The impact of a professional development model for a mobilized science curriculum: a case study of teacher changes
Bibliographic record
Abstract
Background and purpose: To date, there has been little research on the Teacher Professional Development (TPD) for delivering a mobile technology-supported science curriculum. To address this, a TPD model for a science curriculum supported by mobile technology was developed and evaluated in this paper. The study reported focuses on the establishment of the TPD model and exploration of its impact on teacher behaviors in the curriculum implementation.Sample, design, and methods: In the study, two representative science teachers’ implementation of the science curriculum was presented together with an in-depth study of the TPD sessions. The data from the teacher-led PD working sessions, classroom observation and teacher interview were collected. Mixed methods and case study were used to analyze the teacher performance on the PD working sessions and on the curriculum implementation.Results: Our findings suggested that teachers benefited from the structured TPD which provided opportunities for sharing, extensive feedback, and reflection of the curriculum implementation. It showed that teachers had transformed questioning from traditional ways into constructivist-oriented patterns in the classroom. More student-centered activities were conducted and complemented with teachers’ various scaffolds for learning. Analysis of learning artifacts attested to improvements in students’ conceptual understanding of science.Conclusion: TPD refers to a continuing and dynamic system for PD which needs to be changed and elaborated based on teacher needs, school context and the problems and challenges encountered in the teaching practice. TPD development and teachers’ growth in the belief and competences on the instruction constitute a mutual evolution process. Their evolution could guarantee the apt enactment and spread of the curriculum innovation to impact depth, to sustain and to spread.
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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 | 0.007 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".