
Mentor(s): Marisa Brandt
Description: Since 2016, the collaborative model of LB 133, the Science + Society first-year course design that I have taught with several other instructors has included a project called Scientific Sites. In this project, teams of students collaboratively study a laboratory or research group on campus in order to address the question, "How does this scientific site produce knowledge?"
I would like to work with my Fellow to design and conduct a survey of past students—with perhaps an opportunity for follow-up focus groups—to assess the long-term impacts of this assignment on their interest, comfort, and overall success in participating in research as undergraduates, and potentially even graduate students. I am curious how the project may have impacted whether students' sought out research experiences during their time in MSU, their sense of preparedness for research if they did so, and their overall sense of empowerment in finding a research environment in which they could learn, grow, and thrive.
Skills the mentor(s) anticipate the Fellow might need: I would like to work with a Fellow who has experience with, or at least a strong interest in developing skills in survey and potentially focus group work to develop this project. This is essential. Some familiarity with experiential learning and/or having students study professionals in their fields as part of learning would also be handy.
Preferred start date: Mid May 2026 or Mid August 2026

Mentor(s): J.P. Lawrence
Description: Biology, as a whole, is a broad and complex topic, which manifests itself as multiple classes as the university level. Undergraduate students, early in their academic careers, tend to take introductory biology classes which are often subdivided into "macro" subjects like ecology and evolution and "micro" subjects like genetics and cell biology. Because these are different classes, students often compartmentalize the material in each which necessitates "relearning" concepts when they go from Introductory Biology 1 to Introductory Biology 2.
As biology, and in particular the topics covered in these introductory courses, is interconnected, it is important for students to see and understand, for example, how ecological success can be traced back to the alleles that make certain phenotypes more or less successful in their environment. Getting students to understand how these different concepts are related can be a challenge. The purpose of this project is to design a two-part lab that is meant to connect these macro and micro subjects together so that students can better understand the connection between them. In short, students will investigate how predators select prey (using clay models), which will be done during their first semester (Introductory Biology 1) and then work on identifying those predators using molecular techniques (e.g., eDNA detection) for their second semester (Introductory Biology 2). The project will develop the pilot course with upper level undergraduate students (~24) for eventual implementation for introductory biology classes.
Skills the mentor(s) anticipate the Fellow might need: I would be interested in working with a fellow who has a strong interest in curriculum design and a familiarity with ecology, evolution, and molecular techniques. This project will involve development of resources (e.g., procurement of peer reviewed papers) and assignments to help guide students through these ecological, evolutionary, and molecular topics. I anticipate this ultimately being published, so I would like a fellow interested in taking lead in publication of our findings.
Preferred start date: Mid August 2026

Mentor(s): Michele Jackson
Description: Higher education is of two minds when it comes to generative AI. One the one hand, AI demonstrates astounding capabilities that offer tremendous potential for research and scholarship. On the other hand, these capabilities confront some fundamental assumptions and precepts about how we teach and how students learn. The most common instructional response to this point has been to try to contain or control student use of the technology. This project takes a different tack and accepts generative AI as a part of today's instructional environment. Instead of focusing on containing AI to preserve traditional methods of teaching and learning, we will identify practices for learning in this new era and how instructional strategies can support those new practices. Even more challenging is that AI capabilities and application development continues to emerge. This makes it an interesting and engaging area for research.
This project is part of a larger ongoing research program that explores the uses and impacts of generative AI on teaching and learning in higher education. This project explores how to help undergraduate students (1) engage in deeper content learning, (2) strengthen their capabilities for self-regulated learning, and (3) identify and support their personal learning goals. In Fall 2026, we will implement, assess, and refine strategies that emerged during the course in Fall 2025. In Spring, we will analyze results using multiple analytic research methods (e.g., content analysis, interviews, observation). We will also create guidebooks for instructors and/or students and disseminate as open educational resources.
Skills the mentor(s) anticipate the Fellow might need: This opportunity does not require specific disciplinary knowledge or advanced technical expertise, but the fellow should (1) have experience collecting and/or analyzing empirical data using social scientific methods, (2) have basic understanding of generative AI terminology (e.g., LLMs, prompting, tokens) and applications (e.g. chatGPT, Copilot, Claude), (3) be comfortable communicating and contributing in group contexts, and (4) enjoy thinking imaginatively and from new perspectives. Must be available classes at least once per week during the Fall 2026 term (Mondays and/or Wednesdays, from 3:00-7:00 p.m.)
Preferred start date: Mid August 2026

