The Use of Brainstorming Strategy Among Teachers of Arabic for Speakers of Other Languages (ASOL) in Writing Classes
Bibliographic record
Abstract
Although brainstorming strategy is not a new concept, the practice is relatively new in the Arab region, especially, in Jordan, where the old approaches are still widely used. This qualitative study examined the attitudes of Arabic language lecturers at Language Center, University of Jordan towards utilizing brainstorming in their instruction. With the help of convenience sampling, ten lecturers were selected to participate in the study. To reach a clear understanding of this issue, the study utilized a qualitative design and semi-structured interviews and observations were used as a tool to collect the data. The findings revealed that the attitudes and the actual use of brainstorming strategy by ASOL lecturers in their instruction were generally positive. A key recommendation of the study is that further research needs to be conducted into the reasons why some instructors opt not to use brainstorming strategy in their instruction.
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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 | 0.031 |
| 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 | 0.000 |
| 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".