Being Academically At-risk and Building Capacity for Self-regulated Learning in University
Bibliographic record
Abstract
University students who experience academic failure are at risk of becoming curbed by a pattern of failure in the absence of adequate self-regulatory processes. Repeated academic failures can result in academic probation or suspension, and the student is labeled academically at-risk (AAR). Adapted from Pintrich and Zusho’s (2007) model for student motivation and self-regulated learning (SRL) in the postsecondary classroom, this study proposes a model specific to the AAR student experience. Using existing literature on academically struggling student SRL and motivation, and psychometric analyses of an academic intervention’s assessment of the study habits and attitudes of AAR undergraduate students, this research investigates SRL within the AAR student experience, expands on the original model’s areas of SRL (cognition, behaviour, motivation and affect, and context), and demonstrates the intervention’s effect on AAR students’ SRL capacity. Future directions for AAR-specific SRL research, refinements to the model and assessments, and other implications are discussed.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".