or More Races" category. Thus, the purpose of this project is visualize national trends in "Two or More Races" college access, enrollment, and outcomes using publicly available datasets.  

BEACoN Scholar’s Role in the Project

The BEACoN Research Scholar will play a pivotal role in expanding a pilot data visualization dashboard, scaling from one state to nationwide. With intentional training and ongoing mentorship, the primary expectations of the BEACoN Research Scholar include:

• Attending weekly project meetings
• Preparing large datasets (e.g., U.S. Census, IPEDS) for analysis using Excel
• Developing data visualizations in Tableau
• Analyzing trends across geographic regions using descriptive statistics
• Contributing to research manuscripts and conference proposals  

Skills the BEACoN Scholar will Gain

• Accessing and analyzing publicly available national datasets
• Utilizing Excel to merge multiple datasets
• Building interactive, map-based data visualizations in Tableau
• Applying Critical Race Spatial Analysis and Critical Multiracial Theory to make meaning of geographic trends and descriptive statistics
• Drafting research manuscripts and conference proposals  

Required Courses/Experiences

No prior coursework is required for this role, but applicants should have an interest in educational equity and multiracial students.  

Preferred Courses/Experiences

Some experience with Excel and/or Tableau preferred.

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Breaking the Brakes: How the Loss of miR-34 Drives Cellular Aging and Cancer

Delaney Dann (she/her/hers)

Biological Sciences

dcdann@calpoly.edu

Research Project Description

For decades, scientists believed that genetic information flowed in a clean, linear path: DNA makes RNA, and RNA makes protein. This view was revolutionized by the discovery of microRNAs, tiny molecules that do not code for any protein themselves but instead act like volume knobs capable of quietly tuning hundreds of genes at once. Among these, miR-34 stands out as a critical regulator of cellular growth, activated by the tumor-suppressor gene p53. In cancer cells, miR-34 is switched on to silence a network of genes that would otherwise drive unchecked cellular growth. When miR-34 is lost or silenced, a common feature of multiple human cancers, these molecular guardrails disappear and dangerous cancer-promoting genes run rampant, allowing damaged cells to bypass critical safety checks and multiply unchecked. The therapeutic potential of miR-34 has not gone unnoticed, as clinical trials have tested miR-34 mimics in patients with advanced cancers, reflecting the broader promise of microRNA-based medicine. However, these efforts have also revealed that manipulating miR-34 in a living system is far more complex than anticipated, underscoring the need for deeper mechanistic understanding of how and when miR-34 acts.

What makes miR-34 fascinating, and not yet fully understood, is its complex dual nature across a lifespan. While its activity should theoretically protect against cancer, miR-34 levels rise sharply with age across species. Rather than preserving health, this chronic late-life elevation appears to also suppress important genes involved in cellular maintenance and repair, contributing to tissue decline. This project investigates this biological paradox using the microscopic roundworm C. elegans, which relies on these same molecular pathways as humans but lives for only a few weeks, making it a uniquely practical window into the biology of aging and cancer. By comparing aging wild-type worms with worms lacking miR-34, this project aims to provide novel insight into how and when a crucial cellular protector transforms into a potential driver of aging.

BEACoN Scholar’s Role in the Project

The BEACoN Research Scholar will be an active contributor to every stage of this project, performing experiments, collecting and analyzing data, and presenting their findings. In Fall semester, the Scholar will focus on building foundational skills in the lab: learning to maintain and handle C. elegans cultures, identifying life stages under the microscope, synchronization of life stages, and practicing RNA isolations to develop the technical consistency this protocol requires.

In Spring semester, the Scholar will carry out the primary research. They will collect synchronized populations of wild-type and miR-34 deletion mutant worms at defined timepoints across lifespan, extract RNA, synthesize cDNA, and perform quantitative PCR to measure the expression of a panel of miR-34 target genes, including both oncogenic targets relevant to cancer suppression and age-related targets implicated in tissue maintenance and decline, at each timepoint.  The Scholar will be responsible for organizing their own data, calculating relative gene expression using standard normalization methods, and constructing figures suitable for publication. Throughout the project the Scholar will meet weekly with the faculty mentor, participate in lab meetings, read and discuss primary literature relevant to the project, and deliver a formal research presentation at the end of the year summarizing their findings.

Skills the BEACoN Scholar will Gain

The BEACoN Research Scholar will develop a strong and transferable foundation in molecular biology techniques used daily in academic, clinical, and industry research settings. On the organismal side, the Scholar will become proficient in C. elegans culture and handling, including staging animals by developmental age under the microscope. Further, RNA isolation from a small multicellular organism is technically demanding, requiring strict attention to contamination prevention and sample quality, and mastering it is itself a meaningful accomplishment. The Scholar will learn cDNA synthesis and quantitative PCR, including the principles behind primer design, reaction optimization, and the use of reference genes to normalize expression data across samples. These techniques are among the most widely used in modern biological and biomedical research and are directly applicable to graduate school, medical research, biotechnology, and clinical laboratory careers.

Beyond bench skills, the BEACoN Research Scholar will gain experience in the full arc of scientific research: forming a hypothesis grounded in published literature, designing controlled experiments, managing and organizing raw data, applying appropriate statistical analysis (t-tests and ANOVA), and interpreting results in the context of what is already known. Finally, through weekly mentorship meetings, lab meeting participation, primary literature discussions, and a formal end-of-year presentation, the Scholar will build scientific communication skills that are essential for any career in the life sciences, including how to read research papers critically and present data clearly to both specialist and general audiences.

Required Courses/Experiences

Curiousity is the most important qualitiy to bring to this project as well as an interest in genetics and/or molecular biology. Course experience of BIO 161 (1161) or equivalent required.

Preferred Courses/Experiences

BIO 351 (3351) Principles of Genetics preferred.

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A Derivatives-First Intervention in Calculus I: Improving Conceptual Understanding and Pass Rates Through Content Reordering

Saba Gerami (she/her)

Mathematics

sgerami@calpoly.edu

Research Project Description

The research objective of this project is to test whether reordering Calculus I content—teaching derivatives before limits—improves student conceptual understanding and pass rates. Calculus I is a critical gateway course for STEM majors, yet it remains a significant barrier to student success nationwide. Students come to the course with a wide range of mathematical preparedness and struggle with the rapid progression of the content, finding it difficult to develop procedural fluency while simultaneously understanding how these concepts build upon and connect to one another. To potentially address these issues, this project proposes a simple yet potentially transformative pedagogical intervention: reordering Calculus I content by teaching derivatives first, then using limits as a conceptual tool to define and deepen understanding of derivatives, and closing the course with applications of derivatives and integrals. Through a quasi-experimental study conducted over Fall 2026 and Spring 2027, this project will compare student outcomes in two business-as-usual versus two reordered sections, all taught by the same instructor. A student researcher will help revise course materials, design and analyze assessments, and share findings at national conferences. By comparing knowledge-test gains, exam performance, and pass rates across the two approaches, as well as analyzing students' own reflections on their experience, the project aims to improve student success at Cal Poly while contributing empirical evidence to the national conversation on evidence-based calculus instruction.

BEACoN Scholar’s Role in the Project

This project provides comprehensive research experience for one (or two) undergraduate student researcher who will contribute to all phases of the study—from curriculum and assessment development through data analysis and dissemination. As a co-researcher, the student will exemplify Cal Poly’s learn-by-doing model in the following ways:

• Phase 1 - Curriculum Development and Assessment Design: Working alongside the PI, the student will revise existing Calculus I course materials to reorder content for the derivatives-first experimental sections. This involves analyzing pedagogical rationale, restructuring notes and assignments, and developing assessment instruments (pre/post knowledge tests, surveys).
• Phase 2 - Data Collection and Management: The student will support IRB-compliant data collection procedures, including administering assessments, distributing surveys, and managing data files. The student will learn proper research protocols, data cleaning, de-identification procedures, and organizational systems for managing the data.
• Phase 3 - Data Analysis and Manuscript Preparation: The student will work with the PI to analyze quantitative data (comparing pre-to-post gains, pass rates, final exam performance) and qualitative data (student reflections). The student will interpret the findings and prepare the results for scholarly dissemination.
• Dissemination (throughout the project): The student will contribute to scholarly writing and two external conferences: Joint Mathematics Meetings (January 2027 meeting), and Research in Undergraduate Mathematics Education conference (February 2027 meeting). The student will be a co-author in all conference presentations and manuscripts resulting from this work.

Skills the BEACoN Scholar will Gain

Through this comprehensive experience, the student will develop expertise in education research methodology and in both quantitative and qualitative data collection and analysis. On the quantitative side, the scholar will learn to clean and manage datasets and to run statistical comparisons of student outcomes (such as pre- and post-test gains and exam performance across sections). On the qualitative side, they will learn to code open-ended student reflections—systematically labeling responses to identify recurring themes—and to build codebooks and calculate intercoder reliability, a measure of how consistently two researchers apply the same codes, which establishes the trustworthiness of the analysis. The scholar will also gain experience in academic writing and presentation, aiding the faculty mentor in co-authoring conference proposals and journal articles. Specifically, they will learn to write abstracts, conduct literature reviews, prepare and present research posters at conferences, prepare materials for conference submissions, and submit research for publication. Together, these skills position the student for future opportunities in research, graduate programs, or related careers.

