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Record W4384344380 · doi:10.29408/didika.v9i1.17455

Pengembangan Modul Pembelajaran Matematika Materi Pecahan Berbasis Kearifan Lokal Kelas IV SDN 2 Surabaya

2023· article· id· W4384344380 on OpenAlexaff
Musabihatul Kudsiah, Irma Dewi

Bibliographic record

VenueJurnal DIDIKA Wahana Ilmiah Pendidikan Dasar · 2023
Typearticle
Languageid
FieldMathematics
TopicMathematics Education and Pedagogy
Canadian institutionsEncana (Canada)Discovery Air (Canada)
Fundersnot available
KeywordsPhysicsHumanities

Abstract

fetched live from OpenAlex

Penelitian ini bertujuan untuk mengembangkan modul pembelajaran matematika materi pecahan berbasis kearifan lokal menggunakan desain penelitian Borg and Gall yang terdiri dari 10 langkah disederhanakan menjadi 7 langkah, yaitu (1) melakukan analisis kebutuhan, (2) perencanaan, (3) pengembangan produk awal, (4) pengujian terbatas, (5) revisi hasil uji produk, (6) uji produk utma, (7) revisi produk akhir. Penelitian ini dilakukan pada peserta didik kelas IV dengan jumlah 11 peserta didik. Instrumen penelitian dan pengembanngann ini menggunakan lembar validasi dan angket respon peserta didik. Hasil uji validasi ahli desain media dengan jumlah skor 93 berada pada rentang skor X>83,94 dengan kategori “sangat baik”. Hasil uji validasi ahli materi dengan jumlah skor sebesar 90 berada pada rentang skor X>83,94 dengan kategori “sangat baik”. Hasil dari angket respon peserta didik terhadap kevalidan dan kefektifan penggunaan modul yang dikembangkan mendapatkan skor rata-rata 50,53 dan berada pada rentang 39<X≤51 dengan kategori “cukup baik”. Sehingga dapat disimpulkan, modul pembelajaran matematika materi pecahan berbasis kearifan lokal valid dan efektif digunakan dalam pembelajaran di Sekolah Dasar

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)0.004
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), Research integrity, Insufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.222
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0030.003
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.003
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0030.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0210.033

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 head0.071
GPT teacher head0.343
Teacher spread0.272 · 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 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

Citations1
Published2023
Admission routes1
Has abstractyes

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