Development of Science Learning Activities Using Inquiry-Based Learning Management to Improve the Academic Achievement of Secondary School Students
Bibliographic record
Abstract
The objectives of this research were as follows: (1) to develop learning activities in science and technology subjects using inquiry-based learning for seventh-grade students (12-13 years old); (2) to develop academic achievement for the topic of elements and compounds using inquiry-based learning management activities to meet the 70% requirement; and (3) to assess the satisfaction of seventh-grade students who are taught with inquiry-based learning management. The target group of this study was 24 seventh-grade students on the science and technology course. The research tools included seven inquiry-based learning management plans, an achievement test, and a satisfaction assessment. The results show that synthesizing the approach to learning management using inquiry-based learning led to the formulation of learning activities. Students had better academic achievement, with a mean score of 81.45%, which was above the 70% requirement. Students were satisfied with inquiry-based learning activities, with an average of 4.75 and a standard deviation of 0.48, which is the highest level.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".