MétaCan
Menu
Back to cohort
Record W4416275415 · doi:10.70437/educative.v3i3.1503

Systematic Review of the Negative Impact of Early Childhood Education Learning Digitalization on Early Childhood Development

2025· article· W4416275415 on OpenAlexaff
Mohammad Fauziddin, Mallevi Agustin Ningrum, Petra Adamcova, Aulia Rahmi Utari

Bibliographic record

VenueEducative Jurnal Ilmiah Pendidikan · 2025
Typearticle
Language
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsEarly childhoodEarly childhood educationAnxietyDigital mediaPoint (geometry)Social media

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.614
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0010.004
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.010
GPT teacher head0.303
Teacher spread0.293 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueEducative Jurnal Ilmiah PendidikanSame topicChild Development and Digital TechnologyFrench-language works237,207