Does it Matter Where You Teach? Insights from a Quasi-Experimental Study on Student Engagement in an Active Learning Classroom
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
Active learning has experienced a recent resurgence with the advent of specialized active learning classrooms. While the fundamental theory behind active learning is anything but new, a relatively recent finding is that active learning pedagogies thrive in suitable active learning classrooms. To date, studies of active learning have focused on outcomes such as student performance. The quasi-experimental study described in this article investigated self-ratings of student engagement as an outcome of active learning in active learning classrooms using a novel instrument that accounts for known factors of engagement in addition to the contribution of the learning environment—the classroom. We delineated the relative contributions of instructor, classmates, and classroom to self-rated student engagement through student surveys in both a traditional classroom and an active learning classroom in two highly similar courses with the same instructor. Our findings were that the configuration of the classroom had a direct influence on self-ratings of student engagement above and beyond instructor contributions. In this article, we describe these findings and how, with careful consideration of course design and a classroom that fits the instructor’s pedagogy, optimal levels of perceived student engagement can be achieved. This knowledge is important to future educational policy on construction and scheduling, as the resurgence of active learning in higher education increasingly reveals deficiencies in physical learning environments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.011 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.012 |
| Insufficient payload (model declined to judge) | 0.001 | 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