This year, I focused on how we can motivate and encourage our students to use AI less. While it’s super tempting, as a bag of potato chips, to do every single thing with AI, it’s not necessarily useful for their development. So, what can we do?

• We can either redesign activities that are inherently boring or can be easily completed with GenAI using one of the following “analog” techniques:

  • truly communicative tasks, which have a real purpose, a target audience, and an authentic context

  • task based and project based learning (check out the recently published book on PBL by Jason Anderson)

  • multiplayer quiz games

  • escape room style activities (check out the Break Out! series by Rhona Snelling).

• Or we integrate AI meaningfully in the form of various structured chats or AI-assisted projects, such as :

  • projects, like “AI in my future job” or “Saving the world byte by byte”

  • vibe coding projects (vibe coding means you generate interactive apps and websites using natural human language)

  • structured chat conversations, such as this “Argumentative essay writing assistant” or this “Debate with me!” activity

  • creating your own custom GPT, like a study assistant.

But the main thing is that students will want to use AI if they think the task is not interesting, personalised, or meaningful enough. What we can do is try to make them use it less.

But what I have to say is that there will always be somebody who cheats because they want to cheat, and there will also be students who cannot be pleased. We can’t please everyone, but we can try to convince those on the fence.

Download the slides here.

Access the handouts here.

The surprising case of receiving my AI-generated photo

So what happened was that between two sets of talks in Italy, I went back home to deliver an online training session for a group of teachers in Hungary. The topic was image generation. I had just explained the main functions and features of Google’s image generator, Nano Banana, and I was expecting them to show me their first generated images. Can you guess how I felt when a participant sent me this photo?

At first I felt surprised. Because I wasn’t expecting this at all.

Then I felt amazed. Because I think it was a super creative solution. My participant took a screenshot of me as I was delivering my online webinar, and then used that photo as a reference image for this AI generated version.

But then I felt a bit uneasy. Because to be honest, they didn’t ask for my permission or consent at all. And now my face is fed into an image generation model’s training data. Not that I haven’t done something similar myself. But in that case I was the one who decided to upload my own image.

The curious case of Grammarly’s Expert Review tool

I saw this post on Amanda Bickerstaff’s Linkedin feed. It talks about Grammarly’s Expert Review feature, which has since been removed, and Grammarly is now facing a class-action lawsuit. The feature promised to give feedback on your piece of writing imitating the style of notable authors, such as Stephen King or the late scientist Carl Sagan. However, no author’s consent was asked for when training the model on their works.

You can read this quote from Casey Newton in a Guardian article: “[Grammarly] curated a list of real people, gave its models free rein to hallucinate plausible-sounding advice on their behalf, and put it all behind a subscription. That’s a deliberate choice to monetise the identities of real people without involving them, and it sucks.”

The even worse thing? That there are many authors whose opinion cannot even be heard because they have recently passed away. AI for Education created a perfect discussion prompt for this:

The remarkable case of authors protesting with an empty book

Connected to this, I have recently seen another post, which is by The Society of Authors. Almost 10,000 authors called out AI companies for illegally using books to train their models.

Titled Don’t Steal This Book, it is empty of text except the names of the authors involved, and represents the impact on authors’ livelihoods and the publishing industry that is expected if the government proceeds with plans it has floated that would make it easier to train AI models on copyrighted work without a licence.

I have already written about how AI models are trained and how they obtain all their training data (click the link below). Most of what’s on the internet is open source and thus OK to be used for training. But most of those sources are not high quality enough, so AI companies have decided to use all the sources they can put their hands on, and they definitely haven’t compensated the authors for it. And they are rightly upset. Although I’m really happy to see authors taking action, it’s difficult to see whether it’s going to have any effect.

Connected activity: File safety

While uploading pictures and files without the owner’s consent could, of course, be somehow prevented with certain tech limits or alerts, but the main thing here is the principle. And that's why it's super important to talk with our students (no matter what age to be honest) about what's OK and what's not OK to share and upload into an AI system. We won't be able to stop them, but at least we can make them understand why this could be problematic.

So here’s a task, File safety, that comes from our book AI Literacy in the Language Classroom. The way you can play it is that first, you elicit what they could do with the particular file if they uploaded it into a chatbot, and then you'd discuss if it's ok or not ok to upload them (or it depends...).

