Emotions and emotion regulation in undergraduate studying: examining students’ reports from a self-regulated learning perspective
Bibliographic record
Abstract
This study examined undergraduate students’ reports of emotions and emotion regulation during studying from a self-regulated learning (SRL) perspective. Participants were 111 university students enrolled in a first-year course designed to teach skills in SRL. Students reflected on their emotional experiences during goal-directed studying episodes at three times over the semester. Measures included self-evaluations of goal attainment, emotion intensity ratings and open-ended descriptions of emotion regulation strategies. Findings generally revealed that positive emotions were positive predictors and negative emotions were negative predictors of self-evaluations of goal attainment, although positive emotions were associated with larger changes in self-evaluations. Boredom was analysed separately and was found to be a positive predictor at the between-person level but not a predictor at the within-person level. Finally, students reported (a) enacting a variety of strategies to regulate their emotions and (b) using a different strategy more often than the same strategy from one study session to the next.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".