IATEFL Brighton 2026 - Day 3

How-to session by Sarah Mercer
How to make research part of my professional practice

Despite the existing power structure in academic discourse, Sarah Mercer (University of Graz, Austria) argues that academic research should not be viewed as superior to informal classroom research. Her key message is that there are different types of research—in the sense of finding out information—for different purposes as well as audiences.

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Plenary session by Larisa Kasumagić-Kafedžić
Reimagining language education for peace in our divided world

In today’s plenary session, Larisa Kasumagić-Kafedžić recalls her harrowing experiences of living through the Bosnian War (1992–95), part of the Yugoslav Wars, as a result of the breakup of the multi-ethnic Federation of Yugoslavia in the 1990s. As an eighteen-year-old in a war-torn country, she began to explore the role of language in promoting peace.

She outlines the key transitions in the Western Balkans since the end of ethnic conflicts:

• Political-ideological: from war to peace and towards internationalisation
• Socio-cultural: cohesion achieved in some newly independent countries but ethnic division remains in other former Yugoslavian states
• Structural and educational policies
• Peace pedagocial: moving on from being stuck in the past

Nevertheless, she laments that the Yugoslav Wars are still taught from an institutional perspective as this topic remains an integral part of the curriculum. She argues that little has been done to focus on the individual experiences during the conflicts.

At the same time, she cautions against the emphasis on STEM subjects at the expense of the humanities. This has led to challenges in our ability to tackle divisive rhetoric in political and social discourses. She points out that language is often weaponised to marginalise or dehumanise certain groups of people. Toxic narratives, moreover, continue to be driven by those with power; such narratives are insufficiently challenged and have been a precursor to physical violence as history teaches us.

She advocates that education holds the key to tackling the above challenges. For example, teachers can highlight the political dimension of language. Research bodies can adopt a pluralistic approach to epistemology where justified, rather than draw exclusively on Western epistemic knowledge. She further argues that pluralism should not be promoted solely for its economic benefits, such as profitability and employability.

On peace education, she describes how it has been implemented across the Western Balkans. Institutions collaborate with each other in the form of “peace hubs”, in order to develop frameworks for embedding peace pedagogy in education. Based on her examples, she illustrates that the pedagogies for peace education are compatible with content-based or topic-based instruction. In the context of higher education, learners are encouraged to discuss and reflect on how people can embrace a culture of peacemaking.

Finally, she outlines the critical roles of language teachers. While some teachers have faced dilemmas as to whether they should include sensitive topics or discuss controversial views in the classroom, they try to remain neutral in the classroom. She also mentions that learners can be encouraged to reflect on their attitudes towards discussing sensitive or controversial topics, i.e. whether they remain an “avoider” on one end or a “risk taker” on the other end.

She concludes her talk with Hadley’s (2018) powerful quote: “we live in a world where peace is unprofitable.”

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Talk by Anna Wierstra
Challenging teacher training trainees: Raising their awareness, targeted feedback and staying sane

Anna Wierstra (International House Rome) recalls her experience of dealing with an extremely challenging teacher trainee on her intensive CELTA course. She supported this trainee by planning lessons with her collaboratively, giving her extensive spoken feedback, and using colour coding in written feedback. Despite her overwhelming support, the teacher trainee showed little evidence of progress.

Her discussion is based on Rosenberg’s book Nonviolent Communication. She mentions four ways in which teacher trainees may react to negative feedback, such as self-blaming, shifting the blame, and reacting defensively. When moral judgements are included in the trainer’s feedback, it causes the trainees to become resistant to ideas immediately. To this end, teacher trainers should avoid making sweeping generalisations in their feedback, e.g. you never, you always, don’t do this, etc.

She suggests that teacher trainers can facilitate trainees’ self-reflection by encouraging them to mention how they felt at a particular point of a lesson and by posing ‘why’-questions. Two other useful techniques are eliciting the trainees’ self-reflection and checking the trainees’ understanding by summarising the trainer’s feedback.

