The Effectiveness of the Inquiry and Brain Storming Strategies in Developing Achievement and Creative Thinking Skills in Arabic Language of University Students
Bibliographic record
Abstract
The study aimed to investigate the effectiveness of using inquiry and brainstorming strategies in teaching Arabic language for developing achievement and creative thinking skills of the university students. To achieve the previous objective, a teaching manual was prepared using inquiry and brainstorming strategies. Achievement test was prepared including 20 items multiple chooses questions related to knowledge, application and reasoning levels. In addition, creative thinking skills test was prepared including 10 items related to Fluency, flexibility and originality skills. The validity and reliability of the instruments were measured. The sample was selected randomly; it consists of two groups, experimental group 43 and a control group 39. The study was based on semi-experimental design pre—post-test, where the experimental group was taught using inquiry and brainstorming strategies, but the control group was taught using the usual strategies. The results of the study showed that there were statistically significant differences between the average scores of the experimental and control groups in the post achievement and creative thinking skills in general and their skills separately for the students of the experimental group. Also, the results showed a positive correlation between the scores of the experimental group in post creative thinking skills, and post achievement test in general. The effectiveness of inquiry and brainstorming strategies in the development of achievement levels and creative thinking skills was significant effect. The study recommended using the Inquiry and brainstorming strategies in the teaching Arabic language of university students.
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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 | 0.001 | 0.006 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".