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Record W4390145451 · doi:10.52060/mp.v8i2.997

MENINGKATKAN HASIL BELAJAR MATEMATIKA MENGGUNAKAN MODEL PROBLEM BASED LEARNING PADA PESERTA DIDIK KELAS IV SD

2023· article· id· W4390145451 on OpenAlexaff
Nurlev Avana, Tri Wera Agrita, Ratri Putri

Bibliographic record

VenueJurnal Muara Pendidikan · 2023
Typearticle
Languageid
FieldComputer Science
TopicEducational Methods and Media Use
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsPhysics

Abstract

fetched live from OpenAlex

Penelitian ini didasarkan pada menerapkan model-model. Hal ini menyebabkan proses dan hasil belajar peserta didik yang buruk. Penelitian tindakan kelas ini bertujuan untuk meningkatkan hasil dan proses belajar matematika di kelas IV SDN 34/II Leban. Penelitian ini terdiri dari dua siklus, dengan perencanaan, pelaksanaan, observasi, dan refleksi. Studi ini dimulai pada semester kedua akademik 2022/2023. Metode pengumpulan datanya adalah melalui pengamatan, dokumentasi, dan hasil tes. Hasil analisis data penelitian menunjukkan bahwa model pembelajaran berbasis (PBL) dapat meningkatkan proses dan hasil belajar matematika di kelas IV SDN 34/II Leban. Hal ini ditunjukkan oleh hasil proses mengajar guru pada siklus I sebesar 74% dan siklus II sebesar 98%, dengan peningkatan pada siklus I dan II sebesar 24%. Hasil proses belajar peserta didik pada siklus I sebesar 64,22% dan siklus II sebesar 90,74%, dengan peningkatan pada siklus I dan II sebesar 26,5%. Hasil belajar peserta didik pada siklus I sebesar 45,45% dan siklus II sebesar 72,72%, dengan peningkatan pada siklus I dan II sebesar 45.75%.

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, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.267
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0030.001
Research integrity0.0000.002
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 head0.050
GPT teacher head0.320
Teacher spread0.270 · 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 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
Published2023
Admission routes1
Has abstractyes

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