Editorial

Abstract

What remains when algorithms can design, assess, and respond? This question—posed with quiet urgency in our inaugural Reflective Notes by Alireza Karbalaei—guides many of the articles in this 32nd issue of GiST.

Karbalaei's "The AI Paradox in Teacher Education: When Tools Empower, Do They Erase Expertise?" does not advocate for outright rejection or uncritical acceptance, but rather for what he terms "metacognitive AI literacy": the ability to interrogate, adapt, or disregard algorithmic outputs in light of pedagogical principles and context. The question is not whether to use AI, but how to ensure it scaffolds, rather than supplants, professional judgment.

The first two articles demonstrate AI's genuine promise. "Why Chunks Go Unnoticed: A Longitudinal Study of a ChatGPT-Aided Chunking Approach in EFL Classrooms" reveals that technology-supported instruction can significantly improve lexical awareness. Chunk recognition ability correlated positively with overall English proficiency, suggesting that raising awareness of lexical units has benefits for language development. Similarly, "The Role of Generative AI and Peer Feedback in Cooperative Writing Within a Feedforward Pedagogy" shows that ChatGPT, combined with peer collaboration, enhances writing performance among IELTS candidates. The experimental group demonstrated significant improvements in grammatical accuracy, lexical range, and discourse organization—gains that students themselves perceived as meaningful, noting that peer collaboration reduced anxiety while GenAI feedback provided timely, actionable guidance.

Yet efficiency is not the whole story. "Group Regulation Strategies in Online Synchronous Classes: A Study of Mexican Beginner EFL Learners" illustrates something algorithms cannot pre-design: the emergence of human connection and peer scaffolding. When Mexican A2-level adult learners were placed in Zoom breakout rooms without a teacher present, they spontaneously developed regulation strategies, with laughter and empathy proving nearly as significant as explicit participation-structure regulation. The central question, then, is not whether to use technology, but how to preserve and enhance human judgment within it.

Yet preserving human judgment within technology is not cost-free, and that cost falls disproportionately on those responsible for implementing it: the teachers themselves. The

human cost of excessive technology use is evident in "Teaching English in the Age of Screens: Technostress, Digital Fatigue, and Occupational Well-Being Among ELT Instructors," where the very tools intended to ease workloads can also be sources of exhaustion. Among 472 ELT instructors across Turkish universities, the study revealed that technostress significantly predicts digital fatigue, which in turn undermines occupational well-being—a mediation effect that underscores how institutional expectations around technology adoption can backfire without adequate support.

Focusing narrowly on technological efficiency, however, obscures something equally crucial: the inclusion and sustainability dimensions of learning. In "Inclusive Pathways: Professors' Voices on Fostering Equity at a Mexican University," the authors show how while professors acknowledged that disability and neurodivergence are not impediments to academic study, they faced a critical gap: insufficient knowledge of inclusive teaching strategies and limited institutional resources for creating accessible language classrooms. Meanwhile, "A Content Analysis of Current English Language Teaching Materials at a Private Colombian University Through the Lenses of Sustainable Development Goals (SDGs)" invites us to consider which worldviews are embedded in the materials we use. The authors call for attention to the gap between institutional aspiration and classroom reality. It suggests that the materials teachers use may not reflect the transformative vision that their institutions claim to pursue.

Finally, the corpus-based studies—"Exploring Authorial Stance Devices and Hedging Strategies in Tertiary Level EFL Learner Argumentation" and "A Corpus-based Study of Cohesion through Reference and Conjunctive Ties in IELTS Simulation Essays by Colombian Students"—highlight complex patterns that require situated, culturally informed interpretation. The Colombian corpus study reveals that ESL learners systematically overuse exemplification markers and temporal connectors, while underusing personal pronouns and maintaining a narrower range of reference and conjunctive ties compared to proficient writers. Notably, approximately 90% of overused conjunctive ties appear in sentence-initial position, and 81 instances of misuse in reference ties reflect specific error patterns (syntax, function, punctuation). These are not random mistakes; they reflect comprehensible interlanguage shaped by Spanish L1 transfer and limited exposure to advanced English discourse patterns. Similarly, tertiary learners' hedging strategies—particularly their overuse of should within interactive moves—reveal an emerging authorial stance and metacognitive awareness. Understanding these patterns demands the kind of patient, longitudinal observation that reveals learners' developing competence rather than algorithmic error correction.

These contributions form a coherent narrative about the complexity of contemporary language education. They remind us that innovation—whether technological or pedagogical—succeeds only when it serves learners and teachers, not when it becomes an end in itself. They insist that efficiency must never eclipse the emotional, relational, and

deeply human dimensions of education. And they reveal that teaching remains a practice rooted in judgment, context, and care—capacities that no algorithm can replicate, and that no institution can take for granted.

We thank the authors and peer reviewers whose rigorous scholarship and intellectual honesty make this issue possible. Their dedication enriches our field and challenges us to think more carefully about what teaching requires. We invite scholars from around the world to continue contributing to GiST Journal, whether through research articles, reflective pieces, book reviews, or other forms of scholarly engagement. Your voices are essential as we navigate the evolving landscape of English language education.

We hope you enjoy reading this issue as much as we have enjoyed bringing it together.

Bogotá, 2026

Declaration of Artificial Intelligence Use by Editor

In accordance with GiST's Editorial Policy regarding the use of Artificial Intelligence, the editor declares the following:

Grammarly Pro was used to identify grammatical errors, punctuation inconsistencies, and spelling mistakes. Claude assisted in verifying APA 7th edition compliance for citations and cross-referencing with reference lists. Crossref Similarity Check was employed for plagiarism detection. The average similarity percentage across manuscripts was 8%, consisting of common academic expressions and standard terminology. All AI-generated feedback was manually reviewed by the editor before communicating corrections to authors.

No editorial decisions regarding manuscript acceptance, rejection, or recommendations were influenced by AI tools. AI was used exclusively for language support, formatting verification, plagiarism detection, and technical consistency checks.