The article argues that pairing GenAI-vulnerable assessment formats as twins mitigates validity threats by triangulating evidence¶

Claim · All claims
Evidence · 1 study · theoretical r2 · q1
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

q1 i? The twin approach helps mitigate GenAI validity threats by triangulating evidence across pedagogically valuable, yet GenAI-vulnerable, assessment formats. → Jasper Roe 2026

Evidence¶

Jasper Roe 2026¶

Jasper Roe, Mike Perkins, Louie Giray. (2026). Assessment twins: An approach for strengthening assessment validity in the age of generative AI. Journal of Applied Learning and Teaching, 9(2). https://doi.org/10.37074/jalt.2026.9.2.3

q1 · i? · theoretical · r2

This is the article's own conceptual argument, not an empirical test: the authors explain how triangulation across twin tasks mitigates validity threats. The article offers no data; the support is the theoretical rationale itself, described as "triangulating evidence across pedagogically valuable, yet GenAI-vulnerable, assessment formats".

"We explain how the twin approach helps mitigate validity threats by triangulating evidence across pedagogically valuable, yet GenAI-vulnerable, assessment formats."

Discussion¶

Related Claims¶

• Proposition 4: evidence gathered through distinct demands supports capability claims better than multiple records of the same performance — the general claim this finding bears on, with the studies behind it
• The article reports a relative lack of literature detailing practical approaches to GenAI-driven assessment redesign — related