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Record W4389192307 · doi:10.26858/jppsd.v3i1.47992

PENERAPAN METODE STORY TELLING UNTUK MENINGKATKAN HASIL BELAJAR BAHASA INDONESIA (STUDI SISWA KELAS V SD INPES 12/79 LEA KECAMATAN TELLU SIATTINGE KABUPATEN BONE)

2023· article· id· W4389192307 on OpenAlexaff
Abd. Hafid, DH Satrianai Satriani, Rostina Rostina

Bibliographic record

VenueJPPSD Jurnal Pendidikan dan Pembelajaran Sekolah Dasar · 2023
Typearticle
Languageid
FieldComputer Science
TopicEducational Methods and Media Use
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysicsHumanitiesArt

Abstract

fetched live from OpenAlex

Penelitian ini adalah penelitian PTK yang bertujuan untuk mendesripsikan penerapan metode story telling untuk meningkatkan hasil belajar Bahasa Indonesia siswa kelas V di SD Inpres 12/79 Lea Kecamatan Tellu Siatingge Kabupaten Bone. Subjek penelitian ini adalah seluruh siswa kelas V yang berjumlah 14 siswa dan guru wali kelas V. Setting penelitian ini bertempat di SD Inpres 12/79 Lea, jalan poros Wajo-Bone kecamatan Tellu Siattinge kabupaten Bone. Teknik pengumpulan data menggunakan observasi dan tes. Teknik analisis data yaitu mereduksi data, mendeskripsikan data, dan penarikan kesimpulan. Hasil penelitian menunjukkan bahwa Pada siklus I sebanyak 64,28% atau 9 siswa memperoleh nilai rata-rata 70,71 berada pada kategori cukup (C) dan mengalami peningkatan pada siklus II sebanyak 87,57% atau 11 siswa dengan nilai rata-rata 77,50 berapa pada kategori baik (B). Kesimpulkan penelitian ini adalah metode Story Telling dapat meningkatkan hasil belajar Bahasa Indonesia siswa kelas V SDN 12/79 Lea Kecamatan Tellu Siatingge Kabupaten Bone

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)0.008
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesMeta-epidemiology (narrow)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.195
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.001
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.005
Science and technology studies0.0040.001
Scholarly communication0.0020.003
Open science0.0050.002
Research integrity0.0010.005
Insufficient payload (model declined to judge)0.0000.002

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 head0.057
GPT teacher head0.310
Teacher spread0.253 · 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 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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