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Updated: Apr 28, 2026

Virtual Agent for Real-Time Motivational Interviewing by Integrating Adaptive Nonverbal Behavior and Language Models
Published on: December 23, 2025
Integrating appreciative education with AI-assisted oral training for sustainable EFL learning: a study on speaking
Fangli Zhang1, Meng Yang2,3
1Luoyang Normal University, Luoyang, China.
Background:
Foreign language speaking anxiety constitutes a persistent barrier to oral proficiency development among Chinese college students; however, prevailing technology-centered instructional approaches inadequately address learners' affective needs, thereby limiting their effectiveness in alleviating anxiety and fostering intrinsic motivation. This study proposed a blended pedagogical model-the "Praise-Speak" program that integrates offline appreciative education with AI-assisted oral training via the FIF platform.
Methods:
A two-phase mixed-methods design was employed. In the first phase, large-scale surveys (n = 1,044 for anxiety assessment; n = 209 for appreciative education needs) identified freshmen as the priority intervention cohort. In the second phase, a 16-week pilot intervention was conducted with 13 participants, utilizing a pretest-posttest design supplemented by reflective journal analysis.
Results:
The findings demonstrated statistically significant improvements in IELTS speaking scores (p = 0.005) and a marked reduction in speaking anxiety (p < 0.001). Qualitative analysis revealed three core mechanisms underlying these outcomes: the establishment of psychological safety, positive receptivity to appreciative pedagogy, and technology-humanism synergy.
Conclusion:
This study offers a replicable pedagogical framework that harmonizes technological empowerment with humanistic care, contributing to the realization of the United Nations Sustainable Development Goal 4.
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