The Effectiveness of Brain-Based Learning (BBL) on Students’ Achievement and Knowledge Retention in Science
Bibliographic record
Abstract
The aim of the current study is to investigate the effects of Brain-Based Learning (BBL) on academic achievement and knowledge retention in science subjects for middle school learners. The participants were six graders at one of the private schools in Abu Dhabi, United Arab Emirates (N=85). In the study, a pre-test (before the beginning of the experiment), experimental design (eight weeks), a post-test (week eight at the end of the experiment), and a retention test (ten days after the experiment) have been used to test the hypothesis. The participants were divided into two groups; an experimental group where 40 students were subjected to intervention of BBL during science classes for about eight weeks, and a control group where 45 students had conventional science classes. The pre-test results before the experiment and the post-test conducted at the end of week eight were analyzed to explore the effectiveness of BBL on students’ achievement in science, the data showed that there was no significant difference between the control group and the experimental group. As a view to explore the effectiveness of BBL on knowledge retention, the results of the post- test and retention test, conducted ten days after the experiment, were compared and analysed, the data showed that there was a significant difference in the results between the control and experimental groups in the boys’ classes. This suggests that BBL approach may be more effective on knowledge retention than the conventional teaching approach.
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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 | 0.005 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| 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".