Required Courses/Experiences

Calculus 1 and 2
Interest in STEM education
Be able to follow instructions and complete assignments before deadlines
Communication and organization skills
Knowledge of Microsoft Office or be willing to learn quickly

Preferred Courses/Experiences

None

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Developing New Methods to Detect Tiny Particles and Study Their Role in Host-Pathogen Interactions

Mallary Greenlee-Wacker (she/her)

Biological Sciences

mcgreenl@calpoly.edu

Research Project Description

In a protective immune response, white blood cells recognize and destroy bacteria, promoting a return to homeostasis. However, problems arise when bacteria evade the immune system or when the immune system unintentionally damages host tissues. Neutrophils are the first type of white blood cell to arrive at the site of a bacterial infection and are critical for host defense. Like all cell types, they release extracellular vesicles (EVs), tiny membrane bound particles that carry proteins, lipids, and other molecules out of the cell. We recently discovered that EVs released by neutrophils following bacterial challenge promote blood clotting, suggesting that they may contribute to the coagulation abnormalities that prevent blood flow and damage healthy tissues and organs. However, because EVs are approximately 150 nm in diameter, they are difficult to detect and distinguish from background debris using standard laboratory methods.

The goal of this project is to develop a new flow cytometry method to identify and quantify neutrophil derived EVs. The student will use proteomic data to identify proteins enriched on EVs and test fluorescent antibodies and membrane dyes as markers for vesicle detection. These experiments will compare labeled EVs with appropriate controls to determine which combinations best distinguish EVs from non vesicular particles. Developing a reliable detection method will provide the foundation needed to investigate how neutrophil derived EVs are produced and how they contribute to host responses during bacterial infection. Furthermore, EVs and related lipid nanoparticles are being developed as therapeutic delivery systems, making methods to detect and characterize these particles increasingly important in biotechnology.

BEACoN Scholar’s Role in the Project

The BEACoN Research Scholar will work with our research team to develop and optimize a method for detecting extracellular vesicles by flow cytometry. The student will read and discuss primary literature, analyze proteomic datasets to identify candidate extracellular vesicle markers, isolate neutrophils and EVs, optimize fluorescent antibody and membrane dye staining, and perform flow cytometry experiments. The student will maintain an electronic laboratory notebook, organize and graph data, and participate in weekly discussions to interpret results and plan follow up experiments. As the project progresses, the student will take increasing ownership of experiments, present research updates during lab meetings, and prepare a poster for presentation at the BEACoN Research Symposium.

Skills the BEACoN Scholar will Gain

The BEACoN Research Scholar will gain experience in biotechnology methods, experimental design, data management, data analysis, scientific communication, and professionalism.

Biotechnology methods: Bacterial and mammalian cell culture, aseptic technique, primary human cell isolation, flow cytometry, immunoblotting, microscopy, and quantitative data analysis.

Experimental design: Designing experiments, selecting appropriate controls, troubleshooting assays, interpreting results, and planning follow-up experiments.

Data management and analysis: Maintaining an electronic laboratory notebook, organizing data, generating publication-quality figures, and applying basic statistical analyses.

Scientific literacy: Reading and interpreting the primary literature and applying published findings to experimental design.

Scientific communication: Presenting research during lab meetings, campus research symposia, and, when appropriate, regional and national conferences.

Professional development: Career exploration and informational interviews, CV and LinkedIn development, personal statements, and internship and graduate school preparation, as applicable.
 

Required Courses/Experiences

BIO 161/BIO 1151 (or equivalent) is required.

Preferred Courses/Experiences

No prior research experience is necessary. An interest in cell biology, immunology, microbiology, or human health is encouraged.

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Using Mathematics, Artificial Intelligence, and Single-Cell Genomics to Understand Cell Fate Decisions

Meilin Huang

Chemistry and Biochemistry

mhuang96@calpoly.edu

Research Project Description

Every cell in the human body contains essentially the same DNA, yet cells develop into many different types, such as neurons, muscle cells, or immune cells. Understanding how cells make these decisions is one of the central questions in modern biology and has important applications in regenerative medicine, cancer research, and developmental biology. Recent advances in single-cell genomics allow scientists to measure the activity of thousands of genes in individual cells, creating exciting opportunities to understand how cells change over time. This project seeks to establish a research collaboration between Cal Poly and Dr. Jianhua Xing's laboratory at the University of Pittsburgh, which develops computational methods for studying cellular dynamics using single-cell genomic data.

The BEACoN Research Scholar will work with publicly available single-cell datasets and computational tools to analyze gene expression patterns, visualize cellular trajectories, evaluate computational models, and help improve data analysis workflows. The student will receive hands-on training in interdisciplinary research at the interface of biology, mathematics, and computer science while developing skills in research practices and scientific communication. Students majoring in biology, chemistry, mathematics, computer science, and related disciplines who are interested in computational biology are encouraged to apply.

BEACoN Scholar’s Role in the Project

The BEACoN Research Scholar will become an active member of an interdisciplinary research team. Responsibilities may include reviewing scientific literature, learning existing software, analyzing publicly available datasets, benchmarking methods, testing workflows, generating figures, documenting analyses, reproducing published results, and, if appropriate, exploring extensions to existing computational methods.

Skills the BEACoN Scholar will Gain

The student will gain experience in computational biology, bioinformatics, data analysis, and scientific computing. Specific skills may include Python programming, analysis of single-cell genomics data, data visualization, version control, scientific literature review, statistical interpretation of computational results, and effective scientific communication. The student will also learn how mathematics, machine learning, and systems biology are integrated to investigate complex biological questions and will develop experience working within an interdisciplinary research environment.

Required Courses/Experiences

No prior research experience is required. Students should have completed at least one introductory course in biology, chemistry, computer science, mathematics, or statistics and should be willing to learn computational tools. Curiosity, motivation, and a willingness to learn are essential.

Preferred Courses/Experiences

Coursework or experience in biochemistry, molecular biology, genetics, bioinformatics, computer science, data science, applied mathematics, statistics, or Python programming is preferred but not required. Prior research experience is beneficial but not necessary.

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Building Community Capacity for Arts Education: Research, Relationship Building, and Advocacy

Crystal Mercado (She/Her/Ella)

Liberal Studies

cmerca12@calpoly.edu

Research Project Description

This project explores how community-engaged and arts-based research can strengthen local arts education by documenting existing opportunities, identifying gaps, and fostering stronger connections among the people and organizations that support creative learning. Building on research initiated through the FROST Undergraduate Research Program, this work examines the current arts education landscape across San Luis Obispo County and neighboring communities while exploring how schools, artists, cultural organizations, and community members work together to create meaningful arts experiences for young people. Although California has expanded funding for arts education through initiatives such as Proposition 28, many communities continue to face challenges related to staffing, coordination, communication, and equitable access.

As the research has evolved, its focus has expanded beyond understanding the existing landscape to exploring how research itself can strengthen local arts ecosystems. By bringing together educators, artists, administrators, parents, and community organizations, the project seeks to foster collaboration, support shared learning, and build momentum for long-term arts education advocacy. Ultimately, this work aims to help lay the foundation for a regional Arts Education Planning Team that can support more connected, equitable, and sustainable arts education opportunities throughout the region.

BEACoN Scholar’s Role in the Project

As part of this project, the BEACoN Research Scholar will help investigate the current arts education landscape across San Luis Obispo County and neighboring communities while building relationships with educators, artists, administrators, parents, and community organizations. Together, we will analyze publicly available arts education data, conduct interviews and community conversations, explore arts-based research methods, and identify opportunities to strengthen collaboration across schools and community partners. The goal is to better understand the region's arts education ecosystem and help lay the foundation for a regional Arts Education Planning Team that can support long-term advocacy, collaboration, and equitable access to high-quality arts education.

Skills the BEACoN Scholar will GainThe BEACoN Research Scholar will gain experience in community-engaged and qualitative research methods, including document analysis, stakeholder mapping, interview preparation, community outreach, qualitative data organization, and thematic analysis. The scholar will also learn how to synthesize information from public datasets, district arts plans, and community conversations to better understand local arts education systems. In addition, students will develop skills in professional communication, relationship-building, project management, and arts-based research while contributing ideas, asking critical questions, and helping shape the direction of the research throughout the project.

Required Courses/Experiences

LS270/LS2370

Preferred Courses/Experiences

No specific coursework is required. Experience with qualitative research, data organization, community engagement, advocacy, education, or the arts is helpful but not necessary. The ideal candidate is curious, self-motivated, and comfortable communicating with new people, whether through email, phone calls, or in-person conversations. Because this project involves building relationships with community partners, students should be willing to take initiative, ask thoughtful questions, engage professionally with stakeholders, and contribute ideas throughout the research process.

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Extreme Temperatures, Greenspace, and Brain Health among Older Adults in California.

Erika Meza (she/her)

Kinesiology and Public Health

emeza08@calpoly.edu

Research Project Description

Research shows that extreme temperatures, such as heat waves, are becoming more prevalent and negatively impact public health. Extreme heat exposure is linked to higher cardiovascular morbidity and mortality, such as myocardial infarction, stroke, and sudden cardiac death, especially in older adults. Extreme temperatures may trigger dehydration, electrolyte imbalances, and stress on the heart, and affect blood pressure, all of which are related to brain health and cognition. Research on temperature and cognition is limited and inconsistent; some studies show worse cognitive performance with heat and cold, others show no effect. Most studies focus on short-term exposure and cross-sectional assessments; long-term effects and studies in diverse racial and ethnic groups are lacking.

