Bibliographic Details
| Title: |
Human–machine knowledge building: reconceptualising knowledge building partnerships in the age of artificial intelligence. |
| Authors: |
Falloon, Garry (AUTHOR), Jones, Mellita (AUTHOR) |
| Source: |
Educational Technology Research & Development. Jun2026, Vol. 74 Issue 3, p1653-1668. 16p. |
| Subjects: |
Generative artificial intelligence, Division of labor, Bloom's taxonomy, Collaborative learning, Discourse, Human-computer interaction, Information sharing |
| Abstract: |
Increasingly ubiquitous access to Generative Artificial Intelligence (GenAI) presents many challenges, but also opportunities. The fundamental capacity of GenAI to mimic and augment human cognitive functioning, sets it aside from the myriad of previous technological 'cognitive tool' innovations that have been promoted as supporting human thinking, problem solving and knowledge construction. Indeed, GenAI has the potential to play a far more substantive and interactive role in knowledge building, founded on real-time dialogic discourse between humans and GenAI working in symbiotic knowledge building partnerships. This article draws on Scardamalia and Bereiter's early work on human knowledge building communities and Krathwohl's revision of Bloom's Cognitive Domain, reconceptualising these to theorise how humans and GenAI might partner in processes of collaborative, joint knowledge construction. It presents a unique model identifying three flexible 'Zones', representing different but overlapping components of knowledge building, aligned with Bloom's cognitive dimensions. It identifies a possible 'division of labour' within and across Zones, but argues the primacy of innately human capabilities operating in the Judgement Zone, as crucial to reasoned decision making and accurate knowledge building. The model and its discussion provide new insights into how human-GenAI knowledge building partnerships might be established and sustained. [ABSTRACT FROM AUTHOR] |
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| Database: |
Psychology and Behavioral Sciences Collection |
