Contribution of an instructional module incorporating PhET simulations to Rwandan students' knowledge of chemical reactions, acids, and bases through social interactions
Bibliographic record
Abstract
The current study ascertained the influence an instructional module had on enhancing students’ understanding of chemical reactions and acid–base topics. The sample size for this study consisted of 197 students, including 101 in an “experimental” group and 96 in a “control” group, selected from schools in two Districts (Rwamagana and Musanze) in Rwanda, Africa. The experimental and control groups received a pre-test and post-test to collect data. In addition, focus group discussions (FGDs) were conducted with students in the experimental group. Further, a test question analysis was used to evaluate the students’ content knowledge of chemical reactions and acids, bases, and pH. To analyze the research data, the Statistical Package for the Social Sciences (SPSS) software was used for quantitative analysis. The independent t -test results indicated no significant difference between the means of the control and experimental groups at the pre-test stage (d f = 195, p = 0.380). At the post-test stage, a statistically significant increase was observed in the mean scores of the experimental group compared to the control group (d f = 195, p < 0.001), showing that the intervention effectively improved student learning outcomes in chemistry education.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".