My suggested answers are:

1. Better NOt due to data privacy and protection

2. OK if no longer protected by copyright

3. OK but might be used for targeted ads

4. OK if not a special design and be aware of mistranslations

5. NOT OK

6. OK if they gave their consent and is only used for feedback suggestions, not for grading

7. NOT OK as it could lead to misdiagnoses

When I was asked last year to predict what the next big thing is going to be in ELT with regard to AI, I was first at a complete loss. But then I glanced through my Linkedin feed, and could quickly see that it’s probably going to have something to do with AI agents.

Although most of the posts and experiments I’ve seen so far come from the worlds of higher education, instructional design, and business, I still believe that it’s going to have an impact on the world of “regular” teaching as well. Because at the end of the day, what all these new technological inventions do is make traditional learning tasks easier to complete.

Cheating vs. Learning with AI

That’s why I decided to take a closer look at what we can do as teachers to create a more authentic and realistic learning environment to make cheating with AI a less appealing option.

Learning with AI, on the other hand, is something we shouldn’t punish as long as it follows the main principles of AI literacy (or AI fluency, as Anthropic called it in their latest report):

• critical approach to the generated results

• checking the sources that were used to generate the results

• asking follow-up questions to make sure everything is clear

• being able to formulate and/or refine what you want

What’s an agent and why does it matter to us?

First of all, we need to clarify some confusing terminology.

There are many places where you might see the word “agent” but it describes something else. I’ll use David PBL Ross’s definition now:

This means that you can give an AI agent or an agentic browser, like Perplexity Comet or ChatGPT Atlas, a task, e.g. to buy a plane ticket or to redesign your already existing course, and they will take action and complete the whole thing independently and autonomously, while stopping and asking for your input whenever it’s needed (for example, when they need to log in somewhere).

I loved Anna Mills’s webinar about how agentic browsers can easily complete online quizzes and activities in Learning Management Systems. What this essentially means is that online course completions and certificates will lose their relevance. And this in turn would actually disadvantage those who can’t access in-person education. At the moment, there are no real solutions to this problem yet (or there could be but it’s not really in the companies’ interest). I highly recommend her webinar and her slides:

Anna Mills’ Substack

Agentic AI: Considerations for Educators

When the Chancellor’s Office for the California Community Colleges sponsored a webinar on agentic AI recently, registration filled up at 1000, and many watched the livestream. I was honored to be on the panel tasked with provide some basic information about the challenge of agentic AI in education. I continue to add to what I shared that day. Here is a …

Read more

3 months ago · 24 likes · 3 comments · Anna Mills

Other uses of AI chatbots: assistants, shared chats, and custom bots

Now, let’s take a quick look at other uses of AI chatbots that might be sometimes confused with agentic behavior.

• AI assistants: You start with a prompt that defines the core task. Every new message builds on the original prompt. E.g., feedback writing assistant, report writing assistant, or parent email assistant. These are basically what you can find in MagicSchool.

• Shareable chats: I’ve recently started experimenting with these since you can now interact with chats that were shared with you. In this case, you create a step-by-step dialog-style activity, which you then share with your students who can have their own individual chat sessions. E.g., argumentative essay developer, text-based role plays, business plan idea generator.

• Custom GPTs: These are the closest to agentic behavior, and that’s why Copilot calls these “Agents” but they can only become agents if they start making decisions independently. GPTs (Gemini calls them “Gems”) are custom-made bots with a clearly defined function and pre-uploaded knowledge. E.g., school FAQ bot.

The main question: Why do students want to use AI to solve tasks?

OK, there are all these new AI chatbots and agents out there that can easily do the work for students. But the real question is this: Why do they want this?

Because most activities in the lesson tend to lack intrinsically motivating content and design and there’s no real sense of achievement. Current generations now more than ever want to know why they’re doing what they’re doing. What’s the purpose of doing the tasks?

Possible solution: more authentic learning environments

One way I think we could solve this problem is if we create more authentic activities and contexts that would hopefully engage our students more. This obviously works more if we teach in an in-person context where we (perhaps) have the chance to make our students pay attention.

As long as there seems to be an authentic reason why they should be engaging with our lessons and activities, I believe we could make them listen to us and work with us.

Let me know what you think about this! Have you tried any of these techniques? Did they work?

