Correlation between Class Evaluation of University Students and Procrastination
Bibliographic record
Abstract
The purpose of this study is to clarify how the characteristics of class evaluation are related to the time of submission of the assignments by university students. Specifically, this paper considered class evaluation based on the three interactions of value of use, value of interest, and expectation and examined the correlation between each factor and the interaction of the factors and the submission time of the assignments. 47 (22 boys and 25 girls) who received responses to the class evaluation questionnaire and agreed to use the data were analyzed. As a result, it was shown that the value of interest and the interaction of value of use and value of interest influenced the timing of submission of the assignments. On the other hand, when the value of interest was low even if it was useful, there was a tendency to delay the submission of the assignments. Interestingly, the assignments were submitted faster when they were less useful and less interest. Using this result as a starting point for clarifying the mechanism of procrastination and pre-crastination and demonstrate the reproducibility of whether the same tendency can be seen even if the scene or target person is changed in the future.
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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 | 0.030 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".