Pre-service Teachers' Science and Web 2.0 Affect and Aspiration: A Survey Study
Bibliographic record
Abstract
Teachers’ affect and aptitude towards science and technology influence their students through their teaching, other activities, and informal interactions. The study explored and understand Ontario pre-service teachers’ affects toward science and Web 2.0 by designing and validating a questionnaire that includes demographic, usage, and scale questions; and by surveying 134 B.Ed. students. The science part of the survey was validated and analyzed, the Web 2.0 scale items were excluded because of low correlation.\nThe results indicate that: (1) Pre-service teachers have overall high motivation, high self-efficacy, a positive attitude, and medium aspiration towards science. (2) Science motivation, self-efficacy, attitude, and aspiration scores in the survey can be predicted by other categories; however, self-efficacy and aspiration do not predict each other. (3) Five variables – time spent on learning about science, time using Web 2.0 to learn science, educational background, science-related university major, and teaching option – influence pre-service teachers’ science motivation, self-efficacy, attitude, and aspiration.
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.
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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".