Profiling learners' affective engagement: Emotion AI, intercultural pragmatics, and language learning
arXiv:2603.20479v2 Announce Type: replace-cross Abstract: Learning another language can be a highly emotional process, typically characterized by numerous frustrations and triumphs, big and small. For most learners, language learning does not follow a linear, predictable path, its zigzag course shaped by motivational (or demotivating) variables such as personal characteristics, teacher/peer relationships, learning materials, and dreams of a future L2 (second language) self. While some aspects of language learning (reading, grammar) are relatively mechanical, others can be stressful and unpredi
The proliferation of advanced AI capabilities, particularly in emotion recognition and natural language processing, is enabling novel applications in personalized education and second language acquisition.
This research highlights specific applications of AI that can personalize and enhance human learning experiences, making education more adaptive and effective.
The explicit profiling of learners' affective engagement using AI will allow for more tailored and responsive language learning methodologies, moving beyond traditional, less individualized approaches.
- · AI in education companies
- · Language learners
- · Educational technology providers
- · Psychology and linguistics researchers
- · Traditional language learning platforms
- · One-size-fits-all educational content providers
AI-powered language learning apps will integrate sophisticated emotion recognition to provide real-time feedback and adapt curricula.
The data collected on affective states in learning could lead to new pedagogical theories and more effective educational interventions across various subjects.
Ethical considerations around data privacy and the potential for manipulation through emotion AI in education will become a significant regulatory and societal debate.
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