MétaCan
Menu
Back to cohort
Record W3000858288 · doi:10.30595/dinamika.v11i1.5983

PENGEMBANGAN MODEL PEMBELAJARAN TEMATIK SENI DAN BUDAYA MENGGUNAKAN VIDEO TEATERIKALISASI COWONGAN DI SEKOLAH DASAR

2019· article· en· W3000858288 on OpenAlexaboutno aff
Anastasia Dwi Wiwik Irawati, Kuntoro Kuntoro, Akhmad Jazuli

Bibliographic record

VenueDinamika Jurnal Ilmiah Pendidikan Dasar · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicCultural and Artistic Studies
Canadian institutionsnot available
Fundersnot available
KeywordsClass (philosophy)Product (mathematics)PsychologyCluster samplingData collectionTest (biology)Mathematics educationSampling (signal processing)Computer scienceArtificial intelligenceMathematicsStatisticsSociologyPopulation

Abstract

fetched live from OpenAlex

This study aims to develop a thematic learning model of art and culture usingvideo theatericalization of “Cowongan” for students in elementary schools. Thisresearch is a research development that aims to improve the ability to verbalize“Kidung Kasengsaraan Mangsa Ketiga” with the Banyumas dialect. The researchdesign uses R and D Data collection techniques in research gather information, productdesign, product validation, product testing, design revision, trial use, product revision,mass production, and dissemination. These data sources are interviews, observations,taking questionnaires, and tests. The sampling technique uses cluster sampling as thepopulation of SDN 4 Sokanegara students. The results of research in verbalizing thegeguritan include laval, intonation, placement of pauses, and expressions. Theobservations of researchers obtained data that the average posttest results that theexperimental class reached 90% of the expected score, while the average control classreached 75.75% of the expected score. The results of the effectiveness test in theresearch prove that the class that uses the product is better than the one that does notuse the product so that the ability to speak up using the Banyumas dialect is moreeffective.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.449
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.026
GPT teacher head0.293
Teacher spread0.267 · 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 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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueDinamika Jurnal Ilmiah Pendidikan DasarSame topicCultural and Artistic StudiesFrench-language works237,207