Finally, she brings up the issue of negative self-talk among teacher trainees. This is usually revealed by language expressions such as I should (have) and I have to. To steer the trainees away from a negative mindset, she provides sentence frames in the trainees’ self-evaluation form, e.g. I choose to do ____ because I want my students to ____.

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Talk by Christiane Lauschitzky
Beyond language didactics: Tapping hidden research for ESP and EAP teaching

Christiane Lauschitzky (FH Technikum Wien, Austria) shares her experience of using journal articles and academic papers from other fields in ESP teaching. As an ESP tutor of university students, her primary concern is how she can help them to develop the ability to express their specialised knowledge in English.

She mentions that elicit.com is a useful AI-powered website that helps academics to find relevant research papers.

To prepare the source texts for use in the classroom, she uses a jigsaw method that shares similarities with Tyson Seburn’s Academic Reading Circles (2016). Christiane Lauschitzky’s method represents a cooperative learning strategy that involves each student acting as the “expert” of a specific aspect of the text, e.g. a physical section or specific type of content within the text.

To go further, when the learners present their findings, they not only summarise the ideas in the source text but also add their personal take on it.

IATEFL Brighton 2026 - Day 2

Plenary session by Danny Norrington-Davies and Richard Chinn
Emergent language: How we see it and what it can be

In today’s plenary session, Danny Norrtington-Davies and Richard Chinn introduce emergent language and share some updates on their latest insights.

They begin by mentioning the theoretical influence on their teaching: Scott Thorbury and Luke Medding’s Teaching Unplugged (2009). This is manifested in three tenets of teaching: conversation-driven, materials-light, and focus on emergent language.

Danny Norrtington-Davies and Richard Chinn define emergent language as any unplanned language that is needed or produced by the learners in meaning-focused interactions. Some examples of such language are errors, communication breakdowns, unclear expressions, and extension (e.g. excellent word choice, appropriate style, etc.). Emergent language need not always contain negative examples, but it is by no means part of the target language of a lesson.

They move on to suggest some criteria that teachers can use to prioritise certain kinds of emergent language. These include communication breakdowns, language or interaction skills related to the teaching context, repetitive mistakes, high-frequency expressions, task-specific language, and language that is judged to be new, interesting or useful to the learners.

To find out what emergent language means across various teaching and learning contexts, Danny Norrington-Davies and Richard Chinn spoke with a cohort of teachers. They shared the main themes in their findings:

• Teachers can create the conditions for language to emerge in meaningful interactions by extending lead-in discussions, using personal response questions, and asking open-ended follow-up questions.
  
  
• Teachers can use communicative tasks that do not specify any target language as it otherwise limits the room for focussing on emergent language.
  
  
• Topics that lie beyond a prescribed textbook syllabus can create the conditions for language to emerge.

Teachers can adopt the view of their role as helping learners to express their ideas effectively in their own ways, rather than trying to elicit what learners are expected to say according to the syllabus. Nevertheless, it does not necessarily mean a lack of consideration of the complexity of language for the learners.

They also mentioned some of the challenges that the teachers had faced when dealing with emergent language, such as different learning backgrounds or clashing beliefs about teacher and learner roles. Some learners may feel embarrassed to speak, whereas others adopt a defensive or confrontational attitude towards feedback as they see it as an affront to them.

Finally, Danny Norrington-Davies and Richard Chinn share an update on the practice of dealing with emergent language. They see it as a fluid concept that may contain different kinds of language depending on the specific classroom context. What is crucial, however, is the idea of eliciting the learners’ intended meaning by the words they have chosen to use. When dealing with emergent language, teachers are encouraged to develop their reactive skills [or responsive teaching skills] by reflecting on their own beliefs, on whether meaning has genuinely been explored, and on feedback from the learners on their learning.

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Talk by Shaun Wilden
Unseen insight: Teacher reflection with AI mentoring

Shaun Wilden (IATEFL Vice-President) traces back to the reflective practice of journalling as the starting point of his experiment with artificial intelligence (AI). In his experiment, he uses AI tools as a partner or collaborator to aid the teacher in the process of self-reflection.

