Oct 2026· International Journal of TESOL & Education· 0 citations· 53 references
EFL/ESL Teaching and Learning
Abstract
This article explores the role of Artificial Intelligence (AI) in English as a Second Language (ESL) writing, examining whether it fosters autonomy or promotes dependency. Utilizing a qualitative methodology, semi-structured interviews were conducted following a timed writing task with 40 intermediate-level ESL students across three higher education institutions in Oman. Thematic analysis reveals that AI's impact on student autonomy is highly contingent upon its pedagogical application. When utilized strategically for brainstorming and personalized feedback, AI acts as a scaffolding tool that fosters self-directed learning. Conversely, when students rely on AI to generate complete texts or passively correct errors, they experience cognitive offloading, leading to decreased independence. The study emphasizes the need for educators to cultivate digital literacy, promoting an approach that empowers students to use AI as an intellectual partner rather than a cognitive replacement.
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
