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Record W2946897545 · doi:10.5539/ies.v12n6p56

Investigating Primary School Teachers’ Knowledge Towards Meanings of Fractions

2019· article· en· W2946897545 on OpenAlexvenueno aff
Adem Doğan, Neşe Tertemiz

Bibliographic record

VenueInternational Education Studies · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicMathematics Education and Teaching Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMeaning (existential)Mathematics educationPsychologyFraction (chemistry)Test (biology)School teachersPrimary educationPedagogyChemistry

Abstract

fetched live from OpenAlex

The concept of fraction and the concepts related to the fraction have an important place in primary and secondary school education programs. In this respect, primary school teachers need to be careful about the concept and sub-meaning of the fraction. In this study, general survey model was used to determine the level of knowledge of the primary school teachers about the meaning of fractions. A total of 266 primary school teachers (149 female and 117 male) participated in the study in Turkey. For collecting data, a success test was developed by the researchers about the meaning of the fraction. The data were analyzed by using SPSS 21 package program. The general success average of the teachers was found to be 60.2%. The most successful sub-meaning of the fraction is the operator meaning with 80% and the least successful meaning is ratio meaning with 48%. Furthermore, it was concluded that there is a positive correlation with each other in all sub-meanings fractions.

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)0.002
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.464
Teacher spread0.367 · 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 designObservational
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

Citations2
Published2019
Admission routes1
Has abstractyes

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