A New Tool for Measuring Student Behavioral Engagement in Large University Classes
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We developed a classroom observation protocol for quantitatively measuring student engagement in large university classes. The Behavioral Engagement Related to Instruction (BERI) protocol can be used to provide timely feedback to instructors as to how they can improve student engagement in their classrooms. We tested BERI on seven courses with different instructors and pedagogy. BERI achieved excellent interrater agreement (>95%) with a one-hour training session with new observers. It also showed consistent patterns of variation in engagement with instructor actions and classroom activity. Most notably, it showed that there was substantially higher engagement among the same group of students when interactive teaching methods were used compared with more traditional didactic methods. The same general variations in student engagement with instructional methods were present in all parts of the room and for different instructors.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.057 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it