AI Insight
This 14-week longitudinal study examined how three Chinese EFL learners' emotional engagement evolved during a GenAI-assisted writing course, revealing three distinct trajectories: positive-resilient (sustained positive emotions), pragmatic-transformative (shift from disengagement to critical engagement), and vulnerable-contingent (progressive disengagement leading to breakdown). These emotional trajectories were shaped by individual factors like English proficiency and GenAI literacy, as well as environmental factors including task design, peer/teacher support, and institutional policies. The findings demonstrate that emotional engagement with GenAI writing tools is highly variable and influenced by the complex interplay between learner characteristics and contextual conditions.
Why it matters
The study challenges assumptions that GenAI uniformly benefits all language learners and highlights the need for differentiated teaching approaches that account for individual emotional responses. These findings have practical implications for designing GenAI-integrated writing curricula that provide appropriate scaffolding based on students' proficiency levels, technological literacy, and emotional needs.
Understand the Science
IntroductionGenerative artificial intelligence (GenAI) has reshaped EFL writing education, yet the emotional dimensions of student engagement in GenAI-assisted writing remain underexplored. This longitudinal multiple-case study investigates how Chinese EFL learners’ emotional engagement evolves during a GenAI-assisted college writing course and what factors drive this evolution.MethodsDrawing on the sociocultural framework of L2 student engagement with written feedback, we traced the emotional trajectories of three focal students across three writing tasks (exposition, group feature article, and argumentation) within a 14-week course. Data were collected through semi-structured interviews with stimulated recall, reflective reports, GenAI-student chatlogs, drafts, informal chats, and course syllabus, and analyzed via thematic analysis.ResultsOur findings reveal three qualitatively distinct trajectories: positive-resilient, characterized by sustained positive affect with temporary fluctuations; pragmatic-transformative, marked by a gradual shift from practical disengagement to critical engagement; and vulnerable-contingent, moving from moderate disengagement, through tentative peer-mediated improvement, to eventual breakdown and intensified disengagement. These trajectories were shaped by the dialectical interplay between individual factors (e.g., English proficiency, GenAI literacy, mindsets, beliefs, and emotion regulation) and environmental factors (GenAI-relevant task design, peer and teacher mediation, and institutional policies).DiscussionThe study extends the sociocultural framework by identifying English proficiency and GenAI literacy as critical developmental competencies, embedding GenAI-related factors across multiple environmental levels, and foregrounding emotional engagement as a dynamic, fluid state that interacts with behavioral and cognitive engagement over time. The findings challenge universalist claims about GenAI’s uniform affective benefits and underscore the need for differentiated pedagogical approaches that attend to learners’ diverse emotional needs in GenAI-mediated writing contexts.