Mentor(s): Ariel Steele
Description: Group work is an increasingly common practice in introductory STEM courses and evidence suggests group work can improve student learning and academic performance. While group work has many benefits, such as improved learning and development of leadership, critical thinking, and teamwork skills, students also report barriers and negative experiences with group work, including unequal work distribution, interpersonal conflicts, and increased anxiety.
There is also evidence to suggest group work may impact the experiences of certain groups of students differently from their peers. The number of students who identify as neurodivergent has been increasing, however, there is limited research on the experiences of neurodivergent students in STEM. This project seeks to contribute to a growing body of research on neurodivergent students’ experiences with group work in introductory biology courses, specifically focusing on the barriers students’ experience with group work and what strengths they bring to their groups when working in small teams.
Skills the mentor(s) anticipate the Fellow might need: Fellows with experience with qualitative research, specifically with designing interview protocols, conducting semi-structured interviews, and analyzing qualitative data would be preferred. Familiarity with (or interest in learning about) disability justice and/or critical disabilities studies is also preferred.
Preferred start date: Mid May 2026

Mentor(s): Carmen Ruiz-Sanchez
Description: This project examines student outreach as a high-impact retention practice by exploring how students respond after being identified as “students of concern” through mechanisms such as early warning reports, academic standing, low term GPAs, or faculty and advisor concern. The study focuses on whether and how advisor-initiated student contact leads to engagement behaviors associated with persistence, including responding to advisors, scheduling and attending appointments, using recommended resources, completing the semester, and remaining enrolled. Using a two‑phase design, the project first evaluates the effectiveness of current outreach practices by analyzing response rates, time to response, engagement patterns, and short‑term persistence outcomes, and then builds on these findings to identify and, where possible, pilot targeted changes to outreach design, such as message framing, clarity, and sequencing, to assess whether small, intentional adjustments can meaningfully increase student engagement and retention‑relevant behaviors.
Skills the mentor(s) anticipate the Fellow might need: This project seeks a Fellow with strong interest in data‑informed research on student success and retention, and with skills that support both quantitative and qualitative inquiry. Because the project involves analyzing patterns of student engagement following student outreach, comfort working with institutional data, such as organizing datasets, conducting descriptive analyses, and interpreting trends is important. At the same time, study may require complementary qualitative approaches, such as coding and analyzing advising communications, open‑ended responses, or reflective notes to better understand how students experience outreach. Experience with quantitative tools (e.g., Excel, SPSS) and/or qualitative methods (e.g., thematic coding) is beneficial. Through this project, the Fellow will gain mentorship in analyzing institutional data and in understanding outreach as an applied student success practice, including the challenges, equity considerations, and communication choices that influence whether students engage with support
Preferred start date: Mid August 2026

Mentor(s): Krysta Foster, Shahnas Masani, Stephanie Calloway & Sarah Dickinson
Description: Helping students to prepare for their career journeys is a critical component of their college experience. For too long this work has occurred outside the classroom, putting the onus on students to navigate often unfamiliar territory as they seek out resources and guidance to help them reach their goals. Here at LBC our career team and faculty have collaborated to begin incorporating career education work into disciplinary learning, helping students to make meaning of their experiences in the classroom and connecting the skills they've gained to their future careers.
As part of an ongoing effort to assess this work and to prepare to develop a new curriculum, we aim to uncover common themes across multiple qualitative sources including graduating senior and alumni surveys as well as classroom focus group feedback. Using the data we collect to inform curriculum design, our team will work to evaluate current curriculum and develop new content as we seek to make career support accessible for all students here at LBC.
Skills the mentor(s) anticipate the Fellow might need: We seek a fellow who brings experience and/or an interest in qualitative data coding and instrument design, while prior experience is valued, we are also committed to training this fellow in these techniques as part of our commitment to hands-on learning experience. Most importantly, we hope to work with a SUTL fellow with a deep interest in improving accessibility for students, and someone who is excited to collaborate across disciplines to make this work possible. All disciplines are welcome to apply!
Preferred start date: Mid August 2026

