PENINGKATAN KEMAMPUAN KOMUNIKASI DAN BERPIKIR KRITIS MATEMATIS MELALUI MODEL KOOPERATIF STAD DAN MURDER
Bibliographic record
Abstract
ABSTRAKPenelitian ini membandingkan penerapan pembelajaran kooperatif tipe STAD (Student Team Achievement Divisions) dengan pembelajaran kooperatif tipe MURDER (Mood-Understanding-Recall-Detect-Elaborate-Review) ditinjau dari kemampuan komunikasi, berpikir matematis, dan Pengetahuan Awal siswa (PAM). Subjek penelitian adalah 49 siswa kelas X di salah satu SMK di Kabupaten Bandung, 23 siswa untuk kelas STAD dan 26 siswa untuk kelas MURDER. Kemampuan komunikasi dan berpikir kritis dievaluasi dari hasil pretes, postes dan N-Gain. Data dianalisis menggunakan uji t dan anova satu jalur. Untuk mengetahui perbedaan hasil penerapan kedua pembelajaran kooperatif berdasarkan Pengetahuan Awal Matematis siswa (PAM) uji scheffe digunakan sebagai sebagai uji lanjutan. Hasil statistik menunjukkan bahwa tidak terdapat perbedaan N-Gain kemampuan komunikasi matematis (p = 0,405, p 0,05) dan peningkatan kemampuan berpikir kritis matematis (p = 0,667, p 0,05) antar tipe pembelajaran kooperatif. Pengaruh PAM terhadap hasil penerapan kedua pembelajaran kooperatif kemudian dibahas.ABSTRACTThis study compared the implementation of STAD (Student Team Achievement Divisions) and MURDER (Mood-Understanding-Recall-Detect-Elaborate-Review) cooperative learning in terms of mathematical communication, critical thinking, and students’ prior knowledge. Subjects were 49 tenth grader in one of vocational high schools in Bandung District, 23 students for STAD class and 26 for MURDER. Mathematical communication and critical thinking ability were evaluated from pretest, posttest, and N-Gain. Data were analyzed using t-test and one-way ANOVA. Difference in implementation results according to students’ prior knowledge was evaluated using scheffe test. Statistical analysis suggested that N-Gain difference in mathematical ability (p = 0,405, p 0,05) as well as mathematical critical thinking (p = 0,667, p 0,05) was insignificant between cooperative learning type. Students’ prior knowledge effect on these cooperative learning implementation results was addressed.
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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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.005 |
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".