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The Key Artificial Intelligence Technologies in Early Childhood Education: A Review

Yi Honghu, Liu Ting, Lan Gongjin

TL;DR

The paper surveys the current landscape of AI in early childhood education, with a focus on AI-based robotic agents and interventions for children with autism spectrum disorder. It combines a qualitative review of representative robots (e.g., NAO, KASPAR, Keepon, Paro, Probo) with a comprehensive bibliometric analysis (via Scopus) to map publication trends, venues, and key contributors from 2010 to 2022. It identifies core challenges—data scarcity and quality, explainability, and educator readiness—while outlining trends toward integrating state-of-the-art AI (including large language models) and VR/vision/NLP tools to enhance learning and social development. The work provides a structured taxonomy, actionable insights, and recommendations to guide future research and practice in AI-enabled early education, serving both newcomers and experienced researchers.

Abstract

Artificial Intelligence (AI) technologies have been applied in various domains, including early childhood education (ECE). Integration of AI educational technology is a recent significant trend in ECE. Currently, there are more and more studies of AI in ECE. To date, there is a lack of survey articles that discuss the studies of AI in ECE. In this paper, we provide an up-to-date and in-depth overview of the key AI technologies in ECE that provides a historical perspective, summarizes the representative works, outlines open questions, discusses the trends and challenges through a detailed bibliometric analysis, and provides insightful recommendations for future research. We mainly discuss the studies that apply AI-based robots and AI technologies to ECE, including improving the social interaction of children with an autism spectrum disorder. This paper significantly contributes to provide an up-to-date and in-depth survey that is suitable as introductory material for beginners to AI in ECE, as well as supplementary material for advanced users.

The Key Artificial Intelligence Technologies in Early Childhood Education: A Review

TL;DR

The paper surveys the current landscape of AI in early childhood education, with a focus on AI-based robotic agents and interventions for children with autism spectrum disorder. It combines a qualitative review of representative robots (e.g., NAO, KASPAR, Keepon, Paro, Probo) with a comprehensive bibliometric analysis (via Scopus) to map publication trends, venues, and key contributors from 2010 to 2022. It identifies core challenges—data scarcity and quality, explainability, and educator readiness—while outlining trends toward integrating state-of-the-art AI (including large language models) and VR/vision/NLP tools to enhance learning and social development. The work provides a structured taxonomy, actionable insights, and recommendations to guide future research and practice in AI-enabled early education, serving both newcomers and experienced researchers.

Abstract

Artificial Intelligence (AI) technologies have been applied in various domains, including early childhood education (ECE). Integration of AI educational technology is a recent significant trend in ECE. Currently, there are more and more studies of AI in ECE. To date, there is a lack of survey articles that discuss the studies of AI in ECE. In this paper, we provide an up-to-date and in-depth overview of the key AI technologies in ECE that provides a historical perspective, summarizes the representative works, outlines open questions, discusses the trends and challenges through a detailed bibliometric analysis, and provides insightful recommendations for future research. We mainly discuss the studies that apply AI-based robots and AI technologies to ECE, including improving the social interaction of children with an autism spectrum disorder. This paper significantly contributes to provide an up-to-date and in-depth survey that is suitable as introductory material for beginners to AI in ECE, as well as supplementary material for advanced users.
Paper Structure (29 sections, 9 figures, 4 tables)

This paper contains 29 sections, 9 figures, 4 tables.

Table of Contents

  1. Introduction
  2. Related Review
  3. Contributions
  4. Bibliometric Analysis
  5. Intelligent Robots for ECE
  6. iRobiQ
  7. NAO
  8. KASPAR
  9. Keepon
  10. AIBO
  11. IROMEC
  12. iCat
  13. Paro
  14. Probo
  15. Other Intelligent Robots
  16. ...and 14 more sections

Figures (9)

  • Figure 1: Taxonomy of this survey on AI for early childhood education.
  • Figure 2: The number of publications per year (from 2010 to 2022) on the topic of AI in ECE. The dashed red lines are the fit of the number of publications. Scopus database returned 9014 results until 10/10/2022.
  • Figure 3: Aggregation type of publications on the topic of AI in ECE (from 2010 to 10/10/2022).
  • Figure 4: Top 20 authors and their number of publications on the topic of AI in ECE (from 2010 to 10/10/2022).
  • Figure 5: Top 20 affiliations and their number of publications on the topic of AI in ECE (from 2010 to 10/10/2022).
  • ...and 4 more figures