Pre-service Teachers’ Readiness for Online Learning
Bibliographic record
Abstract
The purpose of this study was to determine pre-service teachers’ readiness foronline learning. In this study, existing situation has been descripted. Descriptive surveymethod was used. The participants of the study were pre-service teachers taking teachingcertification through online education in the fall semester 2015-2016. All of the participantstook part in the study voluntarily. Seven of the participants were female, two of them male.The data were collected through the focus group interviews including questions about thereadiness for online learning. The interview questions were formed in light of the literatureand examined by the expert in this field. The questions were organized under four categories,namely, “communication self-efficacy”, “institutional support”, “self-directed learning”, and“learning transfer self-efficacy”. Obtained data are grouped under the category of positive,negative and neutral. There are 68 positive, 7 neutral and 20 negative expressions. Whenproportioned, positive statements are approximately three and half times more than negativestatements. By this results we can say participants’ readiness for online learning is atsufficient level.
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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 | 0.002 | 0.000 |
| Scholarly communication | 0.000 | 0.003 |
| Open science | 0.003 | 0.001 |
| 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 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".