Correlation Between Thinking Styles and Teaching Styles of Prospective Mathematics Teachers
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Increasing the quality of education is based on changes thinking and teaching styles. Considering variance ofthinking styles and teaching styles person to person, identifying thinking styles and teaching styles of prospectivemathematics teachers is very important. So, the aim of this study is to determine the correlation between thinking andteaching styles of prospective mathematics teachers and to examine thinking styles and teaching styles of theprospective mathematics teachers by considering some demographic characteristics. The sample of the researchconsisted of 80 prospective mathematics teachers who studied at the Mathematics Education Department of AhmetKeleşoğlu Education Faculty at Necmettin Erbakan University. Relational screening model was used in analysis ofthe data. “Thinking Styles Scale” which was developed by Sternberg and Wagner (1992) and adapted to Turkish byBuluş (2006) and “Teaching Style Inventory” developed by Grasha (1994) and adapted to Turkish by Uredi (2006)were used as data collection tool in the research. According to the conclusion of the research, a positive moderatecorrelation was found between thinking styles and teaching styles of prospective mathematics teachers.
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.
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) | 0.000 | 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 it