Tell us about your course.
KIN 110 is a large-enrollment introductory kinesiology course (≈300 students) focused on human performance and nutrition. It uses a team-based learning model combining lecture and discussion sections to promote applied learning and accountability.
What specific practices do you use to promote peer learning and connection in your large classes?
KIN 110 is intentionally structured around team-based learning to make a large course feel smaller and more interactive. Students work in permanent teams throughout the semester, completing readiness assurance tests, application activities, and case-based problem solving together. I design in-class activities that require consensus decision-making rather than simple answer sharing, which encourages discussion and peer teaching. Teams analyze athlete scenarios, interpret nutrition data, or solve fueling problems that mirror real-world decision-making. I also use structured accountability systems — including peer evaluation and an Individual Accountability Factor — to reinforce consistent participation. Outside of formal activities, discussion sections led by undergraduate teaching assistants help create smaller learning communities where students can ask questions, review concepts, and build relationships. The goal is for students to learn physiology and nutrition through interaction, not just exposure to content.
How do you know when your practices are working?
I look for both quantitative and qualitative indicators. Academically, team performance on application exercises tends to exceed individual readiness scores, suggesting students are learning from one another in meaningful ways. Through the semester, students complete multiple peer evaluations. I observe gradual improvements in team dynamics through a multi characteristic quantitative scoring process. Attendance remains high for a large course, which I interpret as students perceiving value in showing up and participating. I also monitor peer evaluation feedback and mid-semester check-ins, where students frequently report that their teams help them stay accountable and understand difficult concepts. Informally, I notice shifts in classroom dynamics: discussions start more quickly, students challenge each other’s reasoning, and groups become increasingly confident explaining their decisions publicly.
What are you excited to try next in your teaching?
I’m interested in strengthening students’ metacognitive awareness of how they learn course concepts over time. Next, I plan to incorporate short reflection activities that ask students to revisit earlier misconceptions about nutrition or performance and articulate how their thinking evolved. I’m also exploring ways to better integrate AI tools as learning supports rather than shortcuts — helping students use them to test understanding, generate practice explanations, or analyze case studies. Finally, I’m excited to continue refining connections between lecture content and real-world performance settings so students can more clearly see how course concepts apply beyond the classroom.
