A Theoretical and Empirical Analysis of Tensions between Learning Objects and Constructivism
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| Title: | A Theoretical and Empirical Analysis of Tensions between Learning Objects and Constructivism |
|---|---|
| Language: | English |
| Authors: | Jan Erik Dahl (ORCID |
| Source: | Education and Information Technologies. 2025 30(15):22101-22150. |
| Availability: | Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/ |
| Peer Reviewed: | Y |
| Page Count: | 50 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Secondary Education |
| Descriptors: | Constructivism (Learning), Resource Units, Alignment (Education), Electronic Learning, Educational Principles, Teacher Attitudes, Educational Technology, Secondary School Teachers, Foreign Countries, Artificial Intelligence |
| Geographic Terms: | Norway |
| DOI: | 10.1007/s10639-025-13636-z |
| ISSN: | 1360-2357 1573-7608 |
| Abstract: | 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. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1491804 |
| Database: | ERIC |
| Abstract: | 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. |
|---|---|
| ISSN: | 1360-2357 1573-7608 |
| DOI: | 10.1007/s10639-025-13636-z |
