Bibliographic record
Abstract
This paper aims to reveal primary teachers knowledge of the quadrilaterals about the concept of quadrilaterals by examining the definitions of the quadrilaterals. A total of four primary teachers, 1 female and 3 male teachers, participated in the study which determined by maximum diversity sampling. The data collection tool consisted of four open-ended questionnaires, which were not based on mathematical procedural knowledge of the teachers and aims to reveal the subject matter knowledge of quadrilaterals. The first question is about the definition of the quadrilaterals (square, rectangle, trapezoid, parallelogram, rhombus and deltoid), the second question is the determination of the characteristics of the quadrilaterals, the 3rd question is the comparison of the characteristics of the quadrilaterals and the 4th question is about related to the nomenclature of the quadrilaterals. The data were analyzed by using descriptive analysis method (Zazkis & Leikin, 2008). As a result of analyzes, it was seen that the subject area information of the participants was insufficient. In order to be successful in the teaching of geometry, the in-service training activities should be organized in order to eliminate the deficiencies in the subject matter knowledge and the necessity of reviewing the mathematics courses they took at the university, which can be corrected first, in the context of the content.
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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 | 0.000 |
| 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".