He uses Gibb’s Reflective Cycle to inform his experiment. The assumption is that ChatGPT has a comprehensive knowledge of English Language Teaching (ELT) theories as well as a thorough understanding of practices.

The two pillars of his experiment are AI mentoring and narrative self-reflection. This is also compatible with self-observation, which is especially useful for teachers working in contexts without organisational or mentoring support. Before teachers use ChatGPT, they need the following data:

• Detailed description of their classroom context [role]
  (e.g. You are an English for Academic Purposes tutor teaching a university-level pre-sessional class.)
  
  
• Transcript of the recorded lesson, with any sensitive information about the teacher and the students removed. For example, each student can be labelled anonymously with a letter or number.
  
  
• Teacher’s self-evaluation or journal entry of the lesson

The following steps are followed in the evaluation process:

1. The teacher asks ChatGPT a (Socratic) question about the main learning aim of the lesson.
2. The teacher asks ChatGPT another (Socratic) question about what it thinks the self-observation aim is.
3. After ensuring that ChatGPT aligns with the teacher in their idea about the aims, the AI chatbot is asked to act as a lesson observer. It should analyse both the transcript and the teacher’s self-evaluation or journal entry.
4. The teacher compares their own self-evaluation (what is thought to have happened) to ChatGPT’s observations (what actually happened).

Shaun Wilden concludes by suggesting that while ChatGPT can draw teachers’ attention to some overlooked aspects of the lesson, it remains a mirror of the teacher’s input, rather than a collaborator in its true sense. Nevertheless, there is still value in the teacher receiving non-judgmental feedback from ChatGPT. As most formal observations tend to happen once a year, ChatGPT can provide a sense of continuity in teachers’ self-observation journeys.

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Talk by Chris Lewis
Belief and growth: Acknowledging principles in teacher development

Chris Lewis (EC English) invites the audience to consider why some teachers flourish in their professional development, while others seem to be resistant to growth.

He draws on Simon Sinek’s work, which centres around the ‘why’ behind what one decides to do. Although the ‘what’ and the ‘how’ are most often featured in our own thinking, it is more important to be aware of the driving force behind our actions or decisions.

In the context of teachers’ professional development, Chris Lewis suggests that we may not always be aware of the changes or developments in our practices over time. It would, therefore, be beneficial to examine our own teaching beliefs and principles on a regular basis. He shares an idea for encouraging teachers to do that in in-service training (inset) sessions. Teachers are given certain statements about teaching and learning, some of which may be deliberately provocative. Consequently, any outstanding points in their discussion can form the basis for future training sessions.

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Workshop by Beatrice Segura Harvey
Beyond prompts: The great experiment with agentic AI

Beatrice Segura Harvey (Freelance | Nile ELT) demonstrates how we can harness the power of agentic AI to write materials for teaching and learning.

She defines agentic AI as a system in which various AI-powered agents or tools work behind the scenes to generate output for an AI chatbot (e.g. ChatGPT, Gemini, Claude, etc.). In this context, she sees large language models (LLMs) as a jack of all trades whose data supports different AI-powered agents.

She demonstrates how the AI chatbot Claude can write a textbook unit in under a few hours. Using this chatbot, she enlists ten additional AI-powered agents, each of which is tasked with a different aspect of textbook design. For each aspect, the following data needs to be fed to the corresponding AI-powered agent as input:

• Working documents (e.g. CEFR statements)
• Agent roles
• Curriculum outline
• Guardrails, i.e. limiting criteria to prevent AI-powered agents going off-topic
• Constraints

She divides the materials writing process into three phases: content, rendering (design), and quality control.

During her demonstration, Claude AI initially fails to produce her desired output. This shows that technology is not yet fully reliable. Nevertheless, it has the potential to increase our efficiency in certain aspects of materials writing.