Mentor(s): Dominique Green
Description: Lyman Briggs College is launching a student-led, peer-facilitated First-Year Seminar, which provides an engaging and supportive space for students to explore their transition to college life through the lens of the eight dimensions of well-being, self-discovery, community building, and sense of belonging. Rooted in collaboration and mentorship, this seminar is led by experienced upper-class peer mentors who guide discussions, foster meaningful connections, and encourage personal and academic growth.
Through interactive activities and reflective dialogue, students develop a deeper sense of purpose while building a supportive network within the close-knit, residential learning environment of Lyman Briggs College. We are looking for a Fellow who is eager to be part of the foundation of the full-scale launch of the First-Year Seminar at Lyman Briggs College that will have a positive effect on the college experience of 450+ incoming students. We will develop and conduct pre-, mid-semester, and post-assessments, as well as focus groups. These assessments will help us measure the seminar’s impact on student growth in areas such as time management, goal setting, resource navigation, and community building.
Skills the mentor(s) anticipate the Fellow might need: We are seeking a Fellow with a strong interest in but not limited to educational assessment, student success initiatives, and peer mentorship. Critical skills include data collection and analysis. Strong written and verbal communication skills are also essential for crafting surveys, summarizing findings, and presenting recommendations. Beneficial but not required skills include experience with survey tools (Qualtrics, Google Forms, etc.), basic statistical analysis, and familiarity with student development theories. While prior experience in assessment design is helpful, we are happy to provide mentorship in this process. Most importantly, we seek a Fellow who is collaborative, detail-oriented, and passionate about supporting first-year student success.
Preferred start date: Mid May 2026

Mentor(s): Clausell Mathis
Description: This ongoing project focuses on the development and implementation of formative assessments for undergraduate General Physics I and II courses designed specifically for life science majors. The study includes both treatment and control groups. The treatment group will engage with newly developed formative assessments that are intentionally designed to leverage students’ cultural resources, such as their lived experiences, community knowledge, linguistic practices, and disciplinary identities, as assets for demonstrating understanding of physics concepts. The control group will receive standard instructional practices and traditional assessments. Comparisons between the two groups will allow us to examine the impact of culturally grounded assessment practices on student learning outcomes.
The fellow will contribute to the design and refinement of these culturally responsive assessments, ensuring alignment with core disciplinary ideas and scientific practices. The fellow will also assist in organizing and analyzing student responses to examine evidence of disciplinary learning, engagement in scientific practices, and the quality of students’ causal explanations. In addition, the fellow will play an active role in preparing manuscripts for publication based on findings from the comparative data analysis between treatment and control groups.
Skills the mentor(s) anticipate the Fellow might need: The fellow should have skills in both quantitative and qualitative data analysis, a strong foundation in physics content knowledge, and a demonstrated interest in learning and professional growth.
Preferred start date: Mid May 2026

Mentor(s): Marisa Brandt
Description: Since 2016, the collaborative model of LB 133, the Science + Society first-year course design that I have taught with several other instructors has included a project called Scientific Sites. In this project, teams of students collaboratively study a laboratory or research group on campus in order to address the question, "How does this scientific site produce knowledge?" I would like to work with a Fellow to design and conduct a survey of past students—with perhaps an opportunity for follow-up focus groups—to assess the long-term impacts of this assignment on their interest, comfort, and overall success in participating in research as undergraduates, and potentially even graduate students. I am curious how the project may have impacted whether students' sought out research experiences during their time in MSU, their sense of preparedness for research if they did so, and their overall sense of empowerment in finding a research environment in which they could learn, grow, and thrive.
Skills the mentor(s) anticipate the Fellow might need: I would like to work with a Fellow who has experience with, or at least a strong interest in developing skills in survey and potentially focus group work to develop this project. Some familiarity with experiential learning and/or having students study professionals in their fields as part of learning would also be handy.
Preferred start date: Mid May 2025 or Mid August 2025

