The Effectiveness of a Discovery-Learning Strategy in the Acquisition of Scientific Concepts Among Kindergarten Students in Jordan
Bibliographic record
Abstract
The present study aimed to detect the effectiveness of using a discovery-learning strategy in the acquisition of scientific concepts among kindergarten students whose ages are between 5-6 years. The study used the experimental method through semi-experimental design with pre and post-test for the experimental and control groups. To achieve the goal of the study, a visual test for the scientific concepts was developed. After verifying the validity and reliability of the scale, it was applied to the study sample, which included 49 boys and girls randomly assigned to two groups,: An experimental group consisting of 24 boys and girls who were taught by using a discovery-learning strategy, and a control group consisting of 25 boys and girls were taught by using the traditional methods. The results of variance analysis showed a statistically significant difference at the level α = 0.05 between the mean scores of the responses of the control and experimental groups’ participants in the post-test of scientific concepts, attributed to the use of the discovery-learning strategy, and for the benefit of the experimental group. The study found no statistically significant differences at the level of α = 0.05 between the mean scores of the experimental group's participants in the post-test of scientific concepts attributed to gender variable, nor there was any statistical effect of interaction between gender and teaching strategy. In the light of these results, the study concluded the effectiveness of using a discovery-learning strategy in the acquisition of scientific concepts among kindergarten children.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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 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".