A Multi-Dimensional Exploration of Teachers' Beliefs About Civic Education in Australia, England, and the United States
Bibliographic record
Abstract
Teachers' beliefs influence their behaviors in classrooms and their organization of classes, each of which can greatly impact student learning. This study focuses on four categories of teachers' beliefs—beliefs about subject, about learners and learning, about teaching, and about self-efficacy—and their potential to shape civic education. More specifically, this study takes a comparative approach in examining how national policies in Australia, England, and the United States might influence educational beliefs. Analyses of data from the IEA Civic Education Study reveal that teachers from these countries generally hold beliefs that: (a) engagement-based civic activities are necessary components of citizenship, (b) students should learn about engagement, (c) civic education is valuable, and (d) they are confident in presenting these topics. Differences among countries exist in many areas, most notably in teachers' views of activist-oriented citizenship and in the importance of national loyalty. Interrelations among these beliefs are also examined.
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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 | 0.009 | 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 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".