Educational practices in large college courses and their effects on student outcomes
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Part I of this study presents a large-scale characterization of normative educational practices (e.g., course structure, teaching methods, learning activities) across more than 1,000 high-enrollment undergraduate courses at a large public institution over the last 5 years. I assess the extent to which course features reflect educational best-practices by systematically reviewing course syllabi—documenting the type, quantity, and grade-weight of all work assigned in each course as well as the prevalence and variability of teaching practices such as group activities, retrieval practice, and in-class active learning. I assess the degree to which these variables have changed over time, how they differ across colleges, and whether they form distinct clusters. I also analyze language used in the syllabus to see how instructors communicate information to students. I examine pronouns, comparisons, negations, and words related to achievement versus affiliation; I isolate words that unique to certain syllabi, courses, departments, and colleges; and I look at how similar two syllabi from the same course are on average. Findings revealed that high stakes exams are the norm, active learning is relatively uncommon, and students get few opportunities for spaced retrieval practice. Importantly, it was found that no one college has a monopoly on educational best-practices; different colleges had different strengths. Trends over time were mostly positive, indicating an increase in adoption of many best-practices, with a few exceptions. Part II of this study builds directly upon Part I by combining the syllabus dataset with student records to assess how prerequisite-course features affect student performance in their subsequent courses. Specifically, introductory courses high and low in retrieval-practice requirements were compared using inverse propensity-score weighted regressions to improve causal inference. Results showed that additional retrieval practice improved students’ performance in their subsequent courses. However, the average treatment effect estimates were small and somewhat sensitive to variations in model. Finally, subsequent-course performance was regressed on the full set of educational relevant variables using lasso regression, identifying several variables related to retrieval practice and spacing (including number of quizzes and cumulative exams) as important correlates of student success.