The Effect of Self-Assessment on EFL Learners’ Self-Efficacy
Bibliographic record
Abstract
This study investigated the continuous influence of self-assessment on EFL (English as a foreign language) learners’ self-efficacy. The participants, divided into an experimental and a control group, were 57 Iranian EFL learners in an English-language institute. The participants’ self-efficacy was measured through a questionnaire that was the same for both groups. Additionally, the participants in the experimental group completed a biweekly self-assessment questionnaire throughout the semester. The obtained data were analyzed through an Analysis of Covariance (ANCOVA). The findings showed that the students’ self-efficacy improved significantly in the experimental group. This suggests that applying self-assessment on a formative basis in an EFL setting leads to increased self-effi- cacy. This study thus highlights the pedagogical implications of self-assessment in EFL classrooms.Cette étude a porté sur l’influence continue de l’auto-évaluation sur l’auto-effi- cacité des apprenants en ALE. Les participants, 57 Iraniens étudiant l’ALE dans un institut de langue anglaise, ont été répartis parmi un groupe expérimental et un groupe témoin. Le même questionnaire a été administré aux deux groupes et a servi d’outil pour mesurer l’auto-efficacité des apprenants. Les membres du groupe expérimental ont en plus complété un questionnaire d’autoévaluation chaque deux semaines au cours du semestre. Les données ont été traitées par une analyse de covariance (ANCOVA). Les résultats indiquent que l’auto-efficacité des élèves s’est améliorée de façon significative dans le groupe expérimental, ce qui porte à croire que la mise en pratique d’une auto-évaluation formative dans les cours d’ALE entraine une amélioration de l’auto-efficacité. Cette étude fait donc ressortir les incidences pédagogiques de l’auto-évaluation dans les cours d’ALE.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".