Large lecture halls packed with hundreds of students are common at research universities, especially for undergraduates. Instructors seek opportunities to interact with these learners, yet often students in these courses rarely receive feedback beyond exam scores. In response, Jocelyn Nardo, an assistant professor of chemistry and biochemistry at the Ohio State University, has investigated practical approaches for offering students individualized feedback to guide their learning.
She presented on how instructor-created tools might provide academic support to students in high-enrollment lectures during her talk, “Leveraging Python-Generated Learning Analytics to Support General Chemistry Student Success.” This was the latest installment of the Teaching and Learning Center’s (TLC) Educational Innovation and Scholarly Teaching Seminar, a speakers series where experts share research-driven insights with the UCLA instructional community. The series is sponsored by the Vice Provost for Teaching and Learning and hosted by the TLC.
Nardo highlighted how a scalable feedback platform offered individualized learning reports to students in a high-enrollment general chemistry course. Learning Catalytics sections provided students with low-stakes opportunities to practice problem-solving skills before large summative assessments. Nardo then used a Python script to amass raw data from these exercises into individualized Learning Catalytics reports that detailed students’ goals and offered study tips for upcoming assessments. With more personalized feedback, students could then understand their own mastery of the course material and inform their future study habits.
Seminar attendees appreciated the detailed illustration of how to offer students individualized insights in a large lecture format.
“Dr. Nardo’s research is grounded in practical experiences of instructors teaching large STEM courses, which makes her research extremely valuable,” noted K. Supriya, Senior Associate Director of the UCLA Center for Educational Innovation and Learning in the Sciences (CEILS). “She shared a practical way to scale personalized formative feedback for students that can be applied to any large-enrollment class that has quizzes, problem sets, or practice exams.”
Nardo’s Learning Catalytics reports are informed by the pedagogical concepts of deliberate practice and responsive teaching. Deliberate practice emphasizes that meaningful learning occurs when students repeatedly engage in low-stakes practice paired with actionable feedback. Meanwhile, responsive teaching entails an instructor using collected evidence of their students’ experiences of learning and actively adjusting a course to better support their success. Both concepts grounded the Learning Catalytics reports by having students regularly engage in a productive struggle with material adapted to fit their needs.
“Together, these approaches shift feedback from something retrospective and grade focused to something ongoing and coaching oriented,” Nardo emphasized.
She highlighted the results of providing students with these reports in the large chemistry lecture. Initial analyses showed that students who opened the reports more frequently had higher scores on practice exams, while students reported a sense of feeling less overwhelmed while studying for exams and a stronger connection to the course’s teaching team.
For attendees, Nardo’s research provides an actionable framework to offer students feedback in their courses at UCLA.
“I hope to be able to implement a similar system in my own teaching, along with exam wrappers to promote student reflection on their learning,” shared Supriya.
Nardo hopes that the talk showed instructors how they might provide individualized feedback in large courses in a way that is both personalized for students and also possible for instructors with limited technical experience.
“Large classes do not have to feel impersonal: even small, consistent signals about progress can meaningfully influence how students practice, persist, and see themselves as capable learners,” she shared. “My goal was also to show that this work is accessible. With exported LMS data, simple scripts, and incremental automation, instructors can build sustainable systems without needing specialized software.”