Diverse racial and ethnic communities and lower socioeconomic groups often face more temperature extremes due to disinvestment, housing segregation, and urban development. These populations are more likely to live in urban heat islands—areas with higher temperatures caused by dense infrastructure and limited vegetation. These structural inequities in urban development, along with neighborhood-level characteristics, such as access to greenspace, could also modify exposure and vulnerability. Prior research has also found that greenspace is associated with better cognitive function and slower cognitive decline. This means greenspace could act as an effect modifier, attenuating the adverse cognitive impacts of cumulative temperature exposures. This presents a significant gap in the literature, as marginalized racial and ethnic groups experience differential access to greenspace and a higher risk of cognitive impairment and incident dementia. Understanding how environmental factors, such as ambient temperature and greenspace affect cognitive function across diverse racial and ethnic populations is critical for devising effective public health strategies that are properly targeted and equitable. In this study, we will use two diverse cohorts of older adults in California to quantify the association between ambient temperature and cognitive function, and to examine whether access to green space and race or ethnicity may modify this association.

BEACoN Scholar’s Role in the Project

The BEACoN research scholar’s primary responsibilities will include: 1) identifying relevant peer-reviewed research papers, 2) developing a thorough literature review of recent studies on extreme heat and brain health, 3) developing abstracts, flow charts, and figures to illustrate our statistical findings, and 4) synthesizing results to produce a final report and/or presentation.  

Skills the BEACoN Scholar will Gain

Literature search and evidence gathering. Students will learn how to identify relevant peer-reviewed research, use academic databases, assess whether studies are appropriate for the research question, and organize sources for a literature review.

Literature review synthesis and writing. Students will learn how to synthesize recent studies on extreme heat and brain health, identify common themes across the literature, and describe gaps that motivate current research.

Public health and environmental health content knowledge. Students will build substantive knowledge about extreme heat as a climate-related exposure and its potential relationship to cognitive function, brain health, aging, and health inequities.

Data visualization and science communication. Students will learn how to create flowcharts, figures, and visual summaries that communicate statistical findings clearly and accessibly.

Presentation Skills. Students will practice integrating background literature, study findings, and public health implications into a final report and/or presentation.  

Required Courses/Experiences

Applied Epidemiology (HLTH 318)

Preferred Courses/Experiences

Research Methods (HLTH 402)

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Fostering Transfer Student Belonging and Success

Rosie Ojeda (she/her/hers/ella)

Liberal Studies

rvojeda@calpoly.edu

Research Project Description

Transfer students face a unique set of both challenges and opportunities as they integrate into four-year universities (Bustillos, 2017; Shaw & Chin-Newman, 2019). This project will investigate the experiences of transfer students at Cal Poly. This project builds from the Frost SURP conducted in 2025 in the Liberal Studies Department. This BEACON project will have a broader scope and investigate the experiences of transfer students across Cal Poly. Researchers will build partnerships with campus supports, such as the Transfer Center to recruit participants. Researchers will create and distribute electronic surveys, interview participants, analyze survey and interview data, and ultimately make recommendations to support transfer students for Cal Poly faculty and staff. This research seeks to recruit current and former transfer students and possibly even incoming transfer students from local community colleges.

BEACoN Scholar’s Role in the Project

Students will be expected to meet with campus supports to build partnerships to streamline the research and recruit participants. Researchers will create and distribute online surveys and analyze data from these surveys. They will also contact alumni and interested survey participants to invite them to interview which includes setting up interview times. Researchers will interview participants in person or via webcam and record the interview. The interview audio will be transcribed, and then analyzed for themes. Ultimately, researchers will make recommendations for supporting transfer students for Cal Poly faculty and staff. This research project also includes adding to the literature review which includes reading and summarizing research studies.  

Skills the BEACoN Scholar will Gain

The BEACoN research scholar will gain many skills. Time management due to the extensive nature of the research. Collaboration and outreach due to needing to work with or at least consult existing supports for transfer students. Researchers will become familiar with mixed methods (quantitative and qualititative research) Student will be managing data and keeping it private and secrure. Researchers will conduct qualitative analysis including becoming familiar with the institutional review board (IRB) process.

Required Courses/Experiences

None

Preferred Courses/Experiences

Ideally the BEACON research scholar will be a Cal Poly transfer student

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Development of cell-free expression systems toward to production of therapeutic proteins

Javin Oza 

Chemistry & Biochemistry

joza@calpoly.edu

Research Project Description

Some of the most promising new medicines and diagnostic tests begin with a protein "binder," a small, custom-built protein that functions like an antibody to latch onto a specific target such as a cancer marker, a virus, or a toxin, with the precision of a key fitting a lock. Te research project creates these binders using cell-free expression, a biotechnology that harnesses the genetic code to produce proteins directly in a test tube, without relying on living cells. The challenge this project tackles is stability. The most useful binders are held together internally by chemical bridges called disulfide bonds, which act like molecular staples that lock a small protein into a rigid, durable shape so it can grip its target tightly and survive heat, long-term storage, and the environment inside the human body. Forming these staples in the right positions requires special chemical conditions that standard cell-free systems cannot support, and overcoming that limitation is what makes designing disulfide-bonded binders both difficult and exciting.

In this Learn By Doing project, students will work at the interface of computational design and hands-on biochemistry to optimize cell-free systems to build disulfide-bonded binders from scratch. On the computer, students will use modern AI protein-design tools to generate candidate binder structures, position disulfide staples correctly, and predict which designs are most likely to fold and bind their target. At the bench, students will produce their top designs on a disulfide-compatible cell-free platform and test whether the proteins fold properly and recognize the intended target. Along the way, students contribute to a broader goal of our group: making protein-binder discovery faster, cheaper, and simple enough to move out of specialized research labs and into classrooms and, eventually, real therapeutics and diagnostics. The work will be shared through a research poster, with the potential to contribute to a student-authored publication.

BEACoN Scholar’s Role in the Project

The Research Scholar will focus primarily on hands-on laboratory work, taking computationally designed binder candidates and bringing them to life at the bench. The scholar will begin by reading background literature on cell-free expression, disulfide stabilization, and protein binders to build a foundation for the work. Working from a panel of AI-designed binders provided by the lab, the scholar will then learn and run cell-free expression reactions to produce these proteins, and will help prepare the disulfide-compatible cell extract that powers the system. A central part of the role is optimizing the oxidizing conditions that drive disulfide bonds to form correctly, testing how changes to the reaction affect whether a binder folds into its proper shape. The scholar will characterize their proteins using techniques such as gel electrophoresis and fluorescence-based detection, check how much soluble, properly folded protein is produced, and run binding assays to test whether each binder recognizes its intended target. The scholar will record and analyze results and use them to guide the next round of experiments, gaining direct experience in the build-and-test cycle at the heart of protein engineering. Throughout, the scholar will meet regularly with the mentor for guidance and feedback, and will present their findings as a research poster at the BEACoN Symposium, with the potential to contribute to a student-authored publication.

Skills the BEACoN Scholar will Gain

By the end of the project, the Research Scholar will have developed a strong set of laboratory and analytical skills that are valuable across biotechnology, medicine, and research:

Cell-free expression, including setting up and running protein-synthesis reactions and helping prepare cell extracts
Working with redox and disulfide-bond chemistry, including tuning reaction conditions to improve protein folding
Protein characterization, including gel electrophoresis (SDS-PAGE), fluorescence-based detection, and analysis of soluble versus insoluble protein
Binding and activity assays to test whether a designed protein recognizes its target
Core bench fundamentals such as accurate pipetting, sample handling, and good laboratory documentation
Data collection, interpretation, and troubleshooting, including using results to refine an experimental approach
Scientific communication, including reading primary literature, preparing a research poster, and contributing to written work

Just as importantly, the scholar will practice the patience, attention to detail, and problem-solving that successful experimental research requires.

Required Courses/Experiences

No prior research experience is required. The most important qualifications are curiosity, reliability, and genuine enthusiasm for hands-on laboratory work. Students should have completed introductory chemistry and biology coursework and be comfortable learning new bench techniques with guidance.

Preferred Courses/Experiences

Coursework in biochemistry and organic chemistry are helpful, as is any prior laboratory experience, including course labs. Comfort with careful, repetitive bench work and a methodical approach to experiments will serve a student well in this project. Students who are excited by protein engineering, synthetic biology, or the idea of building new medicines and diagnostics will find this project especially rewarding.

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HPC for All: Making High-Performance Computing for Research Accessible at Cal Poly

Trevor Ruiz (he/him)

Statistics

truiz01@calpoly.edu

Research Project Description

Have you ever hit "run" on a big analysis and then waited hours for your laptop to finish — or wished you could run a hundred versions of a simulation at once? Researchers solve this using high-performance computing (HPC): powerful shared computing clusters that run large jobs far faster than any single machine. In Fall 2025, Cal Poly gained access to an HPC cluster hosted by SDSU called Tide (https://tide.sdsu.edu), but the tools it relies on (Docker and Kubernetes, technologies used in both research and industry) have a steep learning curve and aren't taught in most coursework. This project's goal is to change that by identifying where compute-intensive needs exist among Cal Poly students and researchers and making HPC resources accessible and easy to use through teaching materials and a workshop built around tailored use cases. Part of what makes this project matter is access — making sure powerful research computing is within reach for any interested student, not just those who already know it exists or have the research mentorship to support their use of these tools.

