“Teaching is basically feeling”: Unpacking EFL Teachers’ perceived emotions and regulatory strategies in AI-Powered L2 speaking and writing skills instruction

Abstract

The integration of Artificial Intelligence (AI) technologies into various aspects of second/foreign language (L2) education is recently gaining an unprecedented attention. However, teacher emotionality in light of using AI tools for teaching specific language skills has remained unaddressed, so far. To fill this void, the present qualitative study aimed to unveil English as a foreign language (EFL) teachers’ perceived AI-induced emotions and associated regulatory strategies used during their L2 speaking and writing instruction. A cohort of 21 Iranian EFL teachers were non-randomly picked up to attend a semi-structured interview and complete a written narrative frame. The results of thematic analysis through MAXQDA software divulged that the participants frequently experienced seven positive emotions including ‘excitement’, ‘confidence’, ‘joy’, ‘pride’, ‘satisfaction’, ‘passion’, and ‘engagement’. On the negative side, ‘anxiety’, ‘worry’, ‘stress’, ‘apprehension’, and ‘frustration’ were repeatedly induced by AI tools in L2 speaking and writing classes. Moreover, it was found that four ‘up-regulating’ and five ‘down-regulating’ strategies, either antecedent-focused or response-focused had been commonly employed by the teachers to manage their positive and negative AI-induced emotions. A discussion of the findings and practical implications for considering teacher emotionality when integrating AI technologies into L2 productive skills is provided.