Unpacking and Transforming Teachers’ Beliefs Toward Inquiry-Oriented Teaching Through Lesson Study: A Cross-Case Analysis of Thai Preservice Science Teachers
Bibliographic record
Abstract
Teachers’ beliefs can be seen as psychological seeds planted in teachers’ minds. Teachers’ beliefs about effective inquiry-based teaching impact their intentions, instructional designs, and actions required for inquiry-based lessons. This paper discusses how to help Thai preservice science teachers who engaged in their student-teaching practicum in middle schools transform their beliefs toward inquiry-based science teaching through Lesson Study (LS). The research questions guiding this study include: 1) What critical factor contributes to Thai preservice science teachers’ transforming their beliefs toward inquiry-based science teaching? 2) How could LS help Thai preservice science teachers transform their beliefs toward inquiry-based science teaching? and 3) How can LS be integrated into Thai preservice teacher education programs to cultivate preservice science teachers’ inquiry-oriented beliefs and experiences in LS? Multiple data sets were collected, including teacher interviews, LS discussion meetings, and reflection forms. The cross-case analysis indicated that although all preservice science teachers developed more inquiry-oriented beliefs through the LS sessions, their progression paths varied among preservice teachers. A non-anxiety-driven facilitation and flexible modifications were found to be essential for making the LS sessions meet each preservice science teacher’s idiosyncratic needs so that their belief transformations take place towards inquiry-based teaching as they overcome their fear and anxiety in adopting this approach. This study suggests that this facilitation is vital in unlocking diverse avenues of transformations in preservice science teachers’ varying belief systems toward inquiry-driven science teaching.
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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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".