As the BEACoN Research Scholar on this project, you'll learn these tools hands-on, starting from beginner-friendly materials and worked examples, and then help build them into a complete, approachable guide and set of use cases that assumes minimal background beyond familiarity with a scientific computing language such as R or Python. Through informal conversations with faculty and students about their research, you'll help identify and prioritize the use cases worth building. Depending on interest, you will also have opportunities to provide research computing support to Cal Poly students and researchers, subject to your interests and available projects based on need. Along the way you'll develop real programming and research computing skills, and in close collaboration with your mentor you'll (co-)create and (co-)deliver a hands-on workshop that introduces interested Cal Poly students to the system. No prior experience with Docker, Kubernetes, or HPC is expected — learning it from the ground up (and then teaching it) is the core component of the project. If you're curious about scientific computing, enjoy figuring out how things work, and like the idea of helping other students access powerful research tools, this project is for you.

BEACoN Scholar’s Role in the Project

The student will be an active collaborator in further developing a foundation I've already put in place: an initial set of teaching materials (a conceptual guide, a reference cheat sheet, and working end-to-end examples in R and Python) and several candidate use cases the scholar can use as starting points. The scholar will extend and improve this core infrastructure and direction with a focus on making the initial materials more broadly accessible. Their work will fall into four areas outlined below.

1. Learning HPC tools. The scholar will work through the existing examples to learn Docker, Kubernetes, and how to run jobs on the Tide cluster by building container images, submitting and monitoring jobs, and retrieving results by reproducing an end-to-end analysis.
2. Building teaching materials and use cases. The scholar will refine and expand the existing guide so it assumes minimal prior background, using their beginner's perspective to identify and fix where the current materials are confusing. The scholar will also develop a few core use cases tailored to needs identified through informal consultations with Cal Poly students and faculty.
3. Creating and delivering a workshop. Working closely with me, the scholar will help design and co-deliver a hands-on workshop for other Cal Poly students: preparing slides and a live walkthrough, running practice sessions with a small peer audience, and debriefing afterward.
4. Research support (optional). Depending on their interests and project availability, the scholar may apply their skills by providing research-computing support to other students or faculty, or by adapting the tools to a research question of their own.

Throughout, the scholar will manage their work with version control (Git/GitHub), collaborate with me through regular code review, and bring their own ideas and perspective to shape the direction of the work.

Skills the BEACoN Scholar will Gain

The scholar will develop transferrable technical, research, and teaching skills. On the technical and research side, this includes: high-performance computing tools and workflows that enable researchers to run large-scale tasks across powerful shared clusters rather than on isolated machines; industry-standard technologies for packaging and running such work (Docker and Kubernetes); and project management skills including professional methods for managing reproducible code and workflows. These skills are in rapidly growing demand across research and industry. On the teaching side, this includes: technical writing; instructional design; classroom and time management; and public-speaking experience. On the research side, the scholar will gain a concrete understanding of how computational infrastructure supports research across disciplines, and will have opportunities to extend the work into direct research support for other students and faculty, potentially leading to downstream collaborations.

Required Courses/Experiences

Interests in teaching and statistical or scientific/research computing. Experience with a high-level computing language, preferably R or python. If demonstrated through coursework: DATA/STAT 1810 (formerly STAT331), Statistical Computing with R; or, for non-Statistics majors, CSC 1001 (formerly CSC 101), Fundamentals of Computer Science, and CSC 2001 (formerly CSC 202) Data Structures, which together demonstrate comparable programming experience.

Preferred Courses/Experiences

Any combination of past or planned advanced computing or statistical coursework (e.g., STAT431, CSC349, CS364), experience with Git and GitHub, mentored or independent research experience, or teaching/tutoring experience.

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Cultivating Connection: Campus Protective Factors That Foster Belonging, Well-Being, and Student Success

Rachel Smith (she/her)

School of Education

rsmith81@calpoly.edu

Research Project Description

In 2023, the U.S. Surgeon General identified loneliness and social isolation as urgent public health concerns, emphasizing that social connection is essential to health, well-being, and community life. This project applies that national conversation to the college experience by asking: What helps students build meaningful connections and a sense of belonging on campus?

Rather than focusing only on loneliness as a problem, this project takes a strengths-based approach by exploring the protective factors that support student well-being and persistence. The study will examine how undergraduate students experience belonging at Cal Poly and what people, programs, spaces, and experiences help them feel connected. The project will also consider how students' identities shape their campus experiences, recognizing that students may experience belonging differently based on race, ethnicity, gender, first-generation status, transfer status, disability, sexual orientation, and other intersecting identities. Findings from this project may help identify practical recommendations for faculty, staff, and student affairs professionals who want to foster a more connected and supportive campus community.

BEACoN Scholar’s Role in the Project

The BEACoN Research Scholar will be actively involved in multiple stages of the research process. Early in the project, the student will help review literature on loneliness, social connection, student belonging, well-being, retention, and identity in higher education. The student scholar will also complete human subjects research training and participate in developing the interview protocol.

The BEACoN Research Scholar will assist with participant recruitment, scheduling, and data organization. Depending on IRB approval and the student's comfort level, as well as their specific interests, the student scholar may help conduct or co-conduct qualitative interviews with undergraduate students. The student will also assist with reviewing transcripts, identifying patterns in the data, developing codes, and participating in thematic analysis.

Throughout the project, the student will meet regularly with myself as their faculty mentor to discuss research progress, decisions, emerging findings, ethical considerations, and connections to higher education practice. The goal is for the student to experience the full arc of a qualitative research project, from research design to dissemination and potential submission to a peer-reviewed journal.

Skills the BEACoN Scholar will Gain

The BEACoN Research Scholar will gain foundational skills in qualitative research and applied higher education research. These skills will include conducting a literature review, developing research questions, understanding research ethics, preparing IRB materials, creating interview questions, recruiting participants, managing qualitative data, and participating in thematic analysis.

The BEACoN Research Scholar will learn how researchers move from broad social issues, such as loneliness and student well-being, to focused research questions that can be studied in a campus context. They will also learn how to analyze interview data by identifying patterns, developing codes, comparing themes, and connecting findings back to existing scholarship.

In addition to research methods, the BEACoN Research Scholar will gain skills in scholarly communication. They will practice summarizing literature and translating research into practical recommendations for higher education professionals. Because the project focuses on student belonging and identity, the scholar will also develop skills in culturally responsive research practice, including how to approach participant experiences with care, humility, and attention to context.

Required Courses/Experiences

No specific prior research experience or coursework is required. The project is designed to be accessible to students who are new to research and interested in learning through mentorship.

The BEACoN Research Scholar should have an interest in topics such as student belonging, well-being, loneliness, identity, equity, higher education, counseling, psychology, sociology, education, or student affairs.

Preferred Courses/Experiences

Preferred experiences include coursework or interest in areas such as psychology, education, sociology, ethnic studies, gender and sexuality studies, or related fields. Prior experience with qualitative research, interviewing, literature reviews, student leadership, peer mentoring, campus programs, cultural organizations, residence life, advising, or student support work would be helpful but is not required.

BEACoN Research Scholars who are curious about how campus environments shape belonging and well-being would be especially strong fits for this project. Students interested in graduate school, helping professions, higher education, counseling, student affairs, research, or equity-centered institutional change may find this project particularly meaningful.

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From Directed to Self-Determined Learning: Generative AI and Learner Agency

Andrea Somoza-Norton (she/her/hers/ella)

School of Education, Educational Leadership and Administration Program

asomozan@calpoly.edu

Research Project Description

Generative artificial intelligence is changing how students learn, complete academic work, and make decisions about their own learning. This project will examine how AI can support students as they move from instructor-directed learning toward greater independence and self-determined learning. Using the pedagogy–andragogy–heutagogy continuum, we will study how graduate students use AI to clarify concepts, plan learning activities, evaluate information, solve educational problems, reflect on their progress, and design their own learning pathways.

The study will involve approximately 15 graduate students enrolled in three Educational Leadership and Administration courses. Students will participate in a sequence of AI-supported learning activities and may contribute surveys, reflections, and selected learning artifacts to the research. The project will explore when AI strengthens learner agency, confidence, critical thinking, and reflection, as well as when it may create dependence, introduce bias, or raise concerns related to accuracy, privacy, and equitable access. Findings may help educators design more responsible, equitable, and learner-centered approaches to using generative AI in higher education.

BEACoN Scholar’s Role in the Project

The BEACoN Research Scholar will work closely with the faculty mentor throughout the research process and will serve as an active member of the research team. The scholar will begin by completing required human-subjects research training and reviewing literature on generative artificial intelligence, learner agency, pedagogy, andragogy, and heutagogy. The student will help organize the literature, identify key concepts, refine survey and reflection questions, and contribute to the development of a qualitative coding framework.

Because the faculty mentor will be teaching the students participating in the study, the BEACoN Research Scholar will also have an important role in protecting voluntary participation. Under faculty supervision and in accordance with the approved IRB protocol, the scholar will distribute recruitment and consent materials, maintain consent records and participant study codes, and ensure that the faculty mentor does not know who agreed or declined to participate while grades are being assigned. The scholar will complete confidentiality training, store identifiable information only in approved Cal Poly systems, and prepare a de-identified research dataset for analysis.

During data collection and analysis, the scholar will organize survey responses, reflections, and selected learning artifacts; assist with descriptive and pre/post quantitative analyses; and code qualitative data using an established codebook. The scholar will participate in regular research meetings to compare coding decisions, identify themes, interpret findings, and examine how generative AI may support or limit learner agency, critical thinking, reflection, and equitable access to learning resources. The scholar will also help consider issues such as AI bias, accuracy, privacy, prior experience, and possible overreliance on AI.

