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<p>Learning Objects (LOs) have long aimed to make digital education scalable and reusable, yet their alignment with constructivist learning remains contested. This study offers a structured comparison of traditional LO design principles and constructivist learning metaphors—acquisition, participation, and knowledge creation—to examine how emerging research directions position themselves within this educational technology landscape. We analyse how emerging research directions—symbolic AI, generative AI, hybrid AI (Retrieval-Augmented Generation), and constructivist-oriented LO research—align with or challenge these learning metaphors. We then explore how these directions influence the relationship between LOs and constructivist pedagogy. Our findings show that while some AI-based approaches reinforce structured, predefined learning, others—and especially constructivist-oriented LO models—support more adaptive, collaborative, and student-centred designs. Empirical findings from teacher interviews reveal that teachers’ conceptions of learning vary by context—often defaulting to transmissive models under technological constraints, but aligning more closely with participation and knowledge creation metaphors when reflecting on pedagogical theory. These combined and somewhat surprising findings underscore the need for LO frameworks that are pedagogically flexible—that is, able to support both structured and open-ended designs, adapt to varying teaching contexts, and empower learners through meaningful engagement.</p>

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A theoretical and empirical analysis of tensions between learning objects and constructivism

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年6月12日

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  • Jan Erik Dahl,
  • Anders Mørch

摘要

Learning Objects (LOs) have long aimed to make digital education scalable and reusable, yet their alignment with constructivist learning remains contested. This study offers a structured comparison of traditional LO design principles and constructivist learning metaphors—acquisition, participation, and knowledge creation—to examine how emerging research directions position themselves within this educational technology landscape. We analyse how emerging research directions—symbolic AI, generative AI, hybrid AI (Retrieval-Augmented Generation), and constructivist-oriented LO research—align with or challenge these learning metaphors. We then explore how these directions influence the relationship between LOs and constructivist pedagogy. Our findings show that while some AI-based approaches reinforce structured, predefined learning, others—and especially constructivist-oriented LO models—support more adaptive, collaborative, and student-centred designs. Empirical findings from teacher interviews reveal that teachers’ conceptions of learning vary by context—often defaulting to transmissive models under technological constraints, but aligning more closely with participation and knowledge creation metaphors when reflecting on pedagogical theory. These combined and somewhat surprising findings underscore the need for LO frameworks that are pedagogically flexible—that is, able to support both structured and open-ended designs, adapt to varying teaching contexts, and empower learners through meaningful engagement.