Are Faculty Changing? How Reform Frameworks, Sampling Intensities, and Instrument Measures Impact Inferences about Student-Centered Teaching Practices

Although recent studies have used the Classroom Observation Protocol for Undergraduate STEM (COPUS) to make claims about faculty reform, important questions remain: How should COPUS measures be situated within existing reform frameworks? Is there a universal sampling intensity that allows for valid inferences about the frequency of student-centered instruction within a semester or across semesters of a course? These questions were addressed using longitudinal COPUS observations (128 classes, three faculty, 4 years). COPUS behaviors were used to categorize classes into didactic, interactive lecture, or student-centered instructional styles. Sampling intensities (one to 11 classes) were simulated (1000 times) within a course and across semesters. The sampling intensities required for generating valid inferences about 1) the presence of student-centered instruction and 2) the proportion of instructional styles in a course and through time were calculated. Results indicated that the sampling intensity needed to characterize courses and instructors varied and was much higher than previously recommended for instructors with: 1) rare instances of student-centered classes, 2) variability in instructional style, and 3) longitudinal changes in instructional patterns. These conditions are common in early reform contexts. This study highlights the risks of broad, decontextualized sampling protocol recommendations and illustrates how reform frameworks, sampling intensities, and COPUS measures interact to impact inferences about faculty change.

Automated summary

Recent studies using COPUS for faculty reform raised questions on how to situate COPUS measures within existing frameworks and whether there is a universal sampling intensity for valid inferences. Longitudinal observations and simulations showed that sampling intensities needed for valid inferences varied depending on the context, highlighting the risks of broad, decontextualized sampling recommendations.