Artificial Intelligence (AI)-Driven Curriculum Development in Early Childhood Education: Educators' Insights, Barriers, and Policy Pathways

The integration of Artificial Intelligence (AI) in early childhood education (ECE) has gained global attention for its potential to enhance personalized learning and inclusivity. However, challenges such as teacher preparedness, infrastructure limitations, and ethical concerns hinder its effective implementation, particularly in developing contexts. This study explores the perceptions of educators regarding AI-driven curriculum development in ECE, identifies challenges and opportunities, and assesses the effectiveness of AI-based learning models. A qualitative research approach was used, involving semi-structured interviews and focus group discussions with 20 educators from two districts of Lahore, Pakistan. Data were analyzed using thematic analysis. Findings indicate that AI enhances engagement, supports personalized learning, and benefits children with special needs. However, infrastructure gaps and lack of teacher training remain major barriers. The study recommends capacity-building programs for educators, policy frameworks for ethical AI adoption, and investment in digital infrastructure to ensure equitable access to AI-driven education.

Authors

Institutions

Publication Details

Journal
Research Journal of Psychology
Published
2025-03-23
DOI
https://doi.org/10.59075/rjs.v3i1.102
Citations
4
Primary Topic
Engineering Education and Technology
Type
article
Field-Weighted Citation Impact
12.98
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Artificial Intelligence (AI)-Driven Curriculum Development in Early Childhood Education: Educators' Insights, Barriers, and Policy Pathways

Syed Tahir Abbas Shah, Zulqarnain Haider, Abdul Qayyum, Shahbaz Ahmad et al.
4 citations
Research Journal of Psychology
Engineering Education and Technology
12.98
article

Artificial Intelligence (AI)-Driven Curriculum Development in Early Childhood Education: Educators' Insights, Barriers, and Policy Pathways

Syed Tahir Abbas Shah, Zulqarnain Haider, Abdul Qayyum, Shahbaz Ahmad, Zeshan Rafique
article en
4 citations

Abstract

The integration of Artificial Intelligence (AI) in early childhood education (ECE) has gained global attention for its potential to enhance personalized learning and inclusivity. However, challenges such as teacher preparedness, infrastructure limitations, and ethical concerns hinder its effective implementation, particularly in developing contexts. This study explores the perceptions of educators regarding AI-driven curriculum development in ECE, identifies challenges and opportunities, and assesses the effectiveness of AI-based learning models. A qualitative research approach was used, involving semi-structured interviews and focus group discussions with 20 educators from two districts of Lahore, Pakistan. Data were analyzed using thematic analysis. Findings indicate that AI enhances engagement, supports personalized learning, and benefits children with special needs. However, infrastructure gaps and lack of teacher training remain major barriers. The study recommends capacity-building programs for educators, policy frameworks for ethical AI adoption, and investment in digital infrastructure to ensure equitable access to AI-driven education.

Research Journal of PsychologyVol. 3(1)
Institute of Radiotherapy and Nuclear Medicine (PK), University of Education (PK)
Openalex Percentile: Top 2%
Engineering Education and Technology
12.98
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.