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Description
When AI can produce the output, the output stops being the point. This research examines how Japanese university EFL students use generative AI, what this reveals about gaps in educational design, and how a neuroscience-informed Intention–Action–Reflection framework develops the metacognitive, ethical, and communicative capacities that AI cannot replicate.
Abstract section 4: Outcomes/results
Surveys (n = 45) found 89% of students considered AI translation acceptable; only 18% considered submitting AI-generated paragraphs acceptable, yet 41% admitted doing so — a gap between stated ethics and actual behavior driven by assessment design, not moral failure. Submission analysis identified two patterns: reflective iteration, where AI scaffolds student-owned thinking, and mechanical substitution, where AI replaces it entirely. Students practicing communication exclusively with AI showed measurable deficits in live intercultural interaction. The Intention–Action–Reflection protocol, implemented across three courses, increased metacognitive engagement and reduced mechanical AI use, suggesting process-oriented assessment is prerequisite to responsible AI integration.
Abstract section 3: Content/method
Findings were interpreted through neuroscience frameworks on stress and learning, and a taxonomy of AI-resistant human capacities drawn from comparative institutional analysis of global AI literacy policy responses.
Abstract section 5: References
Lavigne, A. (2026). AI literacy in higher education: Classroom realities and global frameworks from a Japanese perspective. Doshisha Global and Regional Studies Review, 25–26, 1–39.
Lavigne, A. (2025). Higher education and the challenge of superintelligent AI: Adaptability, alignment, and agency [Manuscript submitted for publication]. Doshisha University.
Long, D., & Magerko, B. (2020). What is AI literacy? Competencies and design considerations. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1–16.
Lupien, S. J., McEwen, B. S., Gunnar, M. R., & Heim, C. (2009). Effects of stress throughout the lifespan on the brain, behaviour and cognition. Nature Reviews Neuroscience, 10(6), 434–445.
Vogel, S., & Schwabe, L. (2016). Learning and memory under stress: Implications for the classroom. NPJ Science of Learning, 1, Article 16011.
Abstract section 1: Relevance
Japanese university students adopt generative AI rapidly, yet institutional responses focus on prohibition rather than pedagogy. Neuroscience research demonstrates that stress hormones impair hippocampal memory consolidation and prefrontal cortex function, reducing higher-order thinking (Lupien et al., 2009; Vogel & Schwabe, 2016). When assessment prioritizes output — a condition AI now satisfies on students' behalf — learning environments inadvertently optimize against the cognitive processes education is designed to develop (Lavigne, 2025a; Long & Magerko, 2020).
Abstract section 2: Contribution/research questions
This research investigated: How do generative AI use patterns among Japanese university EFL students reveal gaps in educational design, and how can a neuroscience-informed pedagogical framework develop AI-resistant human capacities — metacognition, ethical reasoning, and authentic communicative judgment — that generative AI cannot replicate?
| Title | AI-Resistant Capacities in Japanese University EFL |
|---|---|
| Teaching Context | College and university education |