Sep 2026· International Journal of TESOL Studies· 0 citations· 78 references
TL;DR
The study proposes the “ Emotion-Identity-Agency Nexus in Flux,” a non-linear model illustrating how macro-political forces are filtered through teachers’ emotional and identity resources, shaping whether agency manifests as adaptation, compliance, or resistance.
Abstract
This qualitative multiple case study follows two EAP teachers: one novice and one experienced over 24 months to explore how they enacted professional agency during significant educational reforms at a Sino-British university in China. The study is situated within a context of “flux and transformation” , a period marked by the cancellation of Year 2 EAP courses and the rapid integration of Generative Artificial Intelligence (GenAI). The study traced the co-evolution of emotions, identity negotiations, and agentive actions over 24 months (2023–2025) using critical reflective narratives, semi-structured interviews, and informal communication logs. The findings reveal that agency is jointly mediated by emotion and identity. The experienced teacher demonstrated adaptive agency, reframing anxiety as a catalyst for professional growth and constructively integrating the teacher-researcher identity. In contrast, the novice teacher exhibited strategic compliance coupled with internal resistance, as negative emotional turbulence and identity fragmentation blocked meaningful identity negotiation. The study proposes the “ Emotion-Identity-Agency Nexus in Flux ,” a non-linear model illustrating how macro-political forces (e.g. neoliberal Key Performance Indexes (KPIs), curriculum cuts, GenAI disruption) are filtered through teachers’ emotional and identity resources, shaping whether agency manifests as adaptation, compliance, or resistance. Our findings point to the need for emotional scaffolding for novice teachers, differentiated performance evaluation policies, and a reconceptualization of the teacher-researcher role in EMI contexts.
This paper investigates developing real-world perception for active agents, proposes Gibson Environment for this purpose, and showcases a set of perceptual tasks learned therein.
F. Xia, Amir Zamir, Zhi-Yang He et al.· 2018 IEEE/CVF Conference on...· 1,069 citations· ⚡112
GAOKAO-Bench is introduced, an intuitive benchmark that employs questions from the Chinese GAOKAO examination as test samples, including both subjective and objective questions that contribute a robust evaluation benchmark for future large language models and offers valuable insights into the advantages and limitations...
Xiaotian Zhang, Chun-yan Li, Yi Zong et al.· arXiv.org· 216 citations· ⚡17
An algorithm is proposed which leverages disentangled semantic factors to generate adversarial perturbation by altering controlled semantic attributes to fool the learner towards various "adversarial" targets.
Haonan Qiu, Chaowei Xiao, Lei Yang et al.· arXiv.org· 208 citations· ⚡17
This work proposes a HALO that directly maximizes the utility of generations instead of maximizing the log-likelihood of preferences, and suggests that the best loss depends on the inductive biases most appropriate for a given setting, an oft-overlooked consideration.
This work investigates the possibilities of using LLMs in a resume screening setting via a document retrieval framework that simulates job candidate selection and finds that the MTEs are biased, significantly favoring White-associated names in 85% of cases and female-associated names in only 11.1% of cases.
This work shows that orders of magnitude enhancement in performance could be obtained by a combination of hardware improvements and tight quantum-HPC integration and introduces high-performance architectures for quantum-probabilistic computing with custom-designed accelerators to tackle today's industry-scale classical...
Masoud Mohseni, Artur Scherer, K. Johnson et al.· arXiv.org· 121 citations· ⚡9