The Possible Learning and Teaching Benefits of Short Mind-calming Exercises in Undergraduate Courses
Bibliographic record
Abstract
The potential benefits of meditation exercises to promote more focused student attention and engagement have only rarely been quantitatively investigated at the college/university level. Here, I report student perceptions on the impacts of regular short mind-calming exercises at the beginning of every class in second, third, and fourth-year biology undergraduate courses, using voluntary anonymous surveys that were completed by at least two-thirds of each class (total enrollments 326, 68, and 15 respectively). In the third year course, 93% of respondents indicated that the exercise was “enjoyable and relaxing”, 73% indicated that it was “a valuable use of lecture time because I feel it enhances deep learning”, 75% found it a useful perspective “to achieving balance/calm in my life”, and 76% rejected the suggestion that although “the exercises are useful, they are not course-related material and therefore are inappropriate within class time”. Responses to several other distinct survey statements were also strongly positive, and furthermore, very similar favourable results as above were obtained in the other two courses. Overall, although it is unclear whether these very short exercises actually enhanced learning, many students perceived that it did. Finally, my teaching performance in university-based student assessments of the third-year course was significantly elevated in the year with mind-calming exercises compared to each of the previous nine iterations in which I had been an instructor. Together, these quantitative results suggest that the regular use of such exercises has multiple direct and indirect benefits that may contribute to more effective undergraduate learning and teaching.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".