Developing a TPACK-based Course to Promote the Pre-service Preschool Teachers’ Instructional Design Competence
Bibliographic record
Abstract
This study integrates the TPACK framework into a Preschool Language Education course to examine its effects on pre-service preschool teachers' instructional design competence (IDC). The research aims to explore effective methods for IDC development and analyze its growth characteristics. Using an R&D methodology, this study employed an experimental design with an experimental group and a control group. Data were collected from 41 pre-service preschool teachers at Putian University, Fujian Province, China, through cluster sampling. The experimental group (n=21) participated in a 13-week TPACK-based course, while the control group (n=20) received traditional instruction. The IDC Scale and Lesson Plan Scoring Rubric were used for data collection. Data analysis included independent and paired t-tests, as well as assessments of lesson plan scores and grade distributions. Key findings indicate that (1) the TPACK-based course encompasses course objectives, content, learning organization, and assessment, with all participants achieving satisfactory or higher lesson plan scores and a 95% satisfaction rate; (2) the course significantly enhances pre-service preschool teachers' IDC; and (3) at the early stage of professional development, IDC growth exhibits characteristics of simplification, linearity, and dogmatism.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".