Leave a comment

Some additional sources

1. Truly communicative tasks >> Hadfield, J.: Intermediate Communication Games ; Anderson, J.: Role Plays for Today

2. Task Based Learning >> Anderson, N.&McCutcheon, N.: Activities for Task-Based Learning

3. Project Based Learning >> Anderson, J.: A Framework for PBL in ELT ; Ross, C.: Project Power!

4. Escape room style activities >> Vosieva, D.&Decker, K.: How to Use Escape Room Activities ; Minami, F.W.: Escaping the Classroom

5. Multiplayer quiz games >> Wayground (Quizizz) Mastery Peak ; Nearpod Time to Climb

Come to IATEFL Brighton, where we’ll explore this in the form of a workshop!

Ez a 👉 hosszabb magyarázó (explainer) videó Google Notebook LM segítségével készült egy általam összerakott 👉 fogalomgyűjtemény alapján. A végeredmény persze nem 100%-os - hallatszik az erős MI hang, hallatszanak kiejtésbeli és nyelvtani problémák, de ez a verzió így is sokkal jobb lett, mint a rövid videó változat. Külön tetszik nekem, ahogy a fogalomlista elemeit megpróbálta logikusan összefűzni, hogy az egyik következzen a másikból.

2. MI műveltség a tanteremben - hivatalos könyvbemutatónk anyaga (ppt)

Az MI műveltség/MI tudatosság fejlesztéséről szóló angol nyelvű könyvünknek több bemutatója is volt. Ez a 👉 diasorozat a hivatalos magyar nyelvű esemény anyaga, melyet az Engame Akadémia közreműködésével tartottunk és melyben több azonnal bevethető feladatot is találtok.

Feladatlista:

• Képi torzítások

• Song reboot - Újragondolt dalok

• A nyelvtanulás jövője

Könyvünk megvásárolható az alábbi helyeken:

• Libra Books (Budapest, Kölcsey utca) - 15-20% kedvezmény tanároknak

• Libri online

• Bookline

3. Feladatgyártás az MI segítségével

Ebben a 👉 posztban megnézünk egy példát a hatékony ember-MI kollaborációra. Bemutatom lépésről-lépésre, hogyan hoztam létre egy szabadulószobát ChatGPT segítségével. Itt még nem a vibe codingról van szó, csak arról, hogyan tud az ötletelésben segíteni egy chatbot.

4. Változó szerepek - az MI hatása az oktatásra (ppt)

Ez a 👉 diasorozat a Hifeszt esemény keretében tartott rövid előadásom anyaga. Célja figyelemfelkeltés és az MI műveltség fontosságának bemutatása.

5. Hogyan tanítsuk meg a diákokat az MI kritikus, etikus és felelős használatára? (interjú)

Ebben a 👉 Modern Iskola interjúban arról beszéltünk közösen Menyhei Zsófival, hogy miért tartjuk fontosnak az MI tudatos beépítését az oktatásba. Nem a tiltás lesz a végső válasz, hanem a pedagógialag megfontolt közös munka.

6. Hogyan írjuk meg iskolánk MI ajánlását? (poszt)

Ebben a 👉 posztban megosztok veletek néhány tippet egy MI ajánlás/szabályzat/útmutató/iránymutatás összeállításához, valamint becsatolok még néhány remek sablont és dokumentumot, amik online elérhetők. Amiben egy ilyen dokumentum tud segíteni, az az, hogy világos(abb) iránymutatásokat adunk, valamint az osztályunkat vagy az iskolát a generatív MI oktatásban és tanulásban való használatával kapcsolatos attitűdskálán elhelyezzük.

7. A munka/ám jövője (projekt feladat)

Ebben a projektfeladatban a diákok csoportokban visznek végig egy rövid kutatást arról, hogyan fogja az MI befolyásolni a jövőbeli szakmákat és a munkavégzés módját. Néhány irányadó kérdés, amelyet követhetnek:

• Mely munkák fognak eltűnni az MI miatt, és milyen új foglalkozások fognak létrejönni?

• Hogyan fogja az MI megváltoztatni az emberek mindennapi munkavégzését?

• Mely készségek lesznek a legfontosabbak a munkavállalók számára, amikor az MI kezeli a rutin feladatokat?

• Hogyan készülhetnek fel a diákok olyan foglalkozásokra, amelyek még nem is léteznek?

A projekt során különböző mesterséges intelligencia eszközöket használhatnak:

• chatbotokat információkereséshez (ChatGPT deep research, Perplexity, Gemini deep research…, Google Notebook LM)

• poszterek, infografikák, vizualizációk és prezentációs diák készítéséhez (Gamma, Canva, Napkin, Google Notebook LM)

• hangalámondások, videók készítéséhez (Elevenlabs, HeyGen, Synthesia)

És íme a poszter!

