The Effectiveness of Using Brainstorming Strategy in the Development of Academic Achievement of Sixth Grade Students in English Grammar at Public Schools in Jordan
Bibliographic record
Abstract
The study aims to identify the effect of using brainstorming method in the teaching of English grammar; to improve the level of sixth grade students in English grammar at public schools in Jordan. The study population consisted of all sixth grade students of both sexes. The sample of the study was chosen in the random stratified manner, represented in four schools: two for males and two for females, which were divided into two groups (experimental and control). The results showed that there were significant differences at the level of (α = 0.05) in the achievement test in the English grammar, in favor of the experimental group. The results also showed significant differences between males and females in the achievement test in favor of the females. One of the most prominent recommendations was to refer to those concerned with educational guidance, and school administrations to give priority to the issue of the weakness of students in English grammar by focusing on the use of modern methods of teaching, including the method of brainstorming.This study deals with a vital subject concerns those interested in the educational process, especially in the field of teaching English, where the study sheds light on the method of brainstorming and how to benefit from it to narrow the gap resulting from traditional practices in the teaching of English grammar, in order to reach objective results that reflect the pedagogical and educational reality regarding the level of students' achievement in the English grammar.
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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 | 0.003 |
| 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) | 0.001 | 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".