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Reconceptualizing Generative AI Adoption in Early Childhood Education: An Integrated TAM-TPACK Analysis of AI-Supported Storytelling
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Abstract
Language development in early childhood requires intentional and well-structured stimulation, especially through storytelling. Initial observations at PAUD Anna Husada showed that children in Group A still struggled to follow story sequences, apply new vocabulary, and express ideas confidently. This study examines teachers’ perceptions of using EaseMate AI to support receptive and expressive language skills in children aged 4–5 years, guided by the Technology Acceptance Model (TAM) and the Technological Pedagogical and Content Knowledge (TPACK) framework. Using a descriptive qualitative design, data were collected through observations, interviews, and documentation involving five Group A teachers. The findings reveal that teachers perceived EaseMate AI positively because it provides varied, relevant, and easy-to-use story content that helps children better comprehend narratives and encourages more confident verbal expression. However, teachers also noted challenges such as formal vocabulary, limited visual features, and differing levels of digital proficiency. Overall, EaseMate AI demonstrates strong potential as a supportive tool for early childhood language learning, particularly when its use is adapted to children’s developmental characteristics and complemented with appropriate pedagogical strategies.
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