8. Digitális átállás az oktatásban - 21. századi készségek, MI tudatosság és digitális kompetenciák a jövő tanulásáért (ppt)

Ez a 👉 diasorozat egy TEMPUS eseményre készült, és kicsit tágabb témát ölel fel, mert kitér a digitális kompetenciafejlesztés fontosságára is. Az előadás második felében természetesen áttérünk az MI tudatosságra. Hozok adatokat arra, hogyan érzik magukat a tanárok az MI világában, fölsorolok pár példát már meglévő MI ajánlásokra a felsőoktatás világából, és találtok benne egy konkrét feladatot is (Mi rossz történhet, ha…?), ami az adatvédelem fontosságára hívja fel a figyelmet.

9. Hogyan változtatja meg a felsőoktatást az MI? (webinárium)

Ezt a 16 perces 👉 videót még 2023-ban vettem fel a Károli Gáspár Református Egyetem oktatóinak. Bár a technikát illetően sok minden megváltozott azóta, az alapvető módszertani elgondolások és iránymutatások szinte változatlanok, ezért ajánlom ezt a videót is, különösen a 9. perctől.

10. Felsőoktatás az MI korában (Csomópont podcast)

A Csomópont podcast, Magyarország első tudásmenedzsment podcastja, meghívására 2024-ben arról 👉 beszélgettünk, hogy:

• Hova vezethet a tudástőke generálásának, megszervezésének és megosztásának drasztikus expanziója?

• Egyáltalán hogyan beszéljünk az AI-ról?

• Milyen fogalmi és értékkészlet áll már most a rendelkezésünkre, amely eligazítást adhat korunk kihívásai számára?

Ha pedig személyre- vagy tanári karra szabott MI az oktatásban tréning érdekel, nézd meg, milyen tréningcsomagjaink vannak és vedd fel velünk a kapcsolatot!

Key topics

Oxford University Press’s new series, The Impact of Assessment on Teaching & Learning, is hosted by Ben Knight and features expert guests Joanna Szoke and Nathaniel Owen. Together, they explore:

✔ How exams can drive systemic change
✔ Building teacher assessment literacy
✔ Policy implications and institutional reform
✔ The role of AI in creating fair, efficient feedback

If you’re responsible for shaping assessment strategy or improving learning outcomes, these conversations will give you actionable insights and a fresh perspective on what’s possible.

Episodes

• Ep. 1. - What Is The Real Impact Of Assessment on Learning?
  
  What is the real impact of assessment on learning?
  In this opening episode of our series exploring the dynamic relationship between assessment and learning in English Language Teaching, host Ben is joined by ELT Assessment experts Jo Szoke and Nathaniel Owen to explore the concept of washback, the influence of tests on teaching, and how it can be both positive and negative.
  Nate and Jo share personal stories, classroom experiences, and research insights to help us rethink how assessment can support motivation and progress.
  

Watch ep 1 now

• Ep. 2. - What do Teachers Need to Know about Assessment?
  
  What does assessment literacy really mean for teachers?
  This episode focuses on the classroom, with Jo Szoke and Nate Owen exploring how teachers can design assessments that genuinely support learning. We discuss reliability, fairness, rubrics, and how to balance exam preparation with communicative language teaching, as well as practical tips for managing student expectations and motivation.
  

Watch ep 2 now

• Ep. 3. - Can Assessment Drive Real Change?
  
  Can reforming exams lead to better teaching and learning?
  In this episode, we explore the institutional and policy-level impact of assessment. From integrated skills testing to equity and standardisation, Nate Owen and Jo Szoke discuss how assessment design can influence national education systems, and why teacher buy-in is essential for lasting change.
  

Watch ep 3 now

• Ep. 4. - How Can Assessment Be Used To Support Learning & The Role Of AI
  
  How can assessment be used to support learning, not just measure it?
  This episode explores alternative assessment methods such as portfolios, peer feedback, and gamification, and looks at how AI is reshaping the future of feedback and test design.
  Jo Szoke and Nate Owen also discuss ethical concerns and the importance of keeping humans in the loop.
  

  Watch ep 4 now

These podcast episodes are closely linked to the position paper titled “The Impact of Assessment on Teaching and Learning: Creating positive washback”, which you can access here, and to the interactive webinar called “Unlock the Power of Assessment in Your Classroom: creating Positive Washback”, which you can watch here.

So, I’m going to show you two activities that I already tried in my classrooms - one in-person and one online.

