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Record W4404854515 · doi:10.1080/2331186x.2024.2433818

Exploring Online Preschool Programs in children’s academic preparation for elementary school: a case study in Indonesia

2024· article· en· W4404854515 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCogent Education · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Digital Technology
Canadian institutionsEducation and Early Childhood Development
Fundersnot available
KeywordsPsychologyMathematics educationAcademic achievementPedagogyMedical educationMedicine

Abstract

fetched live from OpenAlex

The COVID-19 pandemic has transformed preschool education, expanding beyond traditional methods to include digital learning innovations, even in early childhood education. This study investigates the implementation of Islamic education through an Online Preschool Program in Indonesia. Using a qualitative approach, the research involved 20 parents as participants over eight months. Data were collected through interviews, observations, and document analysis and analyzed using NVIVO 12 software in conjunction with Miles and Huberman’s framework. The findings highlight the diverse online preschool programs available, parents’ motivations for and challenges in enrolling their children, and the perceived benefits and impacts on both parents and children. Key results show that the Online Preschool Program effectively supports parents in integrating Islamic education at home while also contributing to children’s intellectual, social, and religious development and enhancing their readiness for formal schooling. This study fills gaps in previous research by providing an in-depth analysis of the role of online preschool programs in Islamic education during early childhood.

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.174
Threshold uncertainty score0.476

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.132
GPT teacher head0.395
Teacher spread0.263 · 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