Comparison of high-technology active learning and low-technology active learning classrooms
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
Many academic institutions are investing thousands of dollars in technology-based classrooms to market themselves as modern and adapt to the new generation of students for whom technology forms part of their everyday lives. This technology is also believed to provide the added benefit of better knowledge acquisition, improved critical thinking and greater engagement with the material. However, not many studies have examined their effectiveness in comparison with active learning classes that do not employ a lot of technology. An evaluation of a high-technology-based active learning classroom environment and a low-technology-based active learning classroom for the same organizational behaviour and leadership course is presented in this article. Results revealed no significant differences for grades between the two. However, several problems emerged with the high-technology active learning classroom. Examination of the instructors’ experiences suggests that a variety of obstacles need to be dealt with if this type of classroom is to be adequately utilized and assessed.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.004 |
| 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