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Forum on AI with purpose: Practical frameworks for language classrooms

In the context of higher education, Nazli Deniz Barutçuoğlu (MEF University, Türkiye) proposes a tried-and-tested framework for integrating AI into teaching and learning.

She outlines the different types of lesson tasks according to their cognitive demands:

• Foundational tasks: AI-free
  (e.g. activating prior knowledge, brainstorming ideas)
  
  
• Structured tasks: AI-enhanced, but limits should be imposed on input prompts to prevent outsourcing of learners' cognition
  (e.g. comparing information*, refining ideas, explaining ideas, providing critiques)
  
  
• Open exploration tasks: AI-transformed

* Learners can make comparisons between their output and the output generated by an AI chatbot. [This echoes Mark Smith’s idea about cognitive processes in his talk on Day 1.]

She also suggests that effective prompts usually include the four elements: role, context, task, and control (bounds). [This echoes Peter Lucantoni and Emir Aydin’s workshop on Day 1.]

Learners can be scaffolded in writing effective prompts, moving from the teacher’s prompt as a model, through analysis and evaluation of sample prompts, to learner-generated prompts.

Rasha Halat (Lebanese International University) introduces two models of pedagogical design: TPACK and SAMR.

TPACK stands for the optimal area of a Venn diagram consisting of:

• Content: target concepts for learning or learning outcomes
• Pedagogy: teaching strategies based on the content
• Technology: knowledge of how AI works

She advocates that the most effective use of AI in the classroom is one that is strategic and ethical.

SAMR, which represents four increasing levels of AI integration, stands for:

• Substitution: using AI to complete lesson tasks with zero learner input
• Augmentation: using AI to enhance human ideas
• Modification: using AI to transform, revise or change human output
• Redefinition: AI-facilitated learning through questioning and prompting

In lesson planning, she suggests that teachers can consider the following elements:

• Outcome: content aims and learning aims
• Task: lesson task or activity
• SAMR: cognitive demands of AI integration
• TPACK: value for learning with AI use
• Guardrails: controls and bounds

Consequently, TPACK can be used as a checklist to align with the learning outcome of a lesson, whereas SAMR can be used to target the cognitive depth of a task.

Irme Fekete (Budapest University of Economics and Business, Hungary) presents several classroom ideas for EFL teaching and learning. To elaborate on Nazli Deniz Barutçuoğlu’s idea, Irme Fekete mentions that learners can compare the similarities and differences in both versions, as well as identify anything incoherent in AI-generated output.

Another idea involves the learners’ use of AI tools to generate images. Each learner receives a different part of a reading text, which is used individually for image generation. After that, the images of various parts are put together in a picture story. Learners are asked to discuss how representative the AI-generated pictures are of the reading text, including any inherent bias with AI tools.

His final idea is similar to the one above, but it involves the learners’ group discussion of AI-generated podcasts instead of images. Learners use Google LMNotebook or NoteGPT to create a podcast, which they subsequently listen to and evaluate its credibility.

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Talk by Anna Lyons
How to help students avoid translation-app dependence

Anna Lyons (International House London) outlines several common reasons for the learners’ overreliance on translation apps in their learning process. These include low confidence, the lack of language skills, insufficient language knowledge, and pure convenience.

She first highlights some beneficial uses of translation apps, such as the mediation of certain concepts for the learners, comparative analysis between their first language (L1) and English (L2), clarification of language, and modelling judicious use of such apps.

She moves on to share what she has done to tackle the issue of overreliance.

• Learners need to deduce the overall idea of a reading text by using the words they know. For example, they match the ideas of the text to pictures. In a jigsaw reading task, learners may be allowed to look up a few words in the dictionary. These words are used productively in a later stage, such as by creating a poster to illustrate the ideas of the reading text.
  
  
• Collaborative writing activities without resorting to the use of translation apps. This has the benefit of peer teaching.
  
