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Record W4312334910 · doi:10.57250/ajup.v1i3.17

Penerapan Metode Think Pair and Share dalam Meningkatkan Kemampuan Membaca Wacana Bahasa Inggris di SMAN 1 Purworejo

2021· article· id· W4312334910 on OpenAlexaff
Eko Hendarto

Bibliographic record

VenueArus Jurnal Pendidikan · 2021
Typearticle
Languageid
FieldComputer Science
TopicEducational Methods and Media Use
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsHumanitiesPhysicsPsychologyArt

Abstract

fetched live from OpenAlex

Penelitian ini bertujuan untuk meningkatkan kemampuan peserta didik dalam memahami wacana berbahasa Inggris dengan menggunakan metode pembelajaran Think Pair and Share di SMA Negeri 1 Purworejo, Jawa Tengah yang meliputi 1) implementasi metode Think Pair and Share di dalam proses pembelajaran, 2) implementasi metode Think Pair and Share dalam menemukan informasi pada level low order thinking skills (LOTS) dan high order thinking skills (HOTS), 3) analisis peningkatan kemampuan peserta didik dalam membaca wacana berbahasa Inggris. Subyek penelitian ini adalah peserta didik kelas XII sebanyak 36. Penelitian ini dilaksanakan dalam dua siklus dengan teknik pengumpulan data berupa penilaian tertulis yang dilakukan secara periodik, pengamatan dan angket. Instrumen penelitian berupa tes, jurnal guru dan kuesioner. Dengan penerapan metode Think Pair and Share hasil belajar dalam memahami wacana Bahasa Inggris dinyatakan meningkat yang ditandai dengan kenaikan prosentase belajar tuntas peserta didik. Prosentase ketuntasan belajar peserta didik pada saat pretest adalah 66%, pada siklus 1 adalah 72% dan pada siklus 2 adalah 82%. Hal ini menunjukkan bahwa metode Think Pair and Share bekerja efektif dalam meningkatkan kemampuan membaca wacana bahasa Inggris peserta.

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.

How this classification was reachedexpand

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.540
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.041
GPT teacher head0.301
Teacher spread0.260 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2021
Admission routes1
Has abstractyes

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