Kemampuan komunikasi persuasif guru dalam Motivasi Belajar Siswa Pada Bidang Studi Ilmu Pengetahuan Sosial di Mts Swasta Cendekia Medan Tahun Ajaran 2020-2021
Bibliographic record
Abstract
Penelitian ini dilaksanakan di sekolah Mts Swasta Cendekia Medan. Jenis \npenelitian yang digunakan dalam penelitian ini adalah penelitian deskriptif \nkualitatif. Penelitian ini bertujuan untuk (1)Komunikasi persuasif guru terhadap \nsiswa MTs Swasta Cendekia Medan pada mata pelajaran Ilmu Pengetahuan Sosial \n(2) Motivasi belajar s iswa MTs Swasta Cendekia Medan pada mata pelajaran \nIlmu Pengetahuan Sosial (3) Kendala-kendala yang dihadapi guru dalam \nmenggunakan komunikasi persuasif dalam memotivasi belajar siswa MTs Swasta \nCendekia Medan(4) Guru mengatasi kendala-kendala dalam komunikasi persuasif \ndi MTs Swasta Cendekia Medan. Hasil peneliti menunjukkan bahwa (1) \nMengetahui komunikasi persuasif guru terhadap MTs Swasta Cendekia Medan \npada mata pelajaran Ilmu Pengetahuan Sosial, guru dan sisawa berbicara seperti \nteman biasa tetapi masih ada batasan antara guru dan siswanya, agar siswa \ntersebut terbuka dalam penyampaian pesannya (2)Mengetahui motivasi belajar \nsiswa MTs Swasta Cendekia Medan pada mata pelajaran Ilmu Pengetahuan Sosial \nmemotivasi mereka agar rajian dan giat dalam belajar kelak kedepanya agar \nmenjadi orang yang berguna dan bermanfaat bagi orang lain.(3) Untuk \nmengetahui kendala guru dalam menggunakan komunikasi persuasif dalam \nmemotivasi belajar siswa MTs Swasta Cendekia Medan siswa sulit diatur, banyak \nbicara sama temanya yg lain, birbicara dengan temannya (4)Untuk mengatasi \nkendala-kendala dalam komunikasi persuasif di MTs Swasta Cendekia Medan \nmemberikan arahan kepada siswa, berbicara dan memberikan gambaran \ndampaknya suatu kegagalan dalam pembelajaran.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.031 | 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".