EFL Primary School Teachers’ Attitudes, Knowledge and Skills in Alternative Assessment
Bibliographic record
Abstract
The study investigated female EFL primary school teachers’ attitudes as well as teachers’ knowledge and skills in alternative assessment. Data was collected via a questionnaire from 335 EFL primary school teachers randomly selected from six educational zones. An interview with principals and head teachers and a focus group interview with EFL primary school teachers were conducted along with document analysis of ongoing assessment obtained from the ELT General Supervision at the Ministry of Education (MOE). Descriptive statistics were employed including a t-test and a one-way ANOVA Test. Results showed that teachers perceived themselves knowledgeable and skillful in alternative assessment. Nonetheless, some reported the need for workshops and training courses on alternative assessment. Teachers further expressed their preference for traditional written tests over alternative assessment. Teachers’ attitudes, however, were found to be at a medium level. They reported that alternative assessment is time-consuming and ignores pupil writing skills. Significant differences were found in teachers’ knowledge and skills in relation to their age, undergraduate major, and experience. Significant differences were further found in teachers’ attitudes in relation to their educational zone and experience. Limitations of the study as well as recommendations were further discussed.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".