  
• Learners do a writing task in English. They do the same task again but write it in their L1 before they translate their written work into English. After that, they compare both versions and notice any differences in terms of vocabulary and sentence structures.

IATEFL Brighton 2026 - Day 1

Plenary session by Patricia Angoy

English language – the coloniser: A black female leader’s response

In today’s plenary session, Patricia Angoy shares her decade-long experiences of working in international or transnational education (TNE) as a teacher and educational leader. She begins by inviting the audience to imagine what it would have felt like to speak or listen to an extinct language, or a language that was never influenced by English in any form. Her position is that culture is embedded in language expressions.

She further illustrates her point with an example of somebody who rejects their first or local language and who has adopted a majority language in their own country. Whether this is by force or by conscious choice, she highlights the power that the English language holds in social and educational settings. English has become the preferred language among many people due to its status and the advantages that speakers enjoy. This is sometimes at the expense of the speaker’s original or ancestral first language, which is at best relegated to a secondary status or at worst despised for being unrefined.

She questions the entrenched ideas of one’s English language knowledge as a measure of their intelligence or social status. She invites teachers and educational leaders to examine their beliefs about the English language by considering Sharon Stein’s questions:

• What illusions have shaped me?
• What performances have I confused with responsibilities?
• If we let go of Empire’s stories, what else might we make space for?

She later poses several more guiding questions:

• How can we avoid the coloniality of language when English is the coloniser’s language?
• How do we teach through the language, about the language, and with the language so that we open new worlds and not shut them down?

Mentioning her journey of reconnecting with the language that her Caribbean ancestors once spoke, she suggests that a person becomes disconnected from their original culture when they willingly or unwillingly adopt English as their preferred language. English language teachers should, therefore, be aware of this attitude when working with learners of different nationalities in TNE. It echoes the current debates about Anglo-centricism in transnational education models.

Finally, she cautions against how multilingualism is being interpreted and promoted in TNE. She expresses her concerns over the current power structures by highlighting two opposite kinds of perception of a bilingual person or polyglot. While there are generally positive views on monolingual people’s ability to speak a foreign language in their own country, immigrants are often perceived negatively for their limited ability to speak the language of their host country.

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Workshop by Peter Lucantoni and Emir Aydin
Fostering learner autonomy through collaboration in AI

Peter Lucantoni and Emir Aydin (Cambridge University Press Türkiye) begin their workshop by contrasting control with autonomy. Learner autonomy refers to the ability to exercise control in the learning process. It means that learners maintain agency while working with other people and technological tools.

Peter and Emir then present the three factors for consideration when designing agentic artificial intelligence (AI) tools for teaching and learning: role, rules, and limits. (Teachers can use elevenlabs.io to build or train an agentic AI chatbot.) Using a specially trained AI chatbot with various built-in agents and parameters controlled by the teacher, they suggest that learners can use agentic AI as a partner in doing projects.

In their subsequent demonstration of agentic AI, Peter and Emir’s chatbot responds to any prompt request to produce a written text with only closed (yes/no) follow-up questions and suggested ideas. They reveal how they have trained their chatbot:

• Role: “Act as my partner in the project (attached photo). Your role is ...”
• Rules: “Do not write the text. I will write it.”
• Limits: “Respond with ...”

As the chatbot has been trained not to spoon-feed direct answers, it will not provide the learners with a ready-made text despite their repeated prompt requests. To a certain extent, this requires the learners to engage in a minimal amount of critical thinking.

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Forum on feedback by AI versus teachers

Selda Gumus (Ozyegin University, Türkiye) outlines the case for the learners to use AI for feedback on their work. She suggests that AI tools can help teachers of large classes better deal with mixed abilities, thereby ensuring equal opportunities for each learner to achieve the learning outcomes.

She introduces different procedures for in-class training:

• Reading skills: learners can work on their reading comprehension skills by using a specially trained AI chatbot [link to Peter Lucantoni and Emir Aydin’s workshop] of the teacher’s choice. The chatbot asks comprehension questions and helps the learners to reach the intended responses.
  
