The Effects of Blog-Based Learning on Pre-service Science Teachers’ Internet Self-efficacy and Understanding of Atmosphere-Related Environmental Issues
Bibliographic record
Abstract
The aim of the study was to investigate the effects of blog-based learning (BBL) on pre-service science teachers’ Internet self-efficacy and understanding of atmosphere-related environmental problems (AREPs). The working group of the study consisted of 89 pre-service science teachers. The participants were divided into groups, and each group was asked to perform the following activities in sequence: (1) accessing scientific documents (e.g. articles, books) and reading them individually, (2) coming together in groups to discuss the scientific knowledge extracted by each group member and preparing a presentation about the issue discussed, (3) sharing findings and engaging groups in a discussion of issues, and (4) developing a blog using the knowledge from the discussions within and between groups. In this study, single-group pretest-posttest experimental design was used. To collect data, the Internet Self-efficacy Scale (ISS), the Atmosphere-related Environmental Problems Diagnostic Test (AREPDiT), and the Opinion Questionnaire about Blogging (OQaB) were used. The results revealed that the subjects’ ISS and AREPDiT post-test mean scores were significantly higher than their pre-test mean scores and that their misconceptions about AREPs were substantially eliminated by the intervention. The subjects’ responses to the blog use were generally positive.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.006 |
| 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 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".