Mentor(s): Dominique Green
Description: Lyman Briggs College is piloting a student-led, peer-facilitated First-Year Seminar in Fall 2025. The seminar goal is to provide an engaging and supportive space for students to navigate their transition to and through the first year. Utilizing interactive activities through the lens of the eight dimensions of well-being, self-discovery, and community building. Guided by experienced peer mentors, students will develop essential skills such as time management, goal setting using SMART goals, and academic planning in collaboration with advisors. They will become experts on campus resources and build a strong foundation for their resume and cover letter through partnership with the LBC Career Team. Through engaging in discussions, self-reflection and collaborative learning, students will cultivate meaningful connections and gain practical tools for success. The seminar culminates in a group project where students share the most impactful resources and strategies that have supported their transition, reinforcing their learning and contributions to the Lyman Briggs community. To assess the seminar’s impact, evaluation efforts will focus on collecting and analyzing data on student experiences, learning outcomes, and overall program effectiveness. Surveys and other assessment tools will be developed to measure how well the seminar supports student success, with findings used to refine the program and guide its expansion from the 175-student pilot to over 600 students by Fall 2026.
Skills the mentor(s) anticipate the Fellow might need: We are seeking a Fellow with a strong interest in peer mentorship, student success initiatives, and educational assessment. Critical skills include data collection and analysis. Beneficial but not required skills include experience with survey tools (Qualtrics, Google Forms, etc.), basic statistical analysis, and familiarity with student development theories. While prior experience in assessment design is helpful, we are happy to provide mentorship in this process. Most importantly, we seek a Fellow who is collaborative, detail-oriented, and passionate about supporting first-year student success.
Preferred start date: Mid May 2025

Mentor(s): Rachel A Barnard & Shahnaz Masani
Description: Despite the many systemic barriers that exist, STEM faculty often fail to recognize structural inequities, instead perpetuating race-evasive narratives that inaccurately attribute disparities to individual student characteristics (Russo-Tait, 2022). Undergraduates also hold similar race-evasive beliefs, and those that do are less likely to identify or challenge racial microaggressions. Learning Assistants (LAs) are near-peer educators, bridging hierarchies between students and instructors. Yet, LAs often do not receive sustained training on equitable teaching, and little is known about how they understand or enact equity (Barron et al., 2021). Further, we have found that without explicit training, LAs can engage in the same harmful, dominant narratives that perpetuate racial inequities. For the last two years, we have run a cohort-program concurrent with ULA experience called ACCESS (Advancing ULA critical consciousness for equitable leadership and student success). The ACCESS fellowship introduces LAs to Critical frameworks, bridging theory and practice to develop their “racial noticing lens”. Through this, we have found shifts in LAs’ ability to recognize and challenge dominant racial narratives. However, noticing and challenging inequities, as with any learning is a socio-cultural process- this means that when the learning (the fellowship) is separated from the doing (the classroom and disciplinary teaching team) it poses a major barrier to enacting equity and justice. Thus, through this SUTL project, the graduate fellow will work with faculty and the ACCESS fellows to co-develop short modules and activities. Fellows will lead these activities at weekly teaching team meetings, thus bringing their learning from the fellowship into their disciplinary teaching spaces and shifting the culture of the team to develop their structural noticing lens. Further, the SUTL fellow will help design and implement an assessment plan to better to assess the impacts of this experience on the ACCESS fellows and the teaching teams, as well as to identify the affordances and challenges of bringing in Critical pedagogy into a STEM higher education space through a ground-up approach, where the undergraduate fellows are positioned experts that lead teams of faculty, graduate students, and other undergraduate LAs.
Skills the mentor(s) anticipate the Fellow might need: The fellow will need to come with an understanding of the socio-historical role of race in the United States, as well as the racial structures that continue to allocate resources differently on the basis of race. This could include knowledge of Racial and Race-Evasive discourses, Critical pedagogical frameworks etc. Additionally, knowledge of qualitative research methodologies including interview design, conducting and analyzing interviews etc. is desired
Preferred start date: Mid May 2025

Mentor(s): Andrea Kelley
Description: Lyman Briggs College is shaping the future of its Science and Society curriculum, and this project offers a unique opportunity to be part of that work. LB2XX: Concepts in Science and Society is an online, asynchronous, 2-credit pilot course introducing students to the arts, humanities, and social sciences in the context of Science and Society. Currently in its first pilot semester, the course will expand from 9 to 30 students in SS26. The Fellow will play a key role in evaluating student experiences through post-semester focus groups, refining and scaling the course, and analyzing data to inform future development. With access to the LBC Qualitative Research Lab and its resources the Fellow will gain hands-on experience in qualitative research, curriculum development, and educational assessment.
Skills the mentor(s) anticipate the Fellow might need: I am seeking a Fellow with previous experience in qualitative data collection and analysis. I would prefer some previous experience using NVivo software and/or facilitating focus groups. The Fellow should have interests in justice-centered pedagogy, alternative assessment techniques, and interdisciplinarity.
Preferred start date: Mid May 2025

