Play-Based Learning in Malaysian Early Childhood Education: A Study of Diploma Students' Perspectives and Challenges
Bibliographic record
Abstract
Play is natural and essential to childhood (Tekyi-Arhin, 2023). This is important to children as play helps them to develop important skills such as problem-solving, creativity, and social skills such as sharing, taking turns, and communication skills (Faiz Fauzi, 2022). Play-based learning is a teaching method that emphasizes play and promotes children's cognitive, physical, social, and emotional development through activities that spark imagination and curiosity. Play is significant in early childhood education in Malaysia nowadays as it is essential to prepare young children's minds for lifetimes of learning. The implementation of play-based learning is gaining momentum in early childhood education in Malaysia, with its integration into the curriculum. This research employs a qualitative case study approach to delve into and observe the perspectives and challenges encountered by diploma students. Through purposive sampling, participants were selected from various early childhood education diploma programs from UOW Malaysia KDU College and UNITAR International University, ensuring a comprehensive representation of perspectives and experiences. By shedding light on the viewpoints of these future educators, this study will contribute to the ongoing discussion on early childhood education in Malaysia, paving the way for a more informed and effective approach to early learning. The findings revealed significant insights into three primary areas of concern. First, implementation challenges emerged, predominantly centered around resource constraints, time management difficulties, and varying levels of parental support. Second, the study identified gaps in educator preparedness, highlighting the need for enhanced training in play-based teaching methodologies and challenges in assessment practices. Third, institutional support varied considerably, with limited professional development opportunities and a need for clearer implementation guidelines. These findings collectively underscore the complex interplay of factors affecting successful play-based learning implementation in Malaysian early childhood settings. Building upon these findings, several directions for future research emerge as crucial for advancing understanding in this field.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.008 | 0.005 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| 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".