Routine Breakers for Emotionally Active Learning: A Case Study
Bibliographic record
Abstract
The present paper aims to present a typology of classroom activities which may serve as group driving dynamics to improve student attention in class. Human attention skills may have been shortened now and traditional ways of imparting knowledge should be modified (Soslau, 2015). As a consequence, this implies multi-tasking behaviour as users develop a sense of immediacy. At the same time, student attention span is shorter at school and it decreases after certain time in the classroom doing monotonous activities. In order to find teaching solutions to this problem, we present what we call routine breakers, that is, classroom activities and catalysts with which to improve and optimise learner attention. We present students’ feedback and routine breaker results in the form of a case study: overt classroom observations in a group of undergraduate students in a Spanish university. The practice of these attention-catching exercises, accompanied by a number of changes in the teaching routine, renders a typology of routine breakers which is described in this study. When comparing a traditionally held class and a session with routine breakers, study participants rate the latter more positively. Further pedagogical implementations are also suggested.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".