Time Diary and Questionnaire Assessment of Factors Associated With Academic and Personal Success Among University Undergraduates
Bibliographic record
Abstract
OBJECTIVE AND PARTICIPANTS: A sample of 231 students attending a private liberal arts university in central Alberta, Canada, completed a 5-day time diary and a 71-item questionnaire assessing the influence of personal, cognitive, and attitudinal factors on success. METHODS: The authors used 3 success measures: cumulative grade point average (GPA), Personal Success--each participant's rating of congruence between stated goals and progress toward those goals--and Total Success--a measure that weighted GPA and Personal Success equally. RESULTS: The greatest predictors of GPA were time-management skills, intelligence, time spent studying, computer ownership, less time spent in passive leisure, and a healthy diet. Predictors of Personal Success scores were clearly defined goals, overall health, personal spirituality, and time-management skills. Predictors of Total Success scores were clearly defined goals, time-management skills, less time spent in passive leisure, healthy diet, waking up early, computer ownership, and less time spent sleeping. CONCLUSIONS: Results suggest alternatives to traditional predictors of academic success.
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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 | 0.007 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".