Optimizing of Physics Learning through PjBL-STEM Model to Improve Critical Thinking Skills and Students Responsibility Attitudes
Bibliographic record
Abstract
Physics learning is a complex subject that required an extraordinary understanding. Based on the results of interviews at SMAN 4 DKI Jakarta, in Banda Aceh, critical thinking skill tests have not been carried out and student responsibility in following lessons. This research aims to optimize physics learning through the PjBL-STEM model, in order to improve students' critical thinking skills and lack of sense responsible attitudes. The research design that used in this research was a one group Pretest and Post-Test Design, it was involving 120 students in grade XI. The data collection techniques are carried out through observation, interviews, questionnaires and tests that are prepared based on indicators of critical thinking skills. This research data was analyzed using the average test, N-gain and paired sample t-test. The instruments used critical thinking skills tests and responsibility attitude questionnaires. The research results show that the average N-gain 0,67 is categorized as currently. The results of the responsible attitude questionnaire are in the effective category with an average of 367.2, From the findings of this research it can be concluded that the PjBL-STEM model can optimize physics learning in improving critical thinking skills and attitudes of responsibility.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".