Affect and learning: An exploratory look into the role of affect in learning with AutoTutor
Abstract
The role that affective states play in learning was investigated from the perspective of a constructivist learning framework. We observed six different affect states (frustration, boredom, flow, confusion, eureka and neutral) that potentially occur during the process of learning introductory computer literacy with AutoTutor, an intelligent tutoring system with tutorial dialogue in natural language. Observational analyses revealed significant relationships between learning and the affective states of boredom, flow and confusion. The positive correlation between confusion and learning is consistent with a model that assumes that cognitive disequilibrium is one precursor to deep learning. The findings that learning correlates negatively with boredom and positively with flow are consistent with predictions from Csikszentmihalyi's analysis of flow experiences.
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A current trend in AIEd is that systems typically notify teachers directly.
“a preference that runs counter to a current trend in AIEd where systems typically notify teachers directly (e.g., [31, 62]).”
From AI Sensing and Intervention in Higher Education: Student Perceptions of Learning Impacts, Affective Responses, and Ethical Priorities (2026) · cites this paper as [31]
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“…Assistance : Teacher-facing systems [61, 82] can provide insight about individual students or class-wide progress, such as who is struggling or disengaged [123], enabling teachers to adjust instruction [6, 7, 42, 48], target their attention [62] and offer timely support [31, 62, 64, 136].”
- Authors
- Craig, S., Graesser, A., Sullins, J., & Gholson, B.
- Affiliations
- University of Memphis (US)
- Venue
- Journal of Educational Media
- Publisher
- Informa UK Limited
- Published
- 2004-10
- Volume
- 29
- Issue
- 3
- Pages
- 241-250
- ISSN
- 0260-7417 (ISSN-L)
- 1358-1651
- OpenAlex
- W2117342357
- Cited by
- 630
- References
- 2
- Citations by year
- 2026: 12 · 2025: 35 · 2024: 19 · 2023: 25 · 2022: 25 · 2021: 46 · 2020: 32 · 2019: 37 · 2018: 29 · 2017: 30 · 2016: 32 · 2015: 45 · 2014: 40 · 2013: 50 · 2012: 37
- FWCI
- 10.14
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Educational Television (publishedVersion)
- Funders
- National Science Foundation
- U.S. Department of Defense
- Multidisciplinary University Research Initiative
- Office of Naval Research
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Social Sciences › Psychology › Developmental and Educational Psychology › Innovative Teaching and Learning Methods
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Visual and Cognitive Learning Processes
- Keywords
- affective states, learning, AutoTutor, intelligent tutoring systems, flow experience, boredom, confusion, frustration, cognitive disequilibrium, deep learning, computer literacy, constructivist learning
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