PEMBELAJARAN FISIKA BERBASIS HANDS ON ACTIVITIES UNTUK MENUMBUHKAN KEMAMPUAN BERPIKIR KRITIS DAN MENINGKATKAN HASIL BELAJAR SISWA SMP
Bibliographic record
Abstract
Penelitian tindakan kelas ini bertujuan untuk mendeskripsikan model pembelajaran berbasis Hands on Activities, menumbuhkankemampuan berpikir kritis serta meningkatkan hasil belajar siswa SMP kelas VIII. Penelitian ini dilaksanakan dalam tiga siklus.Setiap siklus terdiri dari empat tahap yaitu perencanaan, pelaksanaan tindakan, pengamatan dan refleksi. Data kemampuanberpikir kritis, hasil belajar afektif dan psikomotorik diperoleh dari lembar observasi, hasil belajar kognitif diperoleh melalui tes.Hasil penelitian menunjukkan bahwa nilai kemampuan berpikir kritis meningkat secara signifikan disertai dengan peningkatanjumlah siswa yang termasuk kategori kritis maupun sangat kritis. Selain itu nilai rata-rata hasil belajar juga mengalami peningkatansecara signifikan sehingga dapat disimpulkan bahwa penerapan pembelajaran fisika berbasis Hands on Activities dapatmenumbuhkan kemampuan berpikir kritis serta meningkatkan hasil belajar siswa. The goals of this three-cycles classroom action research are to describe Hands on Activities based learning model, grow criticalthinking ability and increase learning achievement of JHS student-grade VIII. The data of critical thinking ability, affective andpsychomotor learning achievement are derived from observation sheet, while those of cognitive learning achievement was takenfrom test. The result shows that there is a significant increase of critical thinking ability and average of learning achievement leadingto the conclusion that Hands on Activities based learning model, grow critical thinking ability and increase learning achievement ofJHS. Keywords: critical thinking; Hands on activities (HOA); classroom action research
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.032 | 0.004 |
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".