Exploring the emotional labor of Iranian English language teachers in digital learning environments: A self-determination theory perspective

Abstract

The study explored the emotional labor of Iranian English language teachers in digital learning environments, drawing on Self-Determination Theory (SDT) as the theoretical framework. Emotional labor, encompassing surface acting, deep acting, and naturally felt emotions, is essential for managing interpersonal dynamics in teaching. While emotional labor in traditional classrooms has been extensively studied, its manifestation in online settings remains underexplored. This qualitative study examined how the satisfaction or frustration of basic psychological needs—autonomy, competence, and relatedness—influenced teachers’ emotional regulation strategies during online instruction. Semi-structured interviews were conducted with ten mid-career Iranian English language teachers, and the data were analyzed using thematic analysis. Findings indicated that autonomy enhanced emotional authenticity, with teachers who felt empowered in their teaching methods displaying naturally felt emotions or engaging in deep acting. Competence was a significant determinant of emotional regulation, as teachers with higher technical and pedagogical confidence were more likely to express authentic emotions. Relatedness, though challenging in virtual environments, emerged as crucial for fostering meaningful teacher-student interactions and mitigating emotional dissonance. However, institutional policies and technological constraints often frustrated these psychological needs, compelling teachers to rely on surface acting. The findings underscore the complex interplay between emotional labor and motivation in digital contexts, offering insights into supporting teachers' well-being and enhancing their professional efficacy in online teaching.