AI expectation violations and learner engagement in EFL contexts: a cognitive-affective recovery model
Jiawen Yu1,2, Xianyan Dai3,4, Baoyu Qiu5
1School of Foreign Languages, Nanfang College, Guangzhou, Guangdong, China.
Frontiers in Psychology
|February 23, 2026
Summary
When artificial intelligence (AI) in English-as-a-foreign-language (EFL) education fails learner expectations, engagement drops. However, AI adaptivity, cognitive reappraisal, and trust recovery can help learners persist.
Area of Science:
- Educational Technology
- Artificial Intelligence in Education
- Second Language Acquisition
Background:
- Artificial Intelligence (AI) is widely used in English-as-a-foreign-language (EFL) education for adaptive feedback and personalized learning.
- Research often overlooks learner responses to AI failures and the recovery process, leaving cognitive-affective mechanisms underexplored.
Purpose of the Study:
- To propose and test a cognitive-affective recovery model for learner engagement in AI-supported EFL contexts.
- To investigate how expectation violations impact engagement and the mediating roles of cognitive reappraisal and trust recovery.
- To examine the moderating effect of digital grit on learner persistence after setbacks.
Main Methods:
- A two-wave survey was administered to 298 Chinese EFL learners (university and private institute students).
- Partial Least Squares Structural Equation Modeling (PLS-SEM) was used for data analysis.
- The study integrated Expectation Violation Theory, Cognitive Appraisal Theory, and Digital Divide/Resilience Theory.
Main Results:
- Expectation violations significantly decreased learner engagement.
- Perceived AI adaptivity mitigated the negative impact of expectation violations and initiated recovery.
- Cognitive reappraisal and trust recovery acted as crucial mediators, while digital grit moderated engagement pathways.
Conclusions:
- Learner engagement with AI in EFL is influenced by expectation violations and recovery processes.
- Designing AI systems that are adaptive, foster trust, and promote digital grit is essential for sustained engagement.
- This research highlights the importance of understanding failure and recovery dynamics in AI-learner interactions for equitable language education.
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