Paper Type
ERF
Abstract
As Generative Artificial Intelligence (GenAI) rapidly transforms digital learning environments, understanding how its multimodal affordances modulate cognitive processes has become critical.However, little research has investigated the implicit (automatic or unconscious) determinants of these cognitive states, and more importantly, the potential nonlinear relationships between such implicit antecedents and explicit (perceptual) ones.Addressing this theoretical gap, this paper proposes a novel conceptual framework grounded in the Stimulus-Organism-Response paradigm and Dual-Process Theory.We conceptualize GenAI content characteristics—specifically verisimilitude, vitality, imagination, and synthesis—alongside interaction mechanisms as key environmental stimuli.Crucially, this study theorizes how these stimuli shape both implicit neurophysiological states (learner 'engagement') and explicit perceptual states ('flow'), and how their complex, potentially nonlinear interplay influences the ultimate formation of learning performance.By bridging the gap between multimodal AI inputs and dual-process learning states, this theoretical model provides a vital foundation for future empirical and neuroscientific investigations, offering strategic design principles for next-generation AI-driven educational systems.
Paper Number
1712
Recommended Citation
Wu, Ya-Ling and Chen, Yi-Jhen, "From Unconscious Engagement to Conscious Flow: A Dual-Process Conceptual Framework for Generative AI in Education" (2026). AMCIS 2026 Proceedings. 17.
https://aisel.aisnet.org/amcis2026/sig_ed/sig_ed/17
From Unconscious Engagement to Conscious Flow: A Dual-Process Conceptual Framework for Generative AI in Education
As Generative Artificial Intelligence (GenAI) rapidly transforms digital learning environments, understanding how its multimodal affordances modulate cognitive processes has become critical.However, little research has investigated the implicit (automatic or unconscious) determinants of these cognitive states, and more importantly, the potential nonlinear relationships between such implicit antecedents and explicit (perceptual) ones.Addressing this theoretical gap, this paper proposes a novel conceptual framework grounded in the Stimulus-Organism-Response paradigm and Dual-Process Theory.We conceptualize GenAI content characteristics—specifically verisimilitude, vitality, imagination, and synthesis—alongside interaction mechanisms as key environmental stimuli.Crucially, this study theorizes how these stimuli shape both implicit neurophysiological states (learner 'engagement') and explicit perceptual states ('flow'), and how their complex, potentially nonlinear interplay influences the ultimate formation of learning performance.By bridging the gap between multimodal AI inputs and dual-process learning states, this theoretical model provides a vital foundation for future empirical and neuroscientific investigations, offering strategic design principles for next-generation AI-driven educational systems.
When commenting on articles, please be friendly, welcoming, respectful and abide by the AIS eLibrary Discussion Thread Code of Conduct posted here.
Comments
SIG ED