  
• Writing skills: learners can seek support from AI tools in the drafting process, rather than ask AI chatbots to produce a ready-made text.
  
  
• Critical thinking: learners need to be made aware of how AI conversation works. They should not stop engaging with an AI chatbot after receiving a single response to their questions. What they should do is engage with the response critically by asking follow-up questions.

In addition to task output (product), teachers can use other assessment tools such as the history of learners’ interactions with AI chatbots and reflections on strategic awareness or perceived usefulness of AI (process).

Anna Poghosyan (American University of Armenia) reports on her research project. It involves a case study of graduate students’ engagement with both human and AI feedback on writing skills. In her case study, the participants first received feedback from the teacher, who commented on broad areas such as clarity and coherence. Taking on board the teacher’s feedback, the participants make use of AI tools such as Grammarly for further feedback.

According to her questionnaire results, more than half of the respondents consider both feedback from the teacher and from Grammarly (analytic AI) most engaging. She concludes that AI-generated feedback tends to require lower-order thinking, whereas teachers can give feedback that requires higher-order thinking. Nevertheless, she states that AI literacy is a prerequisite for effective AI-human partnership in feedback giving.

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Talk by Crayton Walker
Teaching modality: A corpus-informed approach

Dr Crayton Walker (University of Birmingham) continues on the theme of using corpus data to inform our choice of language targets in teaching and in textbooks. While he focused on phrases and chunks at last year’s IATEFL conference, he explores modality in his talk this year.

Having established modality as a linguistic means of expressing our attitudes, he shows us groups of sentences taken from the corpus to illustrate the concept of harmony or concurrency, i.e. certain modal verbs tend to be used with specific words in real life. Some examples of this include might seem, must always, can possibly, and must surely.

Although modal verbs are polysemous, he argues that their meaning is not only constructed by the verb itself but also by harmony or concurrency. For example, learners often focus on the context when they learn the meaning of must, such as an obligation or deduction. The missing piece of the puzzle is that teachers and learners often overlook the adverb always in must always, which expresses an obligation, or the word surely in must surely, which refers to a deduction.

He draws our attention to some longer patterns or formulaic language in which modal verbs are used, such as “personal pronoun + must surely + slot + that-clause”. Other examples of patterns include it can possibly be, it should be a matter of, Can I just ask …?, and Could you possibly just ...? In other words, there is a pattern grammar in operation with modality.

As a side remark, he mentions different types of modality, including epistemic (e.g. certainty or belief) and deontic (e.g. obligation, permission and prohibition). He also points out that modality can also be expressed by quasi-modal phrases.

His final and most important message is that sentences in textbook exercises ought to reflect how modality is used in real life. The language should be informed by the examples from a corpus to avoid giving the learners exposure to unnatural models.

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Talk by Ian Pemberton
Using academic viewing circles to teach language and skills

Ian Pemberton (University of Warwick) reflects on one of the questions that he asked himself when he was transitioning from EFL into EAP teaching. His question concerns how language learning can be better promoted in the classroom. This has led him to look into usage-based theories.

Usage-based theories have influenced his development of Academic Viewing Circles. He then mentions two specific sources of influence:

• Construction grammars, which are the antecedents of the Lexical Approach [i.e. a lexicogrammar continuum in which chunks are seen as the interaction between form and meaning]
• Complexity theory, i.e. the emergence of regular patterns among concrete examples of language

Another influence comes from evolutionary biology, which describes the order of acquiring or learning language skills. He suggests that language learning can be enhanced by making use of the learners’ “biological” skills (i.e. listening and speaking) as these represent the first to be acquired among children.

Having addressed his theoretical influences, he outlines the process of developing his model for teaching with videos: Academic Viewing Circles. It began life as his application of Tyson Seburn’s Academic Reading Circles (2016) in EAP classes. [This requires prior knowledge of Seburn’s model for teaching academic reading skills.] Subsequently, Ian Pemberton experimented with different texts while keeping to the same group roles.

