Effectiveness of Using Discovery Learning Model Assisted Tracker on Improvement of Physics Learning Outcomes Observed From Students’ Initial Knowledge
Why this work is in the frame
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Bibliographic record
Abstract
The purpose of this study is to determine the effectiveness of the use of discovery-assisted discovery learning models to improve physics learning outcomes in terms of students' initial knowledge. This research was conduct at Senior High School 1 Talibura in the academic year 2019/2010. This research is an experimental research that uses a quasi-experimental design consisting of a nonequivalent (pretest-posttest) control group design. Sampling uses simple random sampling so that two sample classes obtained, namely level XI MIA 1 as an experimental class and class XI MIA 2 as a control class. The first knowledge instrument and learning outcomes are subjective tests (essays) that have been tested for validity and reliability. Hypothesis testing using ANCOVA \ntest. Based on data analysis, the results showed that there was an influence of the tracker assisted discovery hearing model on student physics learning outcomes, where Fcount is higher than Ftable (4,484 > 3,20) with the significant value obtained is smaller than the significance level (0,017 < 0,05). From this study, we can conclude that the discovery-assisted discovery learning model tracker is handy to be used in physics learning to improve student physics learning outcomes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it