Approaches to Learning Questionnaire: Checking Context-specificity
Bibliographic record
Abstract
Students’ Approaches to Learning (SAL) have been widely assessed using a range of established instruments. In the early phase of the current research conducted in the Democratic Republic of Congo (DR Congo), one of the well-known classical instruments was employed. However, the results indicated concerns regarding its validity and reliability within the Congolese context. This prompted the development of a more contextually appropriate tool. As a result, the Approaches to Learning Questionnaire (ALQ) was specifically designed for use in the DRC. While the ALQ was tailored to reflect local educational realities, its core dimensions remain closely aligned with widely recognized constructs in the broader SAL literature. This conceptual alignment suggests that the ALQ may have broader applicability beyond its original context. To explore this potential, the current study examines the psychometric properties and validity of the ALQ within a Belgian educational setting. By evaluating its structural integrity, reliability, and construct validity, this research aims to assess the ALQ’s transferability and its potential as a robust instrument for measuring students’ learning approaches across diverse educational environments.
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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 | 0.007 | 0.022 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".