Technology Gap and Research Burnout Among China’s Foreign Language Teachers: A Constructivist Grounded Analysis
DOI:
https://doi.org/10.67148/fahss-2026-258Keywords:
technology gap; technology anxiety; self-efficacy; learned helplessness; burnout; technology acceptance; foreign language teachers; constructivist grounded theoryAbstract
The rapid diffusion of frontier artificial intelligence agent tools, such as Codex, OpenClaw, and Claude Code, has been accompanied by a celebratory discourse of low-threshold empowerment. Yet for many foreign language (FL) teachers in humanities-oriented disciplines, this discourse sits uneasily alongside a widening gap between the tools showcased at the research frontier and the web-based AI applications they actually use. This study examines how FL teachers subjectively construct the experience of a technology gap and how that construction travels, through psychological mechanisms, into research burnout. The author adopted a constructivist grounded theory approach, conducting 31 in-depth interviews with FL faculty across six Chinese universities varying in rank, region, and disciplinary orientation. Data were analyzed through open, axial, and selective coding with constant comparison and memoing, and theoretical saturation was reached after the 27th interview. The core category that emerged was a downward spiral from technology gap perception to research burnout, mediated by two mutually reinforcing psychological mechanisms: technology threshold anxiety and efficacy collapse. Disciplinary mismatch perception and upward social comparison amplified the threat appraisal, while defensive rationalization and surface coping served as short-term emotion-regulation strategies that paradoxically deepened long-term helplessness. A counter-pathway of efficacy repair, anchored in mastery experiences and contextualized peer support, was also identified. Counterintuitively, AI functioned less as an empowering tool than as a pressure source that intensified existing inequities in research capacity. The findings reframe the prevailing empowerment narrative by foregrounding its psychological costs in low task-technology fit disciplines. The study contributes a process model and a set of indigenous concepts that reposition teacher AI support as a socio-emotional and organizational challenge, not merely a technical training problem.
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