Application of artificial intelligence in early childhood development: a scoping review protocol

Abstract

Introduction: Early childhood-specifically, the period from 0 to 6 years of age-is a critical time in children's lives with rapid growth in their cognitive, social and emotional development. This period has also been shown to be the most effective time for early interventions. The use of artificial Intelligence (AI) for supporting early child development is increasing alongside the rapid advancement of technology. AI can be used directly by children (eg, for implementing adaptive technologies), by individuals who interact with children (eg, educators, parents, nurses), and by individuals indirectly supporting early child development (eg, early childhood researchers or policy analysts). This scoping review will provide a roadmap for relevant stakeholders on how AI has been applied within and across different contexts to support infants and young children's development, as well as the most predominant AI technologies used across various contexts.

Methods and analysis: The current study follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Review The search syntax will be applied in PsycINFO, ERIC, Education Source, CINHAL, MEDLINE, Embase and IEEE Xplore. The purpose of this study is to curate and synthesise academic papers to examine the application of AI for supporting the development of children between birth and age 6 years of age. Studies with children or individuals who work directly or indirectly with children will be included. Part of the abstract and full-text screening will be conducted by two researchers, with discrepancies being resolved by the lead authors. In addition, AI will be used to help with study screening and data extraction once confirmed to be reliable (Cohen's kappa >0.80). Thematic and content analyses will be conducted to identify the types of AI products used and their applications in different contexts, the most predominant AI products used within and across each context, as well as how children's developmental outcomes are impacted by the use of these AI products. Where applicable, visualisations such as tables, graphs and figures will be used to synthesise the data across contexts and AI products used to support early development of young children.

Keywords: Artificial Intelligence; Child Development; Early Childhood Education; Evidence Synthesis Methods; Human-in-the-Loop.

Figure 1. PRISMA flow chart diagram. PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses.