Collaborative testing shows the taxonomy enables comparison between similar GenAI activities while inevitably falling short of portraying all entangled aspects¶

Claim · All claims
Evidence · 1 study (2 entries) · design r2 · q1–q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q2 i? Taxonomic representation across five examples revealed clear differences between apparently similar activities (Examples 1 and 2) regarding teacher pre-configuring of GenAI and student reflection on GenAI decision-making. → Dohn 2026 q1 i? The taxonomy as an epistemic form is designed to represent hierarchical structures and is not designed to capture more complex relationships such as iterative, entangled engagement. → Dohn 2026 (2)

Evidence¶

Dohn 2026¶

Dohn, N. B., Markauskaite, L., Huber, E., Wardak, D., Yang, H., Zeivots, S., Casey, A., van Diggele, C., Dohn, N. B., Mannix, K., Mantai, L., Pressick-Kilborn, K., Spence, N., Vallis, C., & Wilson, S. (2026). Collaborative Making of a Boundary Object for Classifying Generative AI Learning Activities. Postdigital Science and Education. https://doi.org/10.1007/s42438-026-00671-3

q2 · i? · design · r2

Multi-group dialogic testing of the taxonomy against five concrete GenAI learning activity examples during a collaborative workshop, followed by written dialogue. Representing all five examples diagrammatically showed that "the clear difference between the two apparently similar learning activities" concerned teacher pre-configuring and student reflection.

"Representing all examples (Figs. 3, 4, 5, 6, 7) thus shows the clear difference between the two apparently similar learning activities in Examples 1 and 2, as regards teacher pre-configuring of GenAI and student reflection on GenAI decision-making."

Dohn 2026 (2)¶

Dohn, N. B., Markauskaite, L., Huber, E., Wardak, D., Yang, H., Zeivots, S., Casey, A., van Diggele, C., Dohn, N. B., Mannix, K., Mantai, L., Pressick-Kilborn, K., Spence, N., Vallis, C., & Wilson, S. (2026). Collaborative Making of a Boundary Object for Classifying Generative AI Learning Activities. Postdigital Science and Education. https://doi.org/10.1007/s42438-026-00671-3

q1 · i? · design · r2

Authors' theoretical reflection during the postdigital dialogue on the affordances and limits of the taxonomy as an epistemic form. The taxonomy's left-to-right hierarchical layout "is not designed to capture more complex relationships" such as the recursive, iterative engagement observed in Examples 1 and 2. They suggest a circular or wheel structure as an alternative.

"A taxonomy, as an epistemic form, is designed to represent a hierarchical struc- ture and hierarchical relationships between its elements; it is not designed to cap- ture more complex relationships."

Discussion¶

Beyond describing existing activities, the authors also used the taxonomy as a prompt to design new GenAI activities.

Related Claims¶

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• Assistant and Enabler entanglements dominate GenAI-in-higher-education research, each accounting for 42.16% of a 102-study corpus, while Synthesizer, Reimaginator, and Generator together constitute less than one fifth — related
• The marginality of Generator, Reimaginator, and Synthesizer entanglements reflects institutional accommodation of individualistic competence expectations rather than technological limitation — related
• Cognitive partnerships with AI enable students to engage in theoretical and empirical reflection that the authors characterize as genuinely novel epistemic practices — related