Understanding learners' perceptions of artificial intelligence-mediated Informal Digital Learning of English: A Q methodology approach

Artificial intelligence-mediated informal digital English learning (AI-IDLE) creates new possibilities for language learning beyond the formal classroom. Its core value lies not only in the learning convenience empowered by technology, but also in its potential to meet learners' psychological needs. Analyzing the technology acceptance behavior in AI-IDLE from a psychological perspective involves revealing the formation mechanism of behavioral intention under the interaction of cognitive evaluation, emotional experience, and social influence. This requires moving beyond a surface-level description of tool effectiveness and exploring how individuals construct subjective psychological processes in making technology adoption decisions. This study investigates Chinese university students' perceptions of AI-IDLE by integrating The Extended Unified Theory of Acceptance and Use of Technology (UTAUT2) with Q methodology. A total of 34 students participated in a Q-sort task concerning their experiences with AI-IDLE, followed by retrospective interviews to elicit in-depth reflections. The analysis revealed three primary factors shaping students' engagement with AI-IDLE: (1) Interactive Engagement, (2) A Bipolar Dimension: Digitally Scaffolded Adopters vs. Externally Constrained Skeptics, and (3) Perceived Usefulness and Ease of Use. Factor 1, distinctive in degree and mechanism relative to non-AI technologies, stems from human-computer interaction and highlights the emotional and informational support provided by AI, thereby significantly enhancing learners' positive affective experiences, relational appraisals, and intention to use. Factor 2 encompasses two poles: digitally scaffolded adopters and externally constrained skeptics, emphasizing the role of external support from online communities, teachers, peers, and family, particularly noting the influential role of the digital environment. Factor 3 centers on learners' performance and effort expectancies, recognizing AI as an effective tool for achieving personal learning goals. Furthermore, this study extends the UTAUT2 framework by recontextualizing the construct of Price Value within the educational setting and expanding it into a broader Cost-Value perspective. The findings offer practical implications for both learners and educators seeking to optimize AI-mediated informal English learning.