Towards Effective Artificial Intelligence-Driven Learning in Indonesian Child Education: Understanding Parental Readiness, Challenges, and Policy Implications

Background/purpose. The integration of artificial intelligence (AI) into child education presents transformative opportunities, yet Indonesian parental readiness remains insufficiently explored. This study examines parental preparedness, barriers to adoption, and policy interventions to ensure effective AI implementation in child education. Materials/methods. A mixed-methods approach was employed, involving surveys of 100 Indonesian parents to assess AI literacy, accessibility, and attitudinal challenges. In-depth interviews provided qualitative insights into socio-economic constraints and cultural apprehensions. Quantitative data were analyzed using descriptive statistics and regression modeling, while thematic analysis was applied to qualitative responses. Results. Survey findings revealed that while most parents recognized AI’s potential, their ability to support AI-integrated learning effectively remained limited. Higher education levels, digital literacy, and stable internet access were strong predictors of AI adoption readiness. However, substantial challenges persisted, including data privacy concerns, algorithmic bias apprehensions, and anxieties over reduced human interaction in learning. The practical implication of this study suggests that targeted AI literacy programs are key to empowering Indonesian parents for effective AI integration in child education. Conclusion. Parental readiness for AI integration in Indonesian child education remains critically limited, shaped by inadequate digital competencies, socio-economic constraints, and ethical apprehensions. This study proposes a policy agenda centered on AI literacy programs tailored to parents, accessible educational resources, equitable infrastructure, and data protection frameworks to enable responsible and inclusive AI adoption. As the first empirical mapping of Indonesian parental readiness in this domain, the study offers a globally relevant insight that underscores the urgent need to empower parents as co-navigators of AI-driven educational futures.

Authors

Publication Details

Journal
Educational Process International Journal
Published
2025-01-01
DOI
https://doi.org/10.22521/edupij.2025.15.155
Citations
9
Primary Topic
Educational Curriculum and Learning Methods
Type
article
Field-Weighted Citation Impact
80.34
Controls
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article

Towards Effective Artificial Intelligence-Driven Learning in Indonesian Child Education: Understanding Parental Readiness, Challenges, and Policy Implications

Safuri Musa, Sri Nurhayati, Taufikin Taufikin, Loso Judijanto
9 citations
Educational Process International Journal
Educational Curriculum and Learning Methods
80.34
article

Towards Effective Artificial Intelligence-Driven Learning in Indonesian Child Education: Understanding Parental Readiness, Challenges, and Policy Implications

Safuri Musa, Sri Nurhayati, Taufikin Taufikin, Loso Judijanto
article en
9 citations

Abstract

Background/purpose. The integration of artificial intelligence (AI) into child education presents transformative opportunities, yet Indonesian parental readiness remains insufficiently explored. This study examines parental preparedness, barriers to adoption, and policy interventions to ensure effective AI implementation in child education. Materials/methods. A mixed-methods approach was employed, involving surveys of 100 Indonesian parents to assess AI literacy, accessibility, and attitudinal challenges. In-depth interviews provided qualitative insights into socio-economic constraints and cultural apprehensions. Quantitative data were analyzed using descriptive statistics and regression modeling, while thematic analysis was applied to qualitative responses. Results. Survey findings revealed that while most parents recognized AI’s potential, their ability to support AI-integrated learning effectively remained limited. Higher education levels, digital literacy, and stable internet access were strong predictors of AI adoption readiness. However, substantial challenges persisted, including data privacy concerns, algorithmic bias apprehensions, and anxieties over reduced human interaction in learning. The practical implication of this study suggests that targeted AI literacy programs are key to empowering Indonesian parents for effective AI integration in child education. Conclusion. Parental readiness for AI integration in Indonesian child education remains critically limited, shaped by inadequate digital competencies, socio-economic constraints, and ethical apprehensions. This study proposes a policy agenda centered on AI literacy programs tailored to parents, accessible educational resources, equitable infrastructure, and data protection frameworks to enable responsible and inclusive AI adoption. As the first empirical mapping of Indonesian parental readiness in this domain, the study offers a globally relevant insight that underscores the urgent need to empower parents as co-navigators of AI-driven educational futures.

Educational Process International JournalVol. 15(1)
Quality Education
Openalex Percentile: Top 0%
Educational Curriculum and Learning Methods
80.34
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