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Record W3186776979 · doi:10.20961/shes.v3i4.53372

Increasing Student Learning Outcomes in Mathematics About Operational Numbers With Role Playing Method of Colors Media in Class V SDN Karanganyar Gunung 02 Semarang

2021· article· en· W3186776979 on OpenAlexaff
Siti Khuluqul Khasanah

Bibliographic record

VenueSocial Humanities and Educational Studies (SHEs) Conference Series · 2021
Typearticle
Languageen
FieldMathematics
TopicMathematics Education and Pedagogy
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsMathematics educationClass (philosophy)DocumentationAction researchAcademic yearPsychologyData collectionMathematicsComputer scienceStatisticsArtificial intelligence

Abstract

fetched live from OpenAlex

<p><em>This study aims to improve the ability to learn mathematics through the media of colored marbles in fifth grade students of SD Karang Anyar Gunung 02 Candisari District, Semarang City. This study uses the Kemmis Taggart class action research method with the stages of planning, implementing, observing and reflecting which consists of two cycles. The subjects of this study were 24 students of class V. Data collection techniques used observation, interviews and documentation. Techniques of data analysis using qualitative analysis. The results of the study showed that out of the 24 students who had completed the pre-cycle, only 11 (45%) students and 13 (55%) students had not completed. In the first cycle showed an increase, namely students who completed there were 16 students or (66.67%) and students who had not completed there were 8 students or (33.33%), then the results of the improvement in learning cycle II showed an increase, namely students who completed learning there were 23 students or (96%) and students who have not finished studying there is 1 student or (4%). Thus the results of the color marbles media method can improve the learning outcomes of fifth grade students at SDN Karanganyar Gunung 02 Semarang in the 2019/2020 academic year.</em></p>

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.461
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.103
GPT teacher head0.395
Teacher spread0.292 · 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 designQualitative
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
Published2021
Admission routes1
Has abstractyes

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