Academic self‐handicapping: The role of self‐concept clarity and students' learning strategies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Self-handicapping is linked to students' personal motivations, classroom goal structure, academic outcomes, global self-esteem and certainty of self-esteem. Academic self-handicapping has yet to be studied with respect to students' consistency in self-description and their description of themselves as learners. AIMS: This study examined students' self-esteem and self-concept clarity as well as their tendencies to employ deep- or surface-learning approaches and self-regulate while learning in relation to their self-handicapping tendencies and exam performance. SAMPLE: Participants were 161 male and female Canadian, first-year university students. METHOD: Participants completed a series of questionnaires that measured their self-esteem, self-concept clarity, approaches to learning, self-regulation and reflections on performance prior to and following their exam. RESULTS: Self-handicapping was negatively correlated with self-concept clarity, deep learning, self-regulated learning and exam grades, and positively correlated with surface learning and test anxiety. Regression analyses showed that self-concept clarity, self-regulation, surface-learning and test anxiety scores predicted self-handicapping scores. Self-concept clarity, test anxiety scores, academic self-efficacy and self-regulation were predictors of mid-term exam grades. CONCLUSIONS: This study showed that students' self-concept clarity and learning strategies are related to their tendencies to self-handicap and their exam performance. The role of students' ways of learning and their self-concept clarity in self-handicapping and academic performance was explored.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| 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 it