A control–value perspective on the emotional experiences of AI ‐assisted item‐writing EFL teachers in China

Bibliographic Data

ID11159263
AuthorsBo Jin (0009-0006-2808-3946, School of Foreign Studies Jiangnan University Wuxi China), Xinxin Wu (0000-0001-7522-0399, School of Foreign Studies Jiangnan University Wuxi China, corresponding author)
Year2026
Publication date2026-01-02
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueBritish Educational Research Journal (JOURNAL)
Journal identifiersISSN: 0141-1926 • E-ISSN: 1469-3518
PublisherWiley (PUBLISHER • GB)
DOI10.1002/berj.70110
OpenAlexW7118084075
LanguageEN
References cited44

This study examines how English‐as‐a‐foreign‐language (EFL) teachers experience and regulate emotions when integrating generative artificial intelligence (AI) into high‐stakes test development. Drawing on control–value theory, and using a qualitative case study of a university‐wide examination team in China, we analysed interviews, interaction logs and participant observation to show how emotional experiences diverge systematically across organisational roles. The findings identify a structural pattern—termed the emotional funnelling phenomenon—where AI‐related risks and uncertainty concentrate in leadership positions, producing sustained anxiety and, at times, hopelessness. In contrast, technically or creatively oriented roles, structurally insulated from exam‐related accountability, experienced curiosity, enjoyment and a strong sense of control. A different emotional trajectory emerged for the practitioner responsible for reading items, who reported boredom and grievance stemming from the repetitive verification of unreliable AI outputs, compounded by the sense that her labour was undervalued by colleagues and under‐recognised within the institution. Across roles, teachers employed AI‐specific emotion regulation strategies, such as reframing, anthropomorphisation and competence‐oriented role reversal. The study concludes that emotional outcomes in AI adoption are shaped not by the technology itself but by how institutions distribute control, risk and recognition within AI‐mediated workflows

Anxiety · Boredom · Emotional intelligence · Emotional labor · Perspective (graphical) · Qualitative research · Reading (process) · Test (biology) · Test anxiety · AI in Service Interactions · Artificial Intelligence in Healthcare and Education · Ethics and Social Impacts of AI

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