Students Approaches to Learning: Towards a Context-specific Learning Approaches Instrument
Bibliographic record
Abstract
Students' Approaches to Learning (SAL) are a critical determinant of learning outcomes and have been assessed around the world, from Asia to Africa, using the traditional questionnaires developed in the Western context. However, studies in Asia have challenged the traditional dichotomous view of SAL by supporting the presence of intermediate approaches, suggesting that the current view of SAL may not be universal. In response to the need for a broader understanding of SAL, a new instrument, the Approaches to Learning Questionnaire (ALQ), was developed during a pilot study. This instrument captures both memorization and understanding in an African context, which makes it distinct from traditional instruments. Additionally, the ALQ challenges the current individualistic view of SAL by including a group dimension. Given the high psychometric quality of this new instrument, it is crucial to validate it with a large sample. Therefore, this paper discusses the validation processes and recommends the use of the ALQ for comparative purposes in the Congolese context. Further research will explore the extension of this context-specific instrument to other cultural settings and the assessment of cross-cultural validity.
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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 | 0.008 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".