MétaCan
Menu
Back to cohort

STUDENTS' EPISTEMOLOGICAL BELIEFS IN SOLVING GEOMETRY TRANSLATION PROBLEMS

2022· article· en· W4311158887 on OpenAlexaff
Syafruddin Kaliky, Patma Sopamena, Arya Dwihening Putra

Bibliographic record

VenueKALAMATIKA Jurnal Pendidikan Matematika · 2022
Typearticle
Languageen
FieldMathematics
TopicMathematics Education and Pedagogy
Canadian institutionsCarbon Engineering (Canada)
Fundersnot available
KeywordsMathematics educationNumeracyMathematical problemDocumentationIndonesianSimple (philosophy)LiteracyComputer sciencePsychologyPedagogyEpistemologyLinguistics

Abstract

fetched live from OpenAlex

The 2018 PISA results show that Indonesian students' numeracy and literacy skills are poor. Epistemological beliefs, beliefs in mathematical knowledge, are one of the factors contributing to poor student literacy skills. This study analyzes epistemological beliefs in solving translation problems of Year 9 students in one of the junior high schools in Manipa Islands, Indonesia. This research employed a descriptive a qualitative approach. The subjects in this study were students who tend to meet the indicators of epistemological beliefs. Data collection techniques were observation, tests, interviews, and documentation. The results showed that students' epistemological beliefs in completing the translation met the requirements. First is being able to solve mathematical problems by taking time, where students needed time to solve the problem. This is because students are not sure that they can solve them. Second, students can solve problems that cannot be solved with simple, step-by-step procedures, where students solve problems using their rules/settlement procedures. The third is understanding essential concepts in mathematics, where students understand and work on translation problems using mathematical concepts well. Fourth, word problems are essential in mathematics, with word problems, students can improve critical thinking skill. Finally, efforts can improve mathematical abilities, where students can try to solve problems to improve their math skills. Efforts include reviewing the lesson and increasing practice questions.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.280
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0140.000

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 head0.097
GPT teacher head0.368
Teacher spread0.271 · 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 designTheoretical or conceptual
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
Published2022
Admission routes1
Has abstractyes

Explore more

Same venueKALAMATIKA Jurnal Pendidikan MatematikaSame topicMathematics Education and PedagogyFrench-language works237,207