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Record W4321849932 · doi:10.20961/shes.v6i1.71057

The Influence Of The Cooperative Script Learning Model On The Learning Outcomes Of Fourth Grade Students At Elementary School

2023· article· id· W4321849932 on OpenAlexaff
Igamiralda Lumban Siantar, Antonius Remigius Abi, Patri Janson Silaban

Bibliographic record

VenueSocial Humanities and Educational Studies (SHEs) Conference Series · 2023
Typearticle
Languageid
FieldComputer Science
TopicEducational Methods and Media Use
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsMathematicsHumanitiesPhysicsPhilosophy

Abstract

fetched live from OpenAlex

<p>Tujuan yang akan dicapai pada penelitian adalah untuk mengetahui hasil belajar siswa dan untuk mengetahui pengaruh dari model pembelajaran <em>Cooperative Script</em> terhadap hasil belajar siswa kelas IV tema 7 Indahnya Keragaman di Negeriku subtema 3 Indahnya Persatuan dan Kesatuan Negeriku di SD Negeri 06 Onanrunggu Tahun Pembelajaran 2021/2022. Populasi dalam penelitian ini adalah seluruh siswa kelas IV SD Negeri 06 Onanrunggu Tahun Pelajaran 2021/2022 yang berjumlah 47. Sampel dalam penelitian ini adalah 24 siswa. Teknik analisis data dengan menggunakan uji korelasi. Hasil perhitungan statistik yang ditunjukkan bahwa hasil belajar meningkat dengan menggunakan model pembelajaran <em>cooperative script</em> dengan kategori baik dengan nilai rata-rata 78,33, sedangkan tanpa penggunaan metode tersebut yaitu cukup dengan nilai 49,66. Dan di dukung dengan hasil pengujian korelasi pada nilai 0,712 artinya r<sub>hitung</sub> ≥ r<sub>tabel</sub>. Selanjutnya pengujian hipotesis menunjukkan t<sub>hitung</sub> adalah 4,753 sedangkan t<sub>tabel </sub>1,7109 maka terbukti bahwa hipotesis lebih besar dari t<sub>tabel </sub>maka hipotesis nihil atau (Ho) ditolak dan hipotesis alternative (Ha) diterima. Hal ini menunjukkan bahwa ada pengaruh penggunaan model pembelajaran <em>cooperative script</em> terhadap hasil belajar siswa dengan perhitungan persentase 78% yang memiliki hubungan kuat. <strong></strong></p>

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.568
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0060.002
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.134
GPT teacher head0.374
Teacher spread0.240 · 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 designObservational
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
Published2023
Admission routes1
Has abstractyes

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