An Investigation of Saudi English-Major Learners’ Perceptions of Formative Assessment Tasks and Their Learning
Bibliographic record
Abstract
The effect of standardised and summative assessment on teaching and learning has been explored in various settings. Formative assessment or classroom assessment, however, has not captured considerable attention of washback researchers. The prime goal of the inclusion of formative assessment in the assessment regime of a curriculum is to allow learners to grow as independent learners. This study investigated if learners’ perceptions of formative assessment tools influenced their learning strategies, the scope of what they learned, and the depth of their learning. The results of a survey, distributed among 400 Taif University English-major female learners (TUEMFL) showed that the respondents preferred formative assessment tasks to comprise expected questions in the form of multiple-choice questions. In addition, formative assessment tasks narrowed down the scope of the syllabus the learners studied. However, the participants deemed formative assessment helpful in diagnosing and improving their mistakes. Therefore, it is suggested that the nature formative assessment tasks should synchronise with their course objectives to help learners improve their academic skills. This may mean that the assessment tasks should be more authentic in nature and should have a greater consequential validity replacing the multiple-choice questions which often culminate in surface-level learning.
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How this classification was reachedexpand
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 | 0.003 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".