Basic Technology Competencies, Attitude towards Computer Assisted Education and Usage of Technologies in Turkish Lesson: A Correlation
Bibliographic record
Abstract
The present research was done to determine the basic technology competency of Turkish teachers, their attitude towards computer-assisted education, and their technology operation level in Turkish lessons, and to designate the relationship between them. 85 Turkish teachers studying in public schools in Bartin participated in the research. The research was designed with relational screening model. The results obtained in the research are as follows: The information technology competency of Turkish teachers was determined as high-level in technologies usually used vocationally, and as mid-level in others The Turkish teachers had high-level of attitude towards computer-assisted teaching. However, they tended to use technology in their lessons at mid-level. The dependent variables did not indicate remarkable differences based on gender, teaching experience, and education level. Results showed that there was a high-level relationship between the attitude towards computer-assisted education and using information technology in Turkish lessons. Also, there existed a mid-level relationship between the basic technology competency and attitude towards computer-assisted education.
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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 | 0.001 | 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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".