Turkish Teachers’ Attitudes Towards Distance Learning During the Covid-19 Pandemic
Bibliographic record
Abstract
All schools in Turkey have switched to distance learning since the onset of the pandemic. This paper investigated Turkish teachers’ attitudes towards distance learning based on different variables. This study adopted a mixed research design employing both quantitative and qualitative data collection methods. The sample consisted of 292 Turkish teachers. The qualitative stage involved 292 Turkish teachers, while the qualitative stage involved ten Turkish teachers. Data were collected using a demographic characteristics questionnaire and the Distance Learning Attitude Scale (DLAS) developed by Ağır (2007). Frequency, percentage, arithmetic mean, and standard deviation were used for analysis. A t-test was used to determine whether participants’ attitudes towards distance learning differed by “gender” and “degree.” An ANOVA was used to determine whether participants’ attitudes towards distance learning differed by “work experience” and “knowledge and experience in distance learning.” The Mann-Whitney U test was used to determine whether participants’ attitudes towards distance learning differed by “school type.” A Scheffe’s Test was used to make posthoc comparisons to determine the source of significant differences. Qualitative data were collected through focus group interviews using a semi-structured interview form (n=10). The qualitative data were analyzed using content analysis. The results showed that participants had positive attitudes towards some aspects of distance learning, whereas they had negative attitudes towards others. Their DLAS scores significantly differed by “school type,” “work experience,” and “knowledge and experience in distance learning” but not by “gender” and “degree.”
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".