Mentor(s): Krysta Foster & Shahnaz Masani
Description: In an effort to build on progress made in incorporating career exploration and skill development, LBC's EPICC (Exploration & Purpose Integrated Core Curriculum) graduate participants will help the LBC Career team to expand our reach for career education, educate and empower our undergraduate students, and provide meaningful learning and working experiences for graduate students. EPICC grads will help with the delivery and assessment of career education interventions in undergraduate courses at Lyman Briggs College, including LB144 and the new First Year Seminar course, as well as the development of other career curriculum in collaboration with LBC faculty (early ideas and interest include LB492 courses, Physics, etc.). We will continue to assess the impact of our work in both courses on self-efficacy, STEM career identity and belonging, and eventually hope to assess the long-term impacts of these interventions on student success (retention, persistence) and post-graduation outcomes.
Skills the mentor(s) anticipate the Fellow might need: Students working with the EPICC program should possess the ability to present material in a clear, concise, and energetic manner; we will provide training especially around the specific content topics. Furthermore, students should possess an interest in teaching and be committed to creating an equitable learning experience for all undergraduate students. Quantitative and qualitative data analysis and coding skills preferred but not required.
Preferred start date: Mid May 2025 or Mid August 2025

Mentor(s): Clausell Mathis
Description: This project focuses on developing, implementing, and assessing culturally responsive curricular materials in undergraduate physics courses at MSU. Recognizing that traditional physics instruction often excludes students' cultural backgrounds and lived experiences, this project seeks to design lessons and assessments that integrate students’ cultural resources as assets for learning. Using a design-based research approach, we will co-develop instructional materials with faculty and students, investigate how these materials influence student engagement and understanding, and refine them iteratively based on classroom data. The Fellow will assist in curriculum development, classroom observations, qualitative data collection (focus groups), and analyzing students’ responses to culturally situated physics tasks. This project will contribute to broader efforts in physics education reform by making physics more inclusive and relevant to diverse student populations.
Skills the mentor(s) anticipate the Fellow might need: Critical Skills (must have or be willing to develop quickly): interest in physics education and culturally responsive teaching, willingness to engage with qualitative research methods (thematic analysis), strong writing and communication skills for developing instructional materials. Beneficial Skills (helpful but not required): background in physics or physics education research, experience with curriculum design or instructional material development, familiarity with equity and inclusion frameworks in STEM education, basic coding skills for qualitative data analysis (e.g., NVivo, Dedoose)
Preferred start date: Mid May 2025

Mentor(s): Michele Jackson
Description: Higher education is of two minds when it comes to generative AI. One the one hand, genAI demonstrates astounding capabilities that offer tremendous potential for research and scholarship. On the other hand, these capabilities confront some fundamental assumptions and precepts about how we teach and how students learn. The most common instructional response to this point has been to try to contain or control student use of the technology. This project takes a different tack and accepts generative AI as a part of today's instructional environment. Instead of focusing on containing it to preserve traditional methods, we will focus on what practices students need to use in order to learn in this new era and how instructional strategies can support those new practices. The answers are not clear, and made more difficult by the rapid evolution of generative AI capabilities and by the "learning" nature of the machine learning itself. This makes it an interesting and engaging area for research. This project is part of a larger ongoing research program that is exploring the uses and impacts of generative AI on teaching and learning in higher education. We will focus specifically on exploring how to help undergraduate students (1) engage in deeper content learning, (2) strengthen their capabilities for self-regulated learning, and (3) identify and support their personal learning goals (selfish learning). Working collaboratively with undergraduate students and instructional design professionals, we will develop and iteratively refine a set of strategies during two sections of LB492 in the Fall term. We will pilot the strategies with student participants in the Spring and assess their efficacy using multiple analytic research methods (e.g., content analysis, interviews, observation). We will also create guidebooks for instructors and/or students and disseminate as open educational resources.
Skills the mentor(s) anticipate the Fellow might need: This opportunity does not require specific disciplinary knowledge or advanced technical expertise, but the fellow should (1) have experience collecting and/or analyzing empirical data using social scientific methods, (2) have basic understanding of generative AI terminology (e.g., LLMs, prompting, tokens) and applications (e.g. chatGPT, Copilot, Claude), (3) be comfortable communicating and contributing in group contexts, and (4) enjoy thinking imaginatively and from new perspectives. Must be available on most Mondays and/or Wednesdays during the Fall 2025 term, from 3:00-6:00 p.m., to collaborate with undergraduate student researchers.

