Paper Type

ERF

Abstract

GenAI tools are transforming how students approach academic work, raising concerns about reduced cognitive engagement. This study introduces the phenomenon of anticipatory cognitive offloading, proposing that students reallocate effort during preparation when they expect AI assistance during assessment. We propose a within-subjects experiment where participants complete repeated study–quiz cycles under AI-assisted and AI-unassisted conditions. Multimodal biometric and behavioral data will be collected to examine whether AI availability shifts attention toward shallow processing, lowers perceived strain and physiological arousal, and differentially affects performance across quiz types. By integrating NeuroIS approach with behavioral data, this research provides process-level evidence on whether generative AI functions as a learning scaffold or a substitute for cognitive engagement.

Paper Number

1767

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Aug 15th, 12:00 AM

Anticipatory Cognitive Offloading with GenAI

GenAI tools are transforming how students approach academic work, raising concerns about reduced cognitive engagement. This study introduces the phenomenon of anticipatory cognitive offloading, proposing that students reallocate effort during preparation when they expect AI assistance during assessment. We propose a within-subjects experiment where participants complete repeated study–quiz cycles under AI-assisted and AI-unassisted conditions. Multimodal biometric and behavioral data will be collected to examine whether AI availability shifts attention toward shallow processing, lowers perceived strain and physiological arousal, and differentially affects performance across quiz types. By integrating NeuroIS approach with behavioral data, this research provides process-level evidence on whether generative AI functions as a learning scaffold or a substitute for cognitive engagement.

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