Validity of BRADeR Learning Model Development: An Innovative Learning Model to Improve Science Literacy Skills for Junior High School Students
Bibliographic record
Abstract
The results of the preliminary study show that the scientific literacy ability in 4 SMP Negeri Pematangsiantar is still relatively low. Since science study habits are still traditional and minimize the significance of being able to read science as a competency that students must acquire, there is a tendency for the learning process to not aid students in developing their scientific literacy skills. Due to this, the BRADeR learning model was developed using innovation, taking into account the benefits and drawbacks of the inquiry and SETS models as well as supporting theoretical and empirical research. This study serves to determine the validity of the BRADeR learning model that has been developed. The method of collecting validity data uses the focus group discussion (FGD) method. The validity of the BRADeR learning model was assessed based on content validity and construct validity. The BRADeR learning model was established and is in the very valid category, according to the validity results from experts in the field of science education (IPA). The BRADeR learning paradigm can be used to enhance high school students' science literacy abilities.
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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 | 0.027 | 0.046 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".