When he eventually replaced reading texts with videos, he applied the above usage-based theories to teaching language skills, i.e. using listening and speaking tasks to enhance his students’ learning of various chunks and patterns from the videos. Nevertheless, he decided to do away with the separate roles (e.g. contextualiser) as there was the risk of his students going off-topic or getting distracted from the content and language of the videos.

He outlines the procedure for his Academic Viewing Circles:

• Viewing: video tasks
• Recount: consolidation of new language (chunks and patterns) and peer teaching
• Task: information transfer or synthesis of ideas with collaborative group presentations

Finally, he suggests a range of possible learning targets with videos, using his Academic Viewing Circles. These include triangulation in research skills, paraphrasing, summarising, and academic writing styles, among other examples.

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Talk by Mark Smith
Academic literacies and AI: Teachers giving guidance and fostering agency

Mark Smith (Wimbledon School of English, London) begins by stating his preference for the term “academic literacies” over “study skills”, whose connotation he thinks is based on a deficit model.

Using authentic writing as an example, he states that it is beneficial for teachers to identify the cognitive processes involved, such as interpreting meaning, constructing arguments, connecting ideas, and evaluating ideas. AI tools should be used in a way that helps the learners engage with meaning, rather than one that allows them to conveniently outsource their cognitive processes.

He suggests ways of integrating AI use into three kinds of classroom routines without sacrificing the learners’ cognitive engagement:

Lexical categorisation

1. Each learner groups a set of lexical items according to the criteria of their free choice.
2. Learners compare and evaluate each other’s criteria, justifying their decisions.
3. Learners use AI tools to group the same set of lexical items. They deduce the criteria that their AI tool has used. They also make comparisons between AI and human versions.

Dictogloss

1. The whole class follows the usual routine of Dictogloss.
2. Learners use AI tools to fill any gaps in their individual reconstructed texts.
3. Learners compare and critically analyse the language in both AI and human versions.

Jigsaw reading

1. The whole class is divided into two groups. Each group is given a different part of the source text to summarise. At the same time, the summary of each part of the text is generated by an AI chatbot.
2. Learners in each group compare both AI and human versions of the summary.
3. When they are satisfied with their summaries, groups A and B work together to exchange information and construct the meaning of the whole text.

IH Journal: Issue 56

Issue 56 contains a mini-issue on sustainability. There are articles about professional development, AI feedback, and dealing with stereotypes.

Read the IH Journal (Issue 56) here.

Here is the direct link to my article - Strategies for Encouraging Reticent Learners to Speak.

Gamifying EFL exam preparation classes

The purpose of gamification is to add fun to the language learning experience. The learning target remains the same, but the mode of delivery is different to traditional, pen-and-paper exam practice. After all, some language learners may prefer game-based learning. It is also said that games can make language learning more memorable as the learners recall their pleasant experiences, which they link to the learning target.

In English exam preparation classes, it often goes against the grain to incorporate the idea of 'fun'. Language exams are a serious matter, so how appropriate would it be for teachers to gamify lesson activities? The response varies depending on the teacher's philosophy of teaching and learning. While I'm generally more cautious about gamification for its own sake, I tend to introduce fun games in small doses into my lessons and see how effectively these games work with my students.

Bidding game

In my Cambridge B1 Preliminary for Schools class at the British Council yesterday, I decided to add the 'bidding' element to a multiple-choice cloze passage. This involved zero extra material except a board.

My students did the reading task individually as usual. Then they worked in groups of three to compare their answers. This was where the 'bidding' part came in. For each of their answers, each group had to place a bid of up to five points. If they got it right, they were awarded the exact number of points in their bid. If they got it wrong, however, they had zero points.

Based on my observation, the additional gamified element in the feedback stage did add a bit of spice to the otherwise dull routine of exam practice tasks. My students' motivation increased slightly and this kept them going in the following activity. Gamification doesn't always require intricate game design or elaborate props - some of the most effective ideas are materials-free!