The scholar will contribute to the dissemination of the findings by developing tables or visual summaries, helping prepare a research poster, and presenting the project at the BEACoN Research Symposium. Depending on the study's progress, the scholar may also contribute to a conference proposal or manuscript.  We are planning to present this project at St Andrews University, Scotland. Throughout the project, the student will receive structured mentoring in research ethics, mixed-methods research, qualitative coding, introductory statistical analysis, scholarly communication, and responsible AI use. Responsibilities will gradually increase as the scholar develops confidence and research independence.

Skills the BEACoN Scholar will Gain

The BEACoN Research Scholar will gain hands-on experience in mixed-methods educational research. The student will complete CITI certification in human-subjects research and learn procedures for informed consent, confidentiality, secure data storage, participant coding, and preparation of a de-identified dataset.

The scholar will develop quantitative skills by organizing pre- and post-survey data, checking for missing information, and calculating descriptive statistics, pre/post comparisons, and effect sizes appropriate for a small sample. The student will also gain qualitative analysis experience by helping develop a codebook, coding written reflections and learning artifacts, comparing coding decisions, and identifying themes related to learner agency and AI use.

Additional skills will include critical AI literacy, research project management, interpretation of mixed-methods findings, preparation of tables and visual summaries, poster development, and presentation of findings at the BEACoN Research Symposium.

Required Courses/Experiences

No prior research experience or specific coursework is required. Applicants should have an interest in education, artificial intelligence, learning, equity, psychology, social science, or related areas. The scholar should be dependable, organized, able to maintain confidentiality, and willing to learn research methods, data management, introductory statistics, and qualitative analysis.

Strong written communication, attention to detail, and comfort working with spreadsheets or digital tools are helpful but not required. The selected scholar will receive training and will complete CITI certification in human-subjects research before working with participant data.

Preferred Courses/Experiences

Preferred qualifications include coursework or experience in education, psychology, sociology, data science, statistics, research methods, artificial intelligence, or related fields. Familiarity with surveys, spreadsheets, qualitative coding, or basic statistical analysis would be helpful but is not required.

Preference may be given to students who demonstrate strong organization, attention to detail, clear written communication, an interest in educational equity and responsible AI use, and the ability to handle confidential information professionally.

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We Must Ensure Physical Activity Promotion, Exercise Science, and Sport Science Research is Generalizable, Transferable, and Socially Just: A Comprehensive and Cross-sectional Study to Examine whether Journal Submission Guidelines in Kinesiology Contain Statements and Reporting Policies that Support Diversity, Equity and Inclusion in Kinesiology Research and Scholarship

Jafra Thomas (he, him, they, them)

Department of Kinesiology and Public Health

jthoma84@calpoly.edu

Research Project Description

To be generalizable, research should use representative samples or address similar factors common to subgroups of people (Drisko, 2025, Research on Social Work Practice). To be transferable, research findings or insights should sensitize readers to ways concepts or trends can be used to understand, critique, and creatively address a problem or topic (Drisko, 2025, Research on Social Work Practice). To be socially just, research practices and interpretation of results should mitigate against systemic factors which limit access, equity, and inclusion within research environments, as well as within settings which results might be applied (Harrison Jr. et al., 2021, Quest). In general however, social injustices persist in kinesiology research (and other areas of study)—despite the benign intentions of researchers, reviewers, and journal editors. There remains serious concern of whether findings or insights, published in kinesiology journals (and other areas of study), are generalizable or transferable (D’Lauro et al., 2022, British Journal of Sports Medicine). For example, French and Cardinal (2021) analyzed the characteristics of participants reported in 200 research articles published in the, Recreational Sports Journal, between 2005 and 2019. Only 1% of articles reported sampling individuals with a disability or investigating ways disability may intersect with participation in recreational sport programs or activities. Percentages, however, were marginally better concerning race-ethnicity or gender. Researcher inattention to issues of under- or no representation, and systemic barriers to participating in kinesiology research, reinforces invisibility and marginalization in sport, physical activity promotion programs, and therapeutic exercise services (Position Stand on Inclusion in Exercise Science; Navalta et al., 2024, International Journal of Exercise Science). We must ensure kinesiology research is socially just and generates findings that are generalizable and transferable. To do this, we must better understand the extent kinesiology journal submission guidelines support diversity, equity, and inclusion in kinesiology research and scholarship. This topic is under-investigated. The pilot research that led to the present project might be the first such study (Thomas et al., in press, International Journal of Exercise Science).

The present research opportunity is to analyze a dataset of kinesiology journal submission guidelines (N = 55), randomly sampled from a curated database comprised of highly ranked academic journals. The objective of this research project is to explore whether journals sampled from the database often include statements and reporting policy within their submission guidelines that support diversity, equity, and inclusion in kinesiology research and scholarship. The journals that were sampled mainly publish research in one of the following subdisciplines: Exercise Physiology, Exercise Science, Physical Education, Sport Management, Sports Medicine, and Sport Psychology. Under the mentoring faculty’s tutelage, the student will utilize the computer software, Statistical Package for the Social Sciences, to conduct statistical analysis of the project’s dataset, which characterizes the included journals’ submission-guideline statements and reporting policies. This mentoring project will guide the student in appropriately selecting statistical procedures for meeting the project's research objectives, in rigorously interpreting the results, and in generating professional summary tables and data visualizations of study findings. The student will receive mentorship in framing the study’s topic and discussing the study’s findings for a professional audience, through co-writing a manuscript for peer reviewed publication. The intention is to submit the study's manuscript for peer reviewed publication by June 2027, and for the student to disseminate the study's findings at Cal Poly’s 2027 BEACoN Research Symposium.
 

BEACoN Scholar’s Role in the Project

1. Become familiar with the structure and logic of the project’s dataset database.
2. Understand basic requirements for managing and analyzing data using the computer software, Statistical Package for the Social Sciences.
3. Understand basic principles for accurately and comprehensively interpreting statistical results.
4. Understand basic principles for generating accessible and professional data visualization outputs, in accordance with the latest publication manual guidelines of the American Psychological Association.
5. Understand basic reporting guidelines for composing major sections of a manuscript for peer-reviewed publication consideration (the major sections are the Title, Abstract Introduction, Methods, Results, Discussion, and References List)
6. Develop proficiency in analyzing and explaining ways the study findings compare or contrast with previous relevant research.
7. Develop proficiency in generating statements of implication for kinesiology, based upon the study’s original findings and their comparison to, or contrast with, previous research.
8. Maintain records using assigned research space and online shared drives (e.g., file folders).
9. Develop proficiency in self-directed learning in regard to data management, statistical analysis using standard statistical software, and the generation of visually appealing and accurate data tables and figures.

Skills the BEACoN Scholar will Gain

1. Knowledge and skill in interpreting and discussing results form a quantitative content analysis study.
2. Knowledge and skill in engaging in inclusive writing practices and writing for a general academic and professional audience.
3. Knowledge and skill in professional communication while working on a research project team.
4. Knowledge and skill in brainstorming for, drafting, and refining writing for professional presentation and manuscripts, compliant with the latest publication manual guidelines of the American Psychological Association.
5. Knowledge and skill in data management and integrity by keeping updated records, following instructions, so future analysis or reporting using database data is trustworthy.

Required Courses/Experiences

1. Introductory course in management and analysis of quantitative data using standard computer software (preferably, Statistical Package for the Social Sciences). Example introductory courses include: STAT 1000 (Statistical and Data Literacy), STAT 1100 (Applied Statistical Concepts and Methods)
2. Completion of GE Area 1 (formerly GE Area A), with a B-letter grader or higher in all courses.
3. Demonstrated experience with working independently to complete tasks with expediency and consistent with instructions or guidelines that have been provided.
4. Completion of an Introductory Sociology Course with a B-letter grade or higher. Example courses include: SOC 1111 (Social Problems), SOC 2201 (Foundational Sociological Perspectives on Society).
5. Proficiency in effectively conducting a search of an electronic database, or of the Internet, to locate relevant information or literature published in the recent to distant past (e.g., periodicals, books, journal articles, videos).

Preferred Courses/Experiences

1. Completion of an advanced undergraduate course in data management and statistical analysis, with a B-letter grade or higher. Example courses include: STAT 3520 (Statistics II), STAT 3540 (Statistical Methods for Study Design and Analysis)
2. Completion of a writing-intense undergraduate course, satisfying GE Upper-Division Area 4, with B-letter grade or higher. (Note: GE Upper-Division Area 4 is formerly GE Upper-Division D).
3. Completion of an undergraduate research methods course with a B-letter grade or higher. Example courses include: KINE 3319 (Introduction to Research Methods in Kinesiology), HLTH 4402 (Research Methods in Public Health Settings).
4. A history of satisfactory to outstanding completion of work where strong skills in communication, time management, and organization were necessary.

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Searching for New Physics Through the Higgs Boson Using Data From CERN's Large Hadron Collider

Jason Veatch (he/him)

Physics

jveatch@calpoly.edu

Research Project Description

The Standard Model of particle physics is one of the most successful scientific theories ever developed, accurately describing the known fundamental particles that make up our universe and their interactions. Despite its remarkable success, the Standard Model leaves many fundamental questions unanswered, including the nature of dark matter, the origin of the matter-antimatter asymmetry in the universe, how gravity fits into our understanding of fundamental forces, and whether additional fundamental particles or forces remain to be discovered. One of the most promising ways to search for new physics is by studying the Higgs boson, which was discovered at CERN's Large Hadron Collider in 2012.

