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Record W2974911753 · doi:10.17977/jptpp.v4i3.12064

Optimalisasi Keterampilan Berbicara melalui Penerapan Metode Silent Way Berbantuan Google Talk

2019· article· id· W2974911753 on OpenAlex
Retna Widowati

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJurnal Pendidikan Teori Penelitian dan Pengembangan · 2019
Typearticle
Languageid
FieldComputer Science
TopicEducational Methods and Media Use
Canadian institutionsWiLAN (Canada)
Fundersnot available
KeywordsPsychologyPhysicsHumanitiesMathematics educationArt

Abstract

fetched live from OpenAlex

Penelitian ini bertujuan untuk meningkatkan keterampilan berbicara siswa melalui metode pembelajaran silent way berbantuan google talk. Penelitian tindakan kelas ini diterapkan pada siswa kelas XI-IPA1 SMAN 1 Pati semester ganjil tahun ajaran 2017/2018 dengan dua siklus. Pengumpulan data menggunakan lembar observasi dan rubrik penilaian speaking. Analisis data dilakukan dengan menghitung frekuensi pengulangan berbicara dengan google talk dan persentase siswa dalam setiap level mulai dari terendah ke tertinggi (very poor sampai excellent). Hasil penelitian menunjukkan bahwa penerapan metode ini mampu meningkatkan keterampilan berbicara dengan indikator keberhasilan yakni penurunan frekuensi pengulangan berbicara dan peningkatan persentase siswa pada level excellent.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.774
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0020.002
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0020.003
Open science0.0050.001
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0030.003

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.

Opus teacher head0.024
GPT teacher head0.283
Teacher spread0.259 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it