Systematic Review of the Negative Impact of Early Childhood Education Learning Digitalization on Early Childhood Development
Bibliographic record
Abstract
This study aims to critically analyze the negative impacts of digitalization of Early Childhood Education (ECE) learning on early childhood development. Systematic Literature Review (SLR) was chosen in this writing by identifying, analyzing, and synthesizing relevant academic literature study results from 2015 to 2025 from various scientific databases. The total number of articles reviewed was 20 in Indonesian and English. The analysis results show that excessive use of digital media can have negative impacts on children's physical, cognitive, social, and emotional development. These include increased risk of obesity, language development delays, decreased social skills, and the emergence of anxiety and depression. The research also found that the type and intensity of digital media use as well as parental involvement play important roles in strengthening or reducing these impacts. The involvement of parents and educators becomes an important point in wisely regulating digital media use and setting time limits for its use. This study provides theoretical and practical foundations for formulating ECE education policies that are adaptive to the digital era while considering holistic aspects of child development.
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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 | 0.013 | 0.055 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.013 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".