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Record W4312248264 · doi:10.35438/e.v10i1.567

KEMAMPUAN PEMAHAMAN KONSEP MATEMATIKA SISWA SMA

2022· article· id· W4312248264 on OpenAlexaff
Rusmin Madia, Ode Supriati Al-Idrus

Bibliographic record

VenueEdutainment Jurnal Ilmu Pendidikan dan Kependidikan · 2022
Typearticle
Languageid
FieldMathematics
TopicMathematics Education and Pedagogy
Canadian institutionsImmunoPrecise (Canada)
Fundersnot available
KeywordsHumanitiesPhysicsPhilosophy

Abstract

fetched live from OpenAlex

Tujuan dari penelitian ini adalah untuk mengetahui kemampuan pemahaman konsep matematika siswa pada materi permutasi dan kombinasi di kelas XI IPA SMAN 13 Ambon kelas IPA-5, selama satu bulan dari tanggal 03 April 2018 sampai 03 Mei 2018. Tipe penelitian ini adalah penelitian deskriptif kualitatif. Dari 37 siswa calon subjek terpilih 5 orang siswa yang diambil berdasarkan hasil tes yang diberikan. Peneliti menjadi instrumen utama dan intrumen pendukung, yaitu tes dan wawancara. Dalam penelitian ini, di analisis kemampuan pemahaman konsep matematika siswa yaitu dengan menggunakan think a louds, dengan materi permutasi dan kombinasi. Penelitian ini, menganalisis kemampuan memahami konsep matematika yaitu mendefinisikan konsep secara verbal dan tulisan, mengenal berbagai makna interpretas konsep, membandingkan dan membedakan konsep, mengidentifikasi dan membuat contoh dan bukan contoh, menggunakan model, diagram. Siswa dalam menyelesaikan soal dalam bentuk permutasi dan kombinasi saat mengerjakan soal ada yang keliru dan bingung dan lambat dalam menyelesaikan soal dengan metode wawancara think a louds. Namun siswa bisa menyelesaikan soal dan memenuhi indikator kemampuan pemahaman konsep Matematika sehingga tujuan penelitian tercapai.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.083
Threshold uncertainty score0.276

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0030.003
Scholarly communication0.0060.005
Open science0.0010.003
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0830.014

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 head0.048
GPT teacher head0.325
Teacher spread0.277 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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