The Impact of Metacognition Strategies in Teaching Mathematics among Innovative Thinking Students in Primary School, Rafha, KSA
Bibliographic record
Abstract
The study aims at finding out the impact of metacognition strategies in the teaching of mathematics in developing creative thinking among gifted primary school students in Rafha province in the Kingdom of Saudi Arabia. They are defined in this study as the students whose IQ score is (120 and above) according to the Wakslar measurement for children intelligence and are selected by their teachers. The study sample consists of 40 male and female students from the fifth class in the primary stage. They were divided randomly into two groups; experimental group which was taught by the methods and strategies of the suggested teaching program and a control group upon whom the ordinary method was applied. Each group included 20 male and female students. For the purpose of the study, a creative thinking measurement in mathematics, designed by the researchers, was used for data collecting. The program was implemented for three successive weeks, three sessions per week each one lasting for one period. After finishing the program, a post measurement was conducted for all the study variables for both the experimental and control groups. The results show statistically significant differences at the significance level (0.05) between using the metacognition strategies on one hand and the ordinary method on the other. The differences were in favor of the metacognition strategies.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".