Investigation of Turkish and Italian Students’ Perceptions of the Concept of "Mathematics Teacher" through Metaphor Analysis
Bibliographic record
Abstract
The main purpose of the present research is examining the Turkish and Italian students’ perceptions of the concept of"mathematics teacher" through metaphors. The study group of the research consists of 167 Turkish and 112 Italianstudents, the total of 279 students in the same age group. Students were asked to use another concept defining what“mathematics teacher” meant for them and to explain why. For this purpose, the data of the research were collectedby each student’s completing the statement "A mathematics teacher is like ..., because …." Content analysistechnique was used to analyze and interpret the obtained data. According to the findings of the research, the studentsdeveloped a total of 255 valid metaphors. These metaphors are divided into 9 different conceptual categoriesaccording to their common characteristics. According to the results of the analysis, Turkish students developedmetaphors on the didactic quality of mathematics teachers and Italian students developed metaphors aboutpersonality traits of mathematics teachers. Additionally, Turkish male students developed metaphors about the factthat mathematics teachers were their constant supporters. These findings are believed to have resulted from themathematics teaching styles of math teachers and the cultural factors.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 source (direct Gemma or distilled Codex), 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".