Empowering Early Learners: Unveiling the “Play and Learn” Mobile Adventure for Little Explorers
Bibliographic record
Abstract
In this mixed-methods study, 73 preschoolers from three schools participated in pre-test/post-test assessments and user satisfaction surveys to evaluate the "Play and Learn" mobile e-learning application for foundational learning of alphabets, numbers, and shapes in children aged 3-6 years.The app's multimedia elements-animations, music, and interactive quizzes-were tailored to young learners' cognitive abilities to ensure smooth navigation and sustained attention.Results showed significant gains across all three schools, with perfect-score rates rising from 79% pre-test to 93% post-test, and a 93% satisfaction rate for engagement and design effectiveness.These findings demonstrate how educational technology, multimedia learning, and adaptive design can bridge gaps in early childhood education by enhancing knowledge retention and holistic development.In conclusion, "Play and Learn" offers an innovative, accessible, and enjoyable mobile learning solution for preschoolers and provides valuable insights for future e-learning technologies.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".