PENERAPAN MODEL TAI UNTUK MENINGKATKAN AKTIVITAS BELAJAR SISWA PADA MATA PELAJARAN MATEMATIKA DI KELAS V-B SD NEGERI 053955 PAYA SALIT
Bibliographic record
Abstract
Abstract: Application of Model TAI To Improve Student Learning Activities In Maths Lesson In Class V-B Elementary School 053 955 Paya Salit. The purpose of this study was to determine the increased activity of learning and students' mathematics learning outcomes when implementing cooperative learning model Team Assisted Individualization (TAI) in class V-B Elementary School 053 955 Paya Salit T.P. 2015/2016. The subjects were all students of class V-B Elementary School 053 955 Paya Salit T.P. 2015/2016, totaling 24 people. The results showed that the cooperative learning model Team Assisted Individualization (TAI) to increase the average student activity and student learning outcomes in the first cycle, there were 13 students who completed individually while the class was not finished and the second cycle there are 22 students who completed individually and classes have been completed. Keywords: Model TAI, Activities Learning, Learning Outcomes Abstrak : Penerapan Model TAI Untuk Meningkatkan Aktivitas Belajar Siswa Pada Mata Pelajaran Matematika Di Kelas V-B SD Negeri 053955 Paya Salit. Tujuan penelitian ini adalah untuk mengetahui peningkatan aktivitas belajar dan hasil belajar matematika siswa saat menerapkan model pembelajaran kooperatif tipe Team Assisted Individualization (TAI) di kelas V-B SD Negeri 053955 Paya Salit T.P. 2015/2016. Subjek penelitian adalah seluruh siswa kelas V-B SD Negeri 053955 Paya Salit T.P. 2015/2016, berjumlah 24 orang. Hasil penelitian menunjukkan bahwa model pembelajaran kooperatif tipe Team Assisted Individualization (TAI) meningkatkan rata-rata aktivitas belajar siswa dan hasil belajar siswa pada siklus I terdapat 13 siswa yang tuntas secara individu sedangkan kelas belum tuntas dan siklus II terdapat 22 siswa yang tuntas secara individu dan kelas sudah tuntas. Kata Kunci : Model TAI, Aktivitas Belajar, Hasil Belajar
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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) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.028 | 0.003 |
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".