This project searches for new physics in the Higgs sector using three complementary approaches. The first approach searches for new particles in proton-proton collision data recorded by the ATLAS detector. These searches require developing sophisticated data analysis techniques, reconstructing particles produced in collisions, estimating Standard Model backgrounds, optimizing event selection, and determining whether the data show evidence for previously undiscovered particles. The second is phenomenological research, in which theoretical models are studied using Monte Carlo simulations and computational tools to identify promising signatures of new physics and guide future searches at the Large Hadron Collider. The third is scientific software development, where new Python-based software is created to efficiently compare theoretical predictions with experimental measurements by combining optimization algorithms, numerical methods, and high-performance scientific computing.

BEACoN Scholar’s Role in the Project

The BEACoN Research Scholar's specific role will be determined based on their interests, prior coursework, programming experience, and professional goals. This flexibility allows students with different backgrounds and strengths to make meaningful contributions while continuing to develop new skills throughout the project.

Depending on this match, the student may contribute to one of three related aspects of the project. A student working on an ATLAS data analysis project will work on a variety of aspects, including helping develop analysis code, studying simulated signal and background samples, reconstructing particle candidates, optimizing event selections, applying machine learning techniques, estimating background contributions, evaluating systematic uncertainties, or interpreting statistical results. A student working on phenomenological studies will read literature on beyond-the-Standard-Model theories, generate and analyze Monte Carlo samples, compare predicted signatures across models, identify promising search channels, and summarize results that could guide future ATLAS analyses. A student working on scientific software development will contribute to Python-based tools for interpreting experimental limits, implement and test numerical optimization methods, improve code structure and documentation, validate results, and develop examples that make the software easier for other researchers to use.

All students will participate in the broader research process: reading relevant papers, writing short literature synopses, learning the software tools needed for their project, keeping organized records of their work, presenting progress in meetings, and preparing a final presentation or poster for the BEACoN Research Symposium. The goal is for the student to move from guided training toward an increasingly independent contribution to an active research program in particle physics.

Skills the BEACoN Scholar will Gain

The specific technical skills the BEACoN Research Scholar develops will depend on the aspect of the project to which they are matched. All students, however, will gain experience with authentic scientific research and will develop transferable research and professional skills, including:

• Reading and evaluating scientific literature

• Scientific problem solving and critical thinking

• Written and oral scientific communication

• Working within a large international research collaboration

• Organizing and documenting computational research

Depending on their research project, students will also develop specialized technical skills.

Experimental Particle Physics

• Scientific programming using Python, C++, and ROOT

• Statistical data analysis

• Machine learning techniques

• Particle reconstruction and event selection

• Background estimation

• Systematic uncertainty evaluation

• Software tools used in experimental particle physics

Phenomenology

• Monte Carlo simulation

• Computational physics

• Theoretical model building

• Data analysis and interpretation

• Parameter-space exploration

• Connecting theoretical predictions with experimental searches

Scientific Software Development

• Scientific Python programming

• Numerical optimization

• Software engineering

• Version control (Git)

• Software testing and documentation

• Development of reliable, reusable research software

These technical and professional skills are broadly transferable to graduate study and careers in physics, data science, software engineering, scientific computing, engineering, and other quantitative disciplines.

Required Courses/Experiences

Because students will be matched to different aspects of the research program based on their background and interests, the required preparation depends on the specific project. In general, students should have:

• At least one course in computer programming.

• Completion of Calculus I (or equivalent mathematical preparation).

• Strong analytical, problem-solving, and quantitative reasoning skills.

• A willingness to learn new scientific software and computational techniques.

For students working on experimental particle physics or phenomenology projects, successful completion of a Modern Physics course (or equivalent background in quantum mechanics and special relativity) is required.

For students working on scientific software development, a strong background in Python programming, substantial coding experience, familiarity with software development practices, and strong mathematical intuition are required. No prior background in physics is required for this research direction.

Preferred Courses/Experiences

Preferred preparation depends on the specific research direction to which the student is matched.

Experimental Particle Physics

• Coursework in particle physics, nuclear physics, or quantum mechanics

• Experience with C++ or Python programming for scientific computing

• Familiarity with statistics, data analysis, or machine learning

• Interest in experimental particle physics and large-scale scientific collaborations

Phenomenology

• Strong mathematical preparation beyond introductory calculus

• Coursework in quantum mechanics, particle physics, or related theoretical physics

• Experience with scientific programming and computational modeling

• Interest in theoretical particle physics and open-ended research problems

Scientific Software Development

• Advanced Python programming skills

• Experience developing larger software projects

• Familiarity with collaborative software development and version control (Git)

• Familiarity with numerical methods, optimization algorithms, or scientific computing

• Coursework in computer science, software engineering, mathematics, or a related field

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Probing the Surroundings of a Supermassive Black Hole

Lizvette Villafaña (she/her/ella)

Physics

lvillafa@calpoly.edu

Research Project Description

Supermassive black holes and their host galaxies seem to grow together. To explore this connection, we study the region of fast-moving, glowing gas that orbits close to the black hole. Although black holes themselves emit no light, the material surrounding them becomes extremely hot and bright as it falls inward. When that light varies in brightness, the nearby gas responds with a delayed "echo." From those echoes, we can determine how far the gas is from the black hole and use gravity to estimate the black hole's mass. However, we can't capture these environments in direct images, and the echoes alone don't reveal the structure or motion of the nearby orbiting gas.

In this project, the student will analyze one of these "echo" datasets using our group's forward modeling code. The code tests different possible arrangements and motions of the gas to find the model that best fits the data. By modeling this gas, the student will probe the surroundings of a supermassive black hole and help us better understand its environment and how it may connect to galaxy evolution.

BEACoN Scholar’s Role in the Project

During the Fall semester, the student will focus on developing familiarity with the literature, data structure, and modeling code using a pre-modeled dataset. In the Spring, the student will begin applying the code to the new data and preparing a poster presentation for the Bailey College of Science and Mathematics Student Research Conference and the BEACoN Research Symposium.

Weekly expectations are as follows:
One-on-one check-in with mentor (1 hour)
Meeting with group (1 hour)
Assigned readings (~2 hours, with short written summaries submitted)
Performing the research (eg. running codes, making plots) (5 hours, 6 for non-colloquium weeks)
Attending colloquium or OUDI events (1 hour every other week)

A successful experience will include clear written documentation of the workflow (for future students), the ability to run and interpret models independently, and a final poster that synthesizes results and visualizations from the project.

Skills the BEACoN Scholar will Gain

Through this project, the student will gain hands-on experience in computational astrophysics research, data analysis, and scientific communication. From a technical standpoint, the student will develop or improve their coding skills in Python and will be introduced to Bayesian inference, a powerful statistical method used for forward modeling across a wide range of fields, including finance, healthcare, sports analytics, and many more.

Beyond technical skills, the student will learn to document their workflow, interpret results, and communicate complex ideas to both technical and general audiences, skills that are highly valuable for graduate school and a wide range of  careers beyond astrophysics.
 

Required Courses/Experiences

• Some prior experience using a programming language (e.g., Python, MATLAB, or R; enough to navigate code, edit parameters, and run scripts).

• Self-motivated and able to work independently between meetings.

Preferred Courses/Experiences

• Familiarity with Python and/or working in a Linux or Unix environment.

• Coursework or strong interest in astronomy or astrophysics.

• Enthusiasm for learning new tools and contributing to a collaborative research group.

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Mathematical Modeling of Learning with AI Assistance and Digital Distraction

Tony Wong (he/him/his)

Mathematics Department

tonywong@calpoly.edu

Research Project Description

When stepping into a library, you will find many students studying with their laptops and phones on, likely chatting with AI tools. This naturally raises the question: do chatbots help us learn better? To master a concept, our minds search for that "clicking" moment when everything finally makes sense. With time, we usually move forward to a fuller understanding, though we may occasionally become confused, forget what we learned, hence take a step backward in our learning progress. Learning is a process with an uncertain timeline. We often do not know how long it will take to reach mastery. While chatbots can demystify our questions in seconds, they may also interrupt our focus, tempt us to read answers without fully digesting them or thinking critically, and even lead us to wrong ideas through hallucinations or imprecise explanations. Can we use mathematics to understand how learning is facilitated, or obstructed, by the use of AI?

In this project, we will build a stochastic model of the learning process under the influence of AI use. The model will incorporate some competing effects: faster access to information through AI assistance, distraction, and the possibility of faster forgetting or misconceptions as a downside of relying on AI. Using this model, we will analyze the probability distribution of the time it takes to master a concept under different levels of AI use. Extracting the key statistics from our model, such as the averge mastery time, we aim to better understand learning in a technology-rich environment.

BEACoN Scholar’s Role in the Project

• Build and test mathematical models

• Literature studies in stochastic analysis and cognitive science.

• Computational study, e.g. stochastic simulations.

• Mathematical analysis; establish a first-passage time theory for learning to mastery

• Meeting on a regular basis. We will discuss findings, such as what's working/not working. I will guide the mentee to articulate their ideas, analyze and interpret their results.

Skills the BEACoN Scholar will Gain

• Mathematical modeling: making reasonable assumptions, model building and revision, analysis and interpretation of results, critical thinking by evaluating the strengths and limitations of different modelling choices.

