Volume 3,Issue 9
Social Psychological Perspective on Affective Mediation in AI-Enhanced College English Teaching: Impacts on Learning Motivation, Attitude, and Academic Achievement
Driven by the deep integration of artificial intelligence (AI) and education, foreign language teaching is undergoing a profound transformation, with affective factors remaining core mediators in second language acquisition (SLA). Based on questionnaire data from 212 first-year undergraduates and a mixed research method combining quasi-experiment and semi-structured interviews, this study constructs an AI-enhanced college English teaching model integrated with affective mediation from a social psychological perspective, and verifies its impacts on students’ learning motivation, learning attitude, and academic achievement. Key findings include: (1) The experimental group adopting the integrated model achieved significantly higher scores in learning motivation (M=74.28, SD=7.46), learning attitude (M=76.52, SD=6.89), and academic achievement (M=82.30, SD=5.60) than the control group (p<0.001), with large effect sizes (Cohen’s d>2.30); (2) Affective factors played a partial mediating role between AI-enhanced teaching and academic achievement (mediation effect=0.35, p<0.001), accounting for 53.8% of the total effect; (3) Students’ perceptions confirmed that AI tools (e.g., affective computing systems, ChatGPT-4o) reduced learning anxiety, while teacher-led affective mediation activities (e.g., "ideal L2 self" construction) enhanced intrinsic motivation. A four-dimensional implementation framework centered on "emotional diagnosis—AI support—teacher mediation—effect evaluation" is proposed to provide actionable guidance for curriculum reform in application-oriented universities’ English teaching, catering to the diverse needs of foreign language talents in multiple international contexts.
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