Investigating Primary School Teachers’ Knowledge Towards Meanings of Fractions
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".