Enhancing Thai In-service Teachers’ Perceptions of STEM Education with Tablet-based Professional Development
Bibliographic record
Abstract
National efforts in Thailand are currently focused on promoting STEM (Science, Technology, Engineering, and Mathematics) education in order to better prepare the future generations to be an effective and productive workforce. In accordance with this mission, the goal of this research is to develop a tablet-based professional development (PD) program to enhance in-service teachers’ perceptions of STEM education, which will directly affect both their decision to incorporate STEM, as well as their ability to effectively do so in their own classroom. To assess the efficacy of the PD program, we recruited 240 STEM and non-STEM teachers from basic education schools in Thailand to participate in the program. The activities in this program were divided into three parts: 1) increasing knowledge about STEM education, 2) providing demonstrations of STEM teaching, and 3) developing STEM-based lessons. Data were collected throughout the tablet-based PD program from focus group discussion sessions, pre-post questionnaires, and informal interviews. Data were analyzed using content analysis. The findings revealed that before participating in the tablet-based PD program, the majority of participants had limited knowledge on STEM education and were uncertain on how to integrate STEM into their instructional practices. They also had difficulty with connecting the different STEM disciplines in their activities. Although they were interested in implementing the STEM educational approach, they lacked confidence on how to accomplish this. After completing the tablet-based PD program, many participants had a much better understanding of STEM education and greater confidence with implementing STEM pedagogical approaches.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".