Editor’s note: “TIRF Perspectives” is a new publications activity from TIRF. It profiles recent research and developments in English Language Teaching (ELT) in a practical and accessible format. TIRF Perspectives is aimed at parents, teachers, school leaders, and all student advocates who want to review recent educational trends regarding AI in a non-academic way. This piece is authored by Dr. Lana Hiasat (Senior Fellow of the Higher Education Academy, UK).

Where We Are

Walk into many classrooms today and the picture is familiar: overloaded teachers balancing content delivery, endless assessments, new digital tools, and student wellbeing, facing an increasingly complex world. Burnout remains high, with many teachers reporting that they often or always feel exhausted at work. At the same time, learners are more diverse, mobile, and connected than ever, and they expect education to be flexible, relevant, and—most importantly—future-ready.

At Higher Colleges of Technology in Dubai, our Classrooms of Tomorrow project captures the shifts above in teacher responsibilities and student expectations. A classroom is no longer defined only by desks and a whiteboard; it is a physical and virtual network of sustainability projects, wellbeing walks, intercultural exchanges, movement-rich activities, and AI-enabled learning beyond school walls. In this context, AI is moving from novelty to necessity, working alongside teachers as an emerging partner in detailed feedback, personalized learning, and assessment. These shifts are summarized in Infographic 1, where focus areas and priorities for teaching, learning, and assessment are summarized in five points.

Current Issues

The gap between traditional schooling and the fast-changing world outside class has been described as a canyon rather than a crack; incremental changes to teaching approaches are no longer enough. Teachers are expected to adopt new tools and platforms while still being measured by old metrics and high-stakes exams. Our Dubai team’s research in TESOL (Teaching English to Speakers of Other Languages) and higher education reveals a concerning trend: Institutions are returning to paper-based, tightly controlled assessments because of AI-related integrity concerns, even as students’ lives become more digital, multimodal, and hybrid. In ELT, this tension is especially visible in writing and speaking assessment, where teachers must balance academic integrity with the need to support multilingual learners’ developing voice, fluency, and accuracy.

Where We’re Going

Our Classrooms of Tomorrow work points to five converging shifts in TESOL instructional approaches: 1) data-rich assessment, 2) immersive learning, 3) accessibility and flexibility, 4) inclusivity and fairness, and 5) AI as an intelligence partner rather than replacement. Implementing these new approaches involves continuous, low-stakes feedback instead of one-off high-stakes exams; real-world simulations and projects instead of decontextualized paper tests; and students using AI to co-analyze texts, rehearse oral defenses, or explore language patterns while teachers guide framing, ethics, and deeper thinking.

For ELT classrooms, this means using AI for pronunciation practice, draft feedback, vocabulary exploration, and rehearsal of oral tasks, while teachers remain responsible for evaluating interaction, pragmatics, and communicative purposes.

Future-ready classrooms also require future-ready teachers. The essential skills we identify through Classrooms of Tomorrow include technology integration, differentiated instruction, reflective teaching, effective questioning, collaboration, cultural competency, data literacy, and strong communication, which are not replaced by AI but rather are strengthened by it. My recent research in this area further highlights three forms of future intelligence for teacher leaders which include emotional intelligence to build psychological safety and trust, foresight intelligence to read trends and design plausible futures, and ethical intelligence to align AI use with human rights, fairness, and accountability.

In short, as TESOL professionals, we can invite AI to become part of a trusted learning system as one with human agency and oversight, clear guardrails, explainable decisions, and a culture where students learn to write, speak, and think with AI, not for AI. Further suggestions and recommendations are summarized in Infographic 2.

Over to You

The future of classrooms is hybrid: humans and AI working together in spaces that stretch beyond four walls into communities, ecosystems, and digital networks. But hybridity does not mean handing the steering wheel to technology – it means designing systems where emotional intelligence, ethical guardrails, and foresight remain deeply human responsibilities.

In ELT, this means strengthening teachers’ assessment literacy for language skills by designing tasks that capture speaking, listening, reading, and writing in authentic contexts, and using AI to surface patterns in learner language without outsourcing professional judgment. Teachers remain the interpreters of progress, especially for multilingual learners whose development may not align neatly with automated scores or generic rubrics.

Here are some activities you can use with colleagues or in professional learning communities, accompanied by your own photos, charts, or classroom artifacts:

1. Map your ELT classroom of tomorrow. Which elements of your teaching—movement, wellbeing, sustainability, community engagement, AI use—need more intentional design?
2. Audit your AI trust architecture. Where is AI already present in your ELT assessment and feedback? Who has oversight? What explanations do students receive? Which ethical frameworks (e.g., EU Trustworthy AI, UNESCO 2021) guide your decisions?
3. Reimagine one assessment. Take one existing paper-based or high-stakes task and redesign it as a continuous, immersive, or performance-based experience, with AI supporting feedback and reflection rather than replacing judgement.
4. Practice shared pain and shared agency. When you notice AI in student work, pause to ask what barrier they were trying to overcome and how you might help them use AI with more agency, responsibility, and creativity.
5. Design an ELT-specific AI learning sequence. Choose one language skill or sub-skill (e.g., academic writing introductions, presentation signposting). Map a short sequence in which students use AI for practice or feedback (e.g., drafting, rehearsing, getting formative comments) and use AI analytics or logs to inform your next teaching move, while keeping final evaluation and grading under human control.

The future is not a distant horizon; it is already walking into our classrooms in the form of new tools, new learners, and new expectations. The question is not whether we blend AI with human instruction, but how intentionally we design that blend.

Over to you: What will you prototype in your classroom of tomorrow this term?

Author’s Bio

Dr. Lana Hiasat, EdD, SFHEA, is a Senior Lecturer in Applied Media specializing in educational leadership, educational technology, future foresight, AI, emotional intelligence, and intercultural intelligence. A certified Future Foresight Trainer (TFSX, USA), she has published extensively and led major research initiatives on future-ready education, classrooms of tomorrow, and global citizenship. She is a recipient of the HCT Teaching Excellence Award (2024), SEE Global Sustainability Summit Best Academic Research Paper Award (2025), TESOL International’s prestigious 30@30 Award (2026), and recently the Global Engagement Award (2026).