Deep Learning and Deeper Learning in Education: A Critical Narrative Review of Evidence and Implications for Indonesia in the Society 5.0 Era
DOI:
https://doi.org/10.52562/jdle.2025.1503Keywords:
deep learning, deeper learning, Society 5.0, artificial intelligence in education, IndonesiaAbstract
Indonesian education policy links three ideas that are often run together: Society 5.0, neural-network deep learning (DL) and pembelajaran mendalam (deeper learning), a pedagogical approach. This critical narrative review asks what evidence supports AI-enabled learning applications, for whom and under what conditions in Indonesia. Secondary reviews, randomised and field trials, international guidance, Indonesian policy documents and empirical studies were purposively selected through targeted searches in October 2026 and coded thematically. The technical and pedagogical senses of “deep learning” are conceptually independent, and Society 5.0 is a normative Japanese policy vision, not an evidenced stage of development. Evidence is strongest for intelligent tutoring systems and emerging for carefully designed generative AI tutors, whereas unguided chatbot access reduced later performance in one field experiment. Indonesian evidence is thin and mostly self-reported. AI is best positioned as a scaffold for deeper learning, conditional on teacher capacity, equitable access and local evaluation.
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