Mentor(s): Kristen Vroom, Taylor McNeill & Chuck Fessler
Description: Traditional assessments in undergraduate mathematics courses, such as timed, high-stakes exams, can contribute to student anxiety, provide an incomplete picture of student understanding, and communicate inauthentic views of the mathematics discipline. Additionally, they perpetuate inequities, particularly for students from marginalized groups. In response, educators in Lyman Briggs mathematics courses are implementing alternative assessment strategies—such as standards-based grading, portfolios, and projects—to create more equitable and meaningful opportunities for students to showcase their learning. This project is a collaborative action research study in which we will investigate and refine these alternative assessment strategies through an iterative process of implementation, data collection, and reflection. By examining students’ experiences with these assessments, we aim to better understand their impact on perceived learning, engagement, and sense of belonging. The Fellow will be a key contributor to this process by assisting with qualitative data collection and analysis, including designing and conducting student interviews/focus groups. The insights gained from this work will inform ongoing efforts to reimagine more equitable assessment practices in undergraduate mathematics education.
Skills the mentor(s) anticipate the Fellow might need: We are seeking a graduate fellow with experience in or interests in learning about qualitative analysis, including designing student interview/focus group protocols, conducting interviews/focus groups, and analyzing data to identify key themes. Experience with calculus and pre-calculus content is preferred, but not required.
Preferred start date: Mid May 2025

Mentor(s): Kirtimaan Mohan
Description: Covariational reasoning (Carlson 2002) is the cognitive process of understanding how changes in one quantity relate to changes in another. It involves recognizing and interpreting the dynamic relationships between variables, such as how the speed of an object changes over time. This type of reasoning is crucial in building an understanding of physics, as it enables learners to better analyze and model real-world phenomena. Computational thinking (Weller 2021) in physics involves using problem-solving techniques that leverage computer science principles to understand and analyze physical phenomena. By applying computational thinking, students can create models and simulations that help in understanding physical phenomena such as motion. In this exploratory study, we aim to investigate the interconnectedness of covariational reasoning and computational thinking in a physics learning environment. Specifically, we will evaluate whether certain computational modeling activities used in an introductory physics for life science curriculum contribute to the development of covariational reasoning skills. We will collect both qualitative data (through interviews and observations) and quantitative data (through surveys and assessments) to evaluate the effectiveness of these activities and assignments. This study has the potential to inform instructional practices and enhance the integration of computational modeling in physics education.
References
Carlson, M., Jacobs, S., Coe, E., Larsen, S., & Hsu, E. (2002). Applying covariational reasoning while modeling dynamic events: A framework and a study. Journal for research in mathematics education, 33(5), 352-378.
Weller, D. P., Bott, T. E., Caballero, M. D., & Irving, P. W. (2021). Developing a learning goal framework for computational thinking in computationally integrated physics classrooms. arXiv preprint arXiv:2105.07981.
Sabo, H. C., Odden, T. O. B., & Caballero, M. D. (2023). How do we assess computation in physics?. arXiv preprint arXiv:2308.15983.
Skills the mentor(s) anticipate the Fellow might need: Interest in understanding how students think, reason and learn is essential. The following are some skills that are preferred, but not necessary. I will help the Fellow help learn skills that they are not familiar with including: basic understanding or familiarity with some of physics, especially with motion and forces, familiarity with computational modelling, familiarity with python programming language, experience designing and conducting interviews, surveying and summarizing relevant literature, experience with qualitative data collection and analysis.
Preferred start date: Mid May 2025 or Mid August 2025