• Scientific computing, such as implementing stochastic algorithms, running numerical experiments, visualization of results and extracting meaningful statistics.

• Integration of available dataset to calibrate the model parameters.

• Communication and presentation skills, both in oral and writing.

Overall, this project will provide a unique experience for the scholar, who will apply stochastic modeling, analysis and scientific computing to a timely problem: how AI tools may influence learning. This project is particular suitable for BEACoN because the mathematical pre-requisite is relatively mild, while the research question is interdisciplinary and relevant to equity in learning.

Required Courses/Experiences

Linear algebra (MATH 206/1151)
Basic programming skills

Preferred Courses/Experiences

Basic probability (STAT 305/2610)
Statistical computing (STAT 331/1810)

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Advancing Audio Material Accessibility for Postsecondary Students With ADHD, Dyslexia, and Dysgraphia

Benjamin Alexander (he/him)

Management, Human Resources, and Information Systems

balexa02@calpoly.edu

Research Project Description

This project evaluates an audio learning system that uses generative AI to make voice the primary channel for engaging with recorded content and integrates playback with a knowledge system. The central research question is whether voice-mediated, AI-supported interaction reduces extraneous cognitive load and supports comprehension relative to conventional workflows, and whether those effects are more pronounced for students with ADHD, dyslexia, and dysgraphia.

Postsecondary instructors increasingly assign audio, including podcasts, recorded lectures, and expert interviews, alongside or in place of text. The platforms hosting that audio, however, were built for entertainment rather than learning. Bookmarking a passage, summarizing, querying an unfamiliar term, or taking a note each require the listener to leave the audio modality, sometimes the platform entirely, perform a visual-tactile task in a separate application, and then return to listening. Task switching imposes measurable costs in time and accuracy, and each disruption means effort spent managing the interface rather than understanding the material. These costs fall unevenly. For individuals with ADHD, the multi-step sequence collides with the executive functions of task initiation, attention regulation, and working memory. Further, it reintroduces the written modality that many dyslexic students chose audio to avoid. Finally, it surfaces the impaired written production that defines dysgraphia during what should be a learning task.

The research will generate empirical evidence on whether AI-mediated, voice-first interaction lowers barriers to learning from audio, along with the integration of learning environment in the same platform. Findings will be presented at the BEACoN Research Symposium, prepared for scholarly publication, and used to inform further development and grant applications. This research treats accessibility as a primary design commitment rather than an accommodation added after the fact, and it centers the experiences of students whose needs educational technology has long underserved.

BEACoN Scholar’s Role in the Project

• Support the IRB process, which may cover multiple phases of research, by helping assemble and organize protocol documents, consent forms, and recruitment materials, and by learning how human-subjects review works.

• Assist with participant recruitment and scheduling.

• Run participant sessions: welcoming participants, administering consent, guiding them through the tasks with both the prototype and the comparison condition, and collecting responses.

• Help maintain the resulting data and support data analysis.

• Contribute to the development of a conference presentation or publication based on this research.

• Assist in the identification and development of additional internal and external grant opportunities

• The student is not expected to develop the software. They will, however, get a close view of how an accessibility-focused technology is designed and tested, which is part of what makes the role a rich learning experience.

Skills the BEACoN Scholar will Gain

The Scholar will build a foundation in empirical social-science research methods:

• Human-subjects research and IRB process: how a study is designed to protect participants, what informed consent requires, and how a protocol moves through institutional review. Many undergraduates never see this until graduate school.

• Mixed-methods research: understanding how focus group and experimental data can be leveraged together in research.

• Experimental design: understanding a between-subjects comparison (prototype vs. standard player plus note-taking), what it means to control conditions, and why the study is built the way it is.

• Measurement: hands-on use of validated instruments and measure development (reliability, etc.)

• Data collection and management: running standardized sessions, keeping clean and well-documented data, and handling participant data responsibly and confidentially.

• Data analysis: organizing data for analysis and interpreting descriptive and comparative results, with room to grow into basic statistical analysis depending on the student's background.

• Domain knowledge: a working understanding of accessibility, Universal Design for Learning, and the cognitive science of learning with ADHD, dyslexia, and dysgraphia, plus exposure to how a university research project navigates technology transfer and intellectual property.

Required Courses/Experiences

• At least one completed research methods course, or equivalent hands-on research experience, in a social-science field (e.g., psychology, sociology).

• A social-science orientation and genuine interest in how people learn and how technology is evaluated.

• Comfort interacting with human participants in a professional, respectful, confidential manner.

• Reliability, organization, and attention to detail, since the work involves standardized procedures and careful record-keeping.

Preferred Courses/Experiences

• A completed statistics or data-analysis course.

• Coursework in experimental design, cognitive psychology, learning sciences, or educational psychology.

• Interest in or understanding of accessibility, disability, and inclusive design.

• Familiarity with survey or data tools, though these can be learned on the project.

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C-AI-R: Helping Students Build Career Agency, AI Fluency, and Responsible Reliance

Ashish Hingle (he/him)

Management, Human Resources, and Information Systems

ahingle@calpoly.edu

Yongcheng Zhan (he/him)

Management, Human Resources, and Information Systems

yozhan@calpoly.edu

Research Project Description

Generative AI is changing much of the college experience, including how students prepare for internships, jobs, and early-career work. Students are increasingly using generative AI to explore career possibilities and develop materials for internship and job applications. However, as with other uses of generative AI, students need structured guidance to understand how AI can support their career preparation and readiness without replacing their own judgment, reflection, or authentic representation of their skills. This project will design and pilot C-AI-R: Career Agency, AI Fluency, and Responsible Reliance, a guided career readiness workshop that supports students use of AI to reflect on career goals, improve career materials, identify skill gaps, and make responsible decisions about AI-generated recommendations. Rather than replacing career services, faculty advising, college-level professional development programs, or other institutional resources, C-AI-R is designed to supplement those resources by giving students an additional guided space to explore job search recommendations with responsible AI guardrails, all while providing a space for students to build their AI literacy.

In the workshop, participants will use their own generative AI accounts (ChatGPT Edu, Claude, etc), and follow guided activities developed by the research team. Possible activities include comparing a resume or experience description to a target job posting, asking AI for feedback, evaluating whether the feedback is accurate and ethical, revising career materials, and creating a short term-action plan. Additionally, the workshop will explore alternative career materials, such as web and brand portfolios and developing a GitHub repository which can serve to display proficiency and signal skills. The study will use a short pre/post survey, student reflections, and workshop feedback to examine how students experience the C-AI-R activity and how the workshop can better support career agency, AI fluency, and responsible reliance. To reduce privacy and data-security risks, the research team will not collect raw resumes, AI chat logs, private career documents, or AI account information. The goal is not to validate a new measurement instrument or conduct a large-scale impact study. Instead, the goal is to produce an initial pilot evaluation that helps clarify how students experience the C-AI-R activity with a focus on Cal Poly's Learn by Doing environment: what types of guidance they find useful, where they need additional support, and how the activity can better supplement existing career services, faculty advising, and college-level professional development programs.

BEACoN Scholar’s Role in the Project

The 2 BEACoN Research Scholars will be integral members of the research team and will be heavily involved in all aspects of the project. Specifically, they will contribute to both the design and evaluation of the C-AI-R workshop model, and analysis of the workshop outcomes. The scholars will help refine the C-AI-R model, review related research on AI-enabled career readiness, responsible AI use, student equity, and career development, and assist with developing student-facing workshop materials.

The scholars may help develop and revise survey items, reflection prompts, workshop instructions, responsible AI checklists, and sample activities. They will test the workshop materials using sample resumes and job postings, provide feedback on clarity and accessibility, and help ensure that the activities are useful for students from different backgrounds and with different levels of prior AI experience. They will also assist with pilot study planning and implementation, which may include recruitment support, workshop logistics, consent and data organization procedures, analysis of pre/post survey responses, and qualitative analysis of student reflection responses. Especially where dealing with qualitative processes, the scholars will be integral to ensuring the inter-rater reliability of any analysis in this project.

Both scholars will work collaboratively across all major phases of the project. Together, they will contribute to the literature review, survey and reflection design, workshop preparation, participant support, and analysis of student responses. Both scholars will participate in project meetings, help interpret pilot findings, and contribute to the final BEACoN Research Symposium poster.

Skills the BEACoN Scholar will Gain

The BEACoN Research Scholars will gain experience with design science research, human-centered evaluation, survey development, responsible AI use, and student-centered career readiness research. The scholars will learn how to connect theory, measurement, and workshop design by helping operationalize the C-AI-R model and evaluate how students use an AI-enabled career preparation system. The scholars will also be part of project management decisions, and will need to manage many aspects of the research pipeline which can need to be ordered and organized to meet deadlines.

The scholars will develop skills in literature review, survey item development, qualitative analysis, basic quantitative analysis, data visualization, user testing, and research communication. They will also gain practical experience with responsible AI workflows for resume development, job skill analysis, portfolio building, GitHub-based evidence of skills, and reflective career planning.

Because the project focuses on AI-enabled career preparation, the scholars will strengthen their own career readiness while contributing to a research project designed to support other students. By the end of the project, the scholars will have experience translating a student-centered problem into a research intervention, analyzing pilot data, and communicating findings through a research poster or presentation.

