AI-assisted data literacy benefits from a cognitive alignment framework that maps AI modes (transmissive or deliberative) to user demands (receptive or deliberative) to reduce passivity and friction.
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4 Pith papers cite this work. Polarity classification is still indexing.
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Trust-driven routine use of generative AI is linked to reduced cognitive engagement in STEM students, with higher technophilic traits increasing vulnerability.
Student-facilitated workshops in one design class produced AI policies highlighting double standards in disclosure requirements between students and faculty, demonstrating value in participatory governance.
AI safety literature overlooks cognitive deskilling and addiction risks from generative AI despite public concern about them.
citing papers explorer
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Disrupting Cognitive Passivity: Rethinking AI-Assisted Data Literacy through Cognitive Alignment
AI-assisted data literacy benefits from a cognitive alignment framework that maps AI modes (transmissive or deliberative) to user demands (receptive or deliberative) to reduce passivity and friction.
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Thinking Less, Trusting More: GenAI's Impacts on Students' Cognitive Habits
Trust-driven routine use of generative AI is linked to reduced cognitive engagement in STEM students, with higher technophilic traits increasing vulnerability.
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Participatory, not Punitive: Student-Driven AI Policy Recommendations in a Design Classroom
Student-facilitated workshops in one design class produced AI policies highlighting double standards in disclosure requirements between students and faculty, demonstrating value in participatory governance.
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Brainrot: Deskilling and Addiction are Overlooked AI Risks
AI safety literature overlooks cognitive deskilling and addiction risks from generative AI despite public concern about them.