Empowering Future Teachers: The Effectiveness of Project-Based Learning in Developing Creative Tendencies Among Pre-Service Early Childhood Teachers
Bibliographic record
Abstract
Creative tendencies are considered one of the key abilities in the field of preschool education and should be intentionally nurtured during the pre-service teacher training stage. However, traditional lecture-based teaching still dominates instructional practices, limiting opportunities for pre-service early childhood teachers to develop their creative tendencies. This study aims to explore the relationship between project-based learning (PBL) and creative tendencies, specifically examining the impact of PBL on the creative tendencies of pre-service early childhood teachers. A quasi-experimental design was employed with a total of 82 participants. The experimental group (EG) participated in a PBL-oriented Picture Book Design Course, while the control group (CG) received traditional lecture-based instruction. Analysis of pre-test and post-test data revealed that both groups showed significant improvement in creative tendencies after the intervention; however, the EG exhibited significantly greater improvement compared to the CG. Further comparisons of post-test scores showed that the EG significantly outperformed the CG in each subdimension of creative tendencies—risk-taking, curiosity, imagination, and challenge—as well as in the total score. The findings provide empirical support for PBL as an effective teaching strategy to systematically enhance the creative tendencies of pre-service early childhood teachers in Picture Book Design Courses. This study offers both theoretical grounding and practical insights for curriculum development and teaching innovation in early childhood education.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".