Factors Affecting General and Online Academic Achievement of University Students: Online Self-Regulated Learning, Online Self-Efficacy, and Motivation Scores
Bibliographic record
Abstract
This study aims to determine whether university students' levels of online self-regulated learning, online technologies self-efficacy, and motivated strategies for learning predict their general academic achievement and online academic achievement. In this study, the scanning design and the prediction research design were used. The participants of this research consisted of 55 undergraduate students studying in different departments of a university in Western Canada. The data were collected with “Online Technologies Self-Efficacy Scale (OTSES)” developed by Barnard et al., (2009); “Motivated Strategies for Learning Questionnaire (MSLQ)” developed by Pintrich et al., (1991); “Online Self-regulated Learning Questionnaire (OSLQ)” developed by Miltiadou and Yu (2000); and “demographic form”. This study did not determine a significant relationship between university students' total scores of OSLQ, OTSES, MSLQ, and their GPAs. Instead, the study found that university students' total scores of OSLQ, OTSES, MSLQ did not significantly predict their GPAs and online GPAs.
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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 | 0.005 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".