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Record W4245610152 · doi:10.31227/osf.io/6ytvg

UPAYA MENINGKATKAN HASIL BELAJAR SISWA PADA MATA PELAJARAN IPS MATERI AKTIVITAS EKONOMI DENGAN MENGGUNAKAN MODEL PEMBELAJARAN KOOPERATIF TIPE MAKE A MATCH DI KELAS IV MIN MEDAN TEMBUNG

2017· preprint· id· W4245610152 on OpenAlexaff
Semnas PGSD FIP UNIMED, Syarifah Aini, Athiyyah Zahrah Al Fananie

Bibliographic record

Venuenot available
Typepreprint
Languageid
FieldComputer Science
TopicEducational Methods and Media Use
Canadian institutionsBell (Canada)
Fundersnot available
KeywordsPhysicsMathematics

Abstract

fetched live from OpenAlex

AbstrakPenelitian ini bertujuan untuk mengetahui (1) hasil belajar sebelum menggunakan Model Pembelajaran Kooperatif Tipe Make A Match pada mata pelajaran IPS Materi Aktivitas Ekonomi di kelas IV MIN Medan Tembung, (2) hasil belajar setelah menggunakan Model Pembelajaran Kooperatif Tipe Make A Match pada mata pelajaran IPS materi Aktivitas Ekonomi di kelas IV MIN Medan Tembung, dan (3) Penerapan menggunakan Model Pembelajaran Kooperatif Tipe Make A Match pada mata pelajaran IPS yang dapat meningkatkan hasil belajar siswa kelas IV MIN Medan Tembung. Penelitian ini berupa PTK (Penelitian Tindakan Kelas), dengan subjek penelitian berjumlah 35 siswa. Kesimpulan dari hasil penelitian adalah: (1) hasil belajar siswa sebelum tindakan mendapat nilai rata-rata 71,42, siswa yang tuntas sebanyak 34,29% (12 siswa). (2) hasil belajar siswa setelah diterapkan Model Pembelajaran Kooperatif Tipe Make A Match pada siklus I nilai rata-rata menjadi 77,72 siswa yang tuntas sebanyak 62,86% (22 siswa). (3) hasil belajar siklus II nilai rata-rata meningkat menjadi 82 siswa yang tuntas sebanyak 80% (28 siswa).

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)0.006
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow), Research integrity
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.771
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.001
Meta-epidemiology (narrow)0.0040.003
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0030.001
Scholarly communication0.0060.002
Open science0.0110.008
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0010.001

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 head0.067
GPT teacher head0.331
Teacher spread0.263 · 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; both teacher heads agree on what is shown here.

Study designSimulation or modeling
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
Published2017
Admission routes1
Has abstractyes

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