Malaysian Primary School ESL Teachers’ Questions during Assessment for Learning
Bibliographic record
Abstract
Classroom questioning is a crucial learning and instructional strategy. It has also been regarded as an important aspect of Assessment for Learning (AfL) by researchers. Classroom questioning helps students gain a better appreciation of what they are learning as well as how they are learning. It also helps teachers understand students’ learning progress. This qualitative case study is a part of a larger study on classroom questioning during AfL and it has to be reminded that only a part of the study is presented here which involves two ESL teachers (one teaching Year One and the other teaching Year Two class) and the types of questions they used during AfL. The current study was conducted in a selected primary school in Kuala Lumpur, Malaysia. To collect data, ten periods of each teacher’s classroom were observed and then interview was conducted with each teacher. Observations and interviews were tape-recorded and transcribed for further analysis. The results of this study showed that the participating teachers were aware of the importance of questioning technique during AfL, however, they asked lower cognitive questions that did not trigger thoughtful reflection. The data also revealed that the teachers in this study formulated questions that at the first sight may seem to be open questions but they expected the students to provide a short-specific answer. Although questions were designed to suit the content of the lesson, it was observed that most of the questions asked by the teachers focused on content, structure and students’ background knowledge and elicited specific, predetermined answers. In short, Most of the questions asked by the teachers in their mixed ability classes were below the students’ Zone of Proximal Development (ZPD) and did not help the students promote their thinking skills.
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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 | 0.001 | 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 | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 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".