Some days are more satisfying than others: A daily‐diary study on optimism, pessimism, coping, and academic satisfaction
Bibliographic record
Abstract
BACKGROUND: Feelings of satisfaction fluctuate across time and situations, and focusing on within-person experiences opens up the door to a better understanding of the daily lives of university students. AIMS: Our overarching goal was to situate academic satisfaction not only as a relatively enduring characteristic but also as a transient state that fluctuates across days in the lives of student. In the present study, we explored how optimism and pessimism related to inter-individual differences in academic satisfaction. We also investigated the association between coping and academic satisfaction at both the between- and within-person levels. SAMPLE: = 19.14) participated in this study. METHOD: Students completed baseline measures of optimism and pessimism. They were then asked to complete daily-diary measures of academic coping strategies and academic satisfaction during six consecutive days. RESULTS: At the between-person level, results from multilevel mediation analyses demonstrated that optimism was associated with greater academic satisfaction and that task-oriented coping was a significant mediator of this association. At the within-person level, our analyses revealed that the daily satisfaction of students varies according to the coping strategies used on those specific days. Almost half of the variance in academic satisfaction can be attributable to daily fluctuations. CONCLUSIONS: This source of within-person variance is non-negligible and supports the need to also conceive academic satisfaction as a question of when. These findings illustrate the importance of considering the role of personality and daily coping to better conceptualize and understand academic satisfaction of university students.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".