Moroccan EFL Secondary School Teachers’ Current Practices and Challenges of Formative Assessment
Bibliographic record
Abstract
This study aims at achieving two fundamental objectives: (1) exploring the extent to which Moroccan EFL secondary school teachers apply questioning, teacher feedback, peer-assessment and self-assessment as forms of formative assessment, and (2) identifying the micro and macro challenges that render the effective utility of formative assessment difficult. Despite the theoretical prominence of formative assessment, it has not been adequately addressed by research in Morocco. Therefore, exploring formative assessment practices might lead to a great understanding of what practices Moroccan EFL secondary school teachers frequently draw on to assess learners formatively. Following an explanatory sequential mixed-method design, the present study has gathered data from 98 EFL secondary school teachers using both questionnaires and semi-structured interviews. The most important results reveal that not all formative assessment practices are frequently employed and that teachers experience a number of contextual, institutional and pedagogical challenges. The results obtained from this study are vital to different stakeholders: practitioners, teacher trainers, decision makers, researchers and teachers as well.
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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 | 0.026 | 0.047 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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 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".