Required Courses/Experiences

Students should have an interest in student career readiness, responsible AI use, technology design, education, equity, or access to opportunity. Students should feel comfortable using spreadsheets. Scholars should be willing to take ownership of project responsibilities, learn new tools, communicate regularly, engage thoughtfully with student data, and contribute to both design and research tasks. No specific prior research experience is required.

Preferred Courses/Experiences

Experience with any of the following would be helpful but is not required: human-computer interaction (courses or research on how people interact with technology), information systems, implementing workshops in education contexts, data analysis and statistics, AI tools, career development, and resume or portfolio development. Familiarity with tools such as survey platforms, and dashboards would be useful.

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The Global AI Opportunity Gap: Access, Equity, and Environmental Cost Across Higher Education Systems

Alexa Loken (she/her)

Industrial Technology, Packaging and Entrepreneurship (OCOB); Management, Human Resources, and Information Systems (OCOB); and Communications (CLA)

aloken@calpoly.edu

Research Project Description

As AI tools become as foundational as the internet, a critical question emerges around who actually gets to benefit, and who pays the price. This research project investigates the growing gap between universities and countries that are meaningfully preparing students to engage with AI and those that are not. Using publicly available data- university course catalogs, national education policy documents, international reports, and sustainability assessments- the student researcher will compare how institutions in the United States, Singapore, Thailand, and Kenya are building AI literacy across their student populations, with reference to emerging EU regulatory frameworks. These four countries represent a deliberate spectrum: from a national mandate requiring all students to develop AI skills (Singapore), to a teaching-focused university system navigating institutional variation without a national standard (U.S.), to emerging economies with strong aspirations but significant infrastructure and access barriers (Thailand, Kenya). The project asks: which students and institutions are gaining genuine AI readiness, and which are being left behind? And critically, how does that answer change for students at under-resourced institutions, in low-income communities, or in countries with limited digital infrastructure?

Woven into this access and equity analysis is an environmental lens. The AI systems that higher education increasingly depends on carry real costs: data centers powering AI now rival entire countries in energy consumption, and those infrastructure costs are disproportionately borne by communities, often in lower-resource contexts, that gain the least AI benefit. The student researcher will examine this "who benefits, who pays" dynamic across the four countries studied, connecting global equity patterns to what it means for Cal Poly students navigating AI in their own education and careers. Outputs include an institutional AI Access Heat Map, a four-country equity and environmental cost spectrum visualization, and a student-facing guide to assessing AI readiness, materials directly applicable to Cal Poly's curriculum, career preparation programming, and BUS 270: AI Literacy for Business.

BEACoN Scholar's role in the Project

The BEACoN Research Scholar will serve as co-investigator across two semesters of structured, phased research. In Fall semester (5 weeks, November- December), the student will: conduct a systematic literature review of AI literacy frameworks from UNESCO, Stanford HAI, and WCET; build a scoring rubric across five institutional dimensions (AI courses offered, institutional policy, equity/access initiatives, faculty support, and career readiness integration); begin primary data collection on U.S. institutions using public course catalogs and policy documents; and draft an annotated bibliography and project methodology document.

In Spring semester (15 weeks, end of January- May), the student will: expand the institutional analysis to Singapore, Thailand, and Kenya; compile and synthesize environmental cost data from IEA, UN University, MIT, and Brookings reports; build two core visual deliverables (an AI Access Heat Map across institutions/countries and a spectrum visualization mapping AI access against environmental cost by country); draft the AI Equity and Impact Framework policy brief; and present findings at the BEACoN Research Symposium on May 19th. The exact scope and country emphasis may be refined collaboratively with the student based on their background, interests, and emerging findings.

The student will also have 1–2 structured conversations with Cal Poly faculty or professionals in environmental studies or sustainability to deepen the environmental cost dimension, as needed. This faculty mentor has a direct professional stake in the Southeast Asia context, including an upcoming teaching appointment in Thailand through Cal Poly's Global Programs in summer 2027, which brings personal motivation and regional attentiveness to the project's analysis of Thai higher education.

Skills the BEACoN Scholar will Gain

Systematic literature review: Identifying, evaluating, and synthesizing peer-reviewed research, institutional reports, and international policy documents- a foundational research competency across disciplines

Comparative document analysis: Building and applying a structured coding rubric to institutional artifacts (course catalogs, policy pages, syllabi) across four national contexts- a core qualitative research method in education, social science, and policy research

Secondary data compilation and analysis: Locating, assessing, and organizing publicly available quantitative data (energy consumption statistics, AI readiness indices, national education reports) into structured datasets

Cross-cultural and international research literacy: Navigating sources across four national contexts and understanding how policy environment, infrastructure, and culture shape educational outcomes — a globally relevant professional competency

Data visualization and science communication: Translating complex findings into two portfolio-ready visual formats (institutional heat map; access-vs.-cost spectrum graphic) using tools such as Canva, Flourish, or Google Sheets

Policy and research writing: Drafting an executive summary, contributing to a student-facing guide, and preparing a research poster and symposium presentation- all transferable professional writing skills

Research design literacy: Understanding why this project is built around publicly available secondary data, what ethical considerations apply to international comparative research, and how to scope a research question for a defined timeline- foundational skills for graduate school or applied research careers.

Required Courses/Experience

No specific courses required. Student should demonstrate: genuine curiosity about technology/AI, equity, sustainability, and/or global issues; reading and synthesizing written sources in English; and basic proficiency with digital tools like Google Suite

Preferred Courses/Experience

Coursework in communications, business, environmental studies, international studies, political science, sociology, or a related field preferred. As is:
-Interest in AI, future-of-work, sustainability, or education policy
-Experience with research or academic writing at any level
-Students who have studied, lived, or worked internationally (particularly in Southeast Asia or East Africa) are strongly encouraged to apply; cross-cultural lived experience meaningfully enriches this research
-Students from backgrounds underrepresented in technology and research fields are especially welcome; this project is explicitly designed to connect equity research to the researcher's own lived context

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AI-Enabled Human–Robot Collaboration through Brain–Computer Interfaces

Javier Gonzalez-Sanchez (he/him)

Computer Science and Software Engineering (CENG)

javiergs@calpoly.edu

Rafael Guerra Silva (he/him)
Industrial Technology & Packaging (OCOB)

rguerras@calpoly.edu

Research Project Description

Brain–computer interfaces (BCIs) and artificial intelligence (AI) are opening new possibilities for how humans and robots can work together. This project provides students with opportunities to collect electroencephalography (EEG) data (brainwave measurements) and explore its application to human–robot collaboration. Students will work with diverse commercial BCI devices to investigate how brain activity reflects user intent, attention, and cognitive workload, and how these signals can support more adaptive interactions between humans and robots in industrial and assistive settings.

Through this project, students will contribute to research in human-centered robotics while gaining exposure to signal processing, AI, software engineering, and interdisciplinary collaboration. They will participate in the development of experimental prototypes, analysis of EEG data, and dissemination of results, while gaining perspectives from neuroscience, human–computer interaction, engineering, and business. The experience also emphasizes project planning, documentation, teamwork, and reflection on potential career pathways in research, industry, and technology innovation.

As participants in this project, students will:

• Gain hands-on experience with commercial brain–computer interface devices and EEG data acquisition.

• Develop software components and AI models that support adaptive human–robot collaboration.

• Produce technical documentation and curated datasets for future stages of the research.

• Design and evaluate prototypes involving robotic systems and intelligent decision-making.

• Create a poster and video demonstration to showcase their results, with the potential to contribute to a conference presentation or paper.

• Build practical skills in signal processing, machine learning/time-series analysis, software engineering, and human-centered system design.

• Collaborate in a multidisciplinary team and gain exposure to engineering and business perspectives on emerging technologies.

BEACoN Scholar’s Role in the Project

Students will be contributing to both the technical and experimental parts of the project. The student will help set up and use commercial brain–computer interface (BCI) devices, collect electroencephalography (EEG) data from study activities, and maintain organized records of device settings, participant tasks, and data collection procedures.

The student will also assist with preparing and running experimental sessions related to human–robot collaboration. This may include testing BCI devices, checking signal quality, organizing EEG files, documenting procedures, and helping identify patterns related to user intent, attention, and cognitive workload. As the project progresses, the student will contribute to software components that support data collection, analysis, or prototype evaluation.

In addition, the student will participate in regular research meetings, share progress updates, maintain technical documentation, and help prepare project outcomes (including poster and video demonstration). The goal is for the student to have a clear, hands-on role in moving the project forward while also contributing to research communication and dissemination.

Skills the BEACoN Scholar will Gain

Students will gain experience with methods commonly used in neurotechnology and AI research. This includes EEG data acquisition using commercial brain–computer interface devices, data organization and management, and the application of machine learning techniques to identify patterns related to user intent, attention, and cognitive workload.

Students will also gain an appreciation for big data challenges, as EEG systems can generate hundreds of signals per second from multiple sensors simultaneously, requiring efficient software solutions for real-time processing and decision-making. The project will introduce students to time-series analysis and robotic systems.

In addition, students will develop software engineering skills relevant to data-intensive applications, including multithreading, distributed systems, prototype development, and data visualization. They will learn how to document and communicate research findings and system development.

The aim is for these experiences to provide insight into the intersection of AI, robotics, neurotechnology, and human-centered computing.

Required Courses/Experiences

Recommended preparation includes courses in (1) programming (Java, Python, or C/C++), (2) data structures.

Preferred Courses/Experiences

It is a plus: (1) software engineering (familiarity with agile software development methods) and (2) computer networking (protocols, ports, etc.) 

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