Skip to main content
Dryad logo

Evaluating Promising Practices in Undergraduate STEM Lecture Courses


Warschauer, Mark et al. (2021), Evaluating Promising Practices in Undergraduate STEM Lecture Courses, Dryad, Dataset,


Observations were collected to examine instructional practices in large undergraduate lecture courses at UCI, particularly in STEM (science, technology, engineering, and mathematics). The study began in 2012 with the intention of documenting the relative presence or absence of practices that potentially promote more active and engaged learning (e.g., enhanced faculty-student interaction, enhanced peer interaction, greater attention to problem-solving strategies, more opportunities for personalized learning, opportunities to receive and communicate information across diverse channels and modalities, more data-based instruction). 


Researchers observed introductory STEM courses at UCI to document instructional practice. For each observation, research assistants videotaped lectures and collected data on instructional strategies using a researcher-developed observation protocol known as Simple Protocol for Observing Undergraduate Teaching (SPROUT). Observations included detailed field notes during the lecture that were subsequently transferred to the observation protocol and contained both dichotomous indicators and qualitative evidence. Two researchers overlapped on 20 percent of the course sessions with inter-rater reliability of Cohen's kappa = 0.80. Coding disagreements and ambiguities were discussed among the research team as they occurred during the data collection process. 

Student administrative data was collected from the Office of Institutional Research (OIR). In addition to demographic and academic data, OIR provided course enrollments and grades (both in observed courses and in courses that students took in subsequent terms), allowing tracking of student progress toward STEM degrees. Students can enroll in more than one of the observed courses.

Usage Notes

Papers linked may not use the full dataset.


National Science Foundation, Award: 1256500