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Record W3195732524 · doi:10.20961/shes.v3i4.54409

Peningkatan Hasil Belajar Bahasa Indonesia melalui Media Audiovisual pada Siswa Kelas III Sekolah Dasar

2020· article· en· W3195732524 on OpenAlexaff
Tita Yulinda

Bibliographic record

VenueSocial Humanities and Educational Studies (SHEs) Conference Series · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology-Enhanced Education Studies
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsIndonesianAction researchMathematics educationPsychologyMathematicsLinguistics

Abstract

fetched live from OpenAlex

This Classroom Action Research is to improve learning outcomes of Indonesian language lessons on the theme of growth and development of living things in third grade students of SD Negeri Karangbandung 02, Keanggungan District, Brebes Regency using audiovisual media. In this model, classroom action research is carried out through four stages, namely planning, action implementation, observation, and reflection and is carried out in two cycles. From this class action research, it was obtained that the average pre-cycle score of students was 59.64 with a completeness percentage of 39.28%. In the first cycle it increased to 63.21 with a completeness percentage of 57.14%. In the second cycle the average score of students became 66.96 with a completeness percentage of 71.42%. Based on the data obtained, it can be concluded that the use of audiovisual media can improve learning outcomes of Indonesian language with the theme of growth and development of living things in third grade students of SD Negeri Karangbandung 02, Keanggungan District, Brebes Regency.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.079

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0240.004

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 head0.146
GPT teacher head0.358
Teacher spread0.212 · 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 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".

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Citations0
Published2020
Admission routes1
Has abstractyes

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