1. Debate with me!

This is actually a slightly modified version of the activity with the same name that’s in our book, AI Literacy in the Language Classroom. I played it with just one computer, which means it’s perfect if your students are under 13, they don’t want to sign up to ChatGPT, or if mobile devices are banned in school.

• First, you pick a topic that’s going to be discussed during the debate. Make sure it can be the basis of a pro-con debate. Have some preparation activities with students, such as activating their previous knowledge or teaching them some necessary words.

• Next, type this prompt into your AI chatbot of choice. Fill in the relevant details:

  You are going to take part in a debate about [INSERT YOUR TOPIC HERE]. For context, [INSERT ANY DEFINITIONS OR BACKGROUND INFO THAT YOU THINK IS RELEVANT]. First, you need to decide which side (the pro or the contra) is more difficult to argue for. That’s going to be your side. Act as a proper debating partner, bring strong arguments to support your point. You start the debate. Do you understand?

• The chatbot is going to spit out an argument, which will serve as the starting point for the class. Depending on class size, either break students up into groups of 3-4 or have them work as one big group. In my case, they worked as one group.

• Have students read and understand the starting argument. Make sure the text is large enough for everyone to read. Ask if they need help in understanding anything. Then give them time to come up with a counterargument. They can either type their idea(s) into a collaborative online document (from where you’ll be able to copy and paste it into the chat conversation) or they can dictate it to the computer. Have them do 2 rounds.

The main strengths of this activity I think are thinking on the spot (because students have to come up with something right away) and unpredictability (we don’t know which side the machine is going to pick and what arguments it’s going to choose). It also helps them practice their reading, speaking, and writing skills all at the same time. What’s more, they can work together to “beat” the machine: my students were keen to find logical loopholes in the AI’s argumentation, which is actually a great method to improve their own critical thinking skills.

Buy the book!

2. Academic writing ping-pong

I came up with this activity as I was thinking hard how to deliver an interesting and meaningful academic English course to teenagers, which is by the way online!! Yes, you heard it right: teaching writing online in this day and age??? But I didn’t want to throw in the towel, so at first we spent some time creating our own AI Code of Conduct, and I tried to make a strong point for this new educational setup: You’re only going to learn something if you’re willing to make an effort. If you want to cheat your way through the course, fine, I don’t care, but you’re only taking away as much as you’re putting in.

With that done, I went on and set up an academic writing ping-pong game via ChatGPT .

• We were studying thesis statements, paragraph structure, and argumentation. So, first, students in pairs had to choose a topic from a list and were asked to write two thesis statements for it. This was done in a shared Google doc. I gave some short feedback on their thesis statements in open class, then went on to describe the AI-based activity.

• The activity has two parts. In the first one, their thesis statement is evaluated against a set of criteria and a slightly upgraded version is offered. The second part is pretty similar to the previous game in that the chatbot takes up the opposite side and writes a short paragraph that follows what we learned about topic and supporting sentences, to which the student(s) should respond.

• Prior to the lesson, I set up a chat conversation with the following prompt:

I want to set up a game for an English for academic purposes lesson.
Step 1: The student gives you the topic of the essay and their idea for a thesis statement. Analyse it according to the following criteria: 1. Avoid overused, general terms and abstractions. 2. A thesis is never a list. 3. A thesis should never be vague, combative or confrontational. 4. An effective thesis has a definable, arguable claim. 5. A thesis is never a question 6. A thesis should be as clear and specific as possible.
If you found the thesis statement well-phrased, move on to Step 2. If it's not well-phrased, help the student until they come up with an acceptable version.
Step 2: Write a paragraph of 4 sentences maximum (with a topic sentence and supporting sentences) that argues with the student's thesis statement. To this they need to respond with a paragraph that is in favour of their original statement. Keep this ping-pong match going for 2 more rounds. That's the end of the game. Do you understand?

• The good thing about shareable chatbot conversations now (you can do this with ChatGPT and Gemini) is that whoever you share them with can continue the conversation. This basically allows you to create a custom game or bot that each student can explore individually.

• In my case, I put students back into pairs, shared the conversation link with them (try it yourself! here’s the link), and asked them to work together by sharing one of their screens. (You can actually invite people into conversations on ChatGPT, meaning that both of you can take part in the same conversation, but I didn’t want to bother with it this time). To my surprise, they enjoyed working together on their paragraph, and were excited to see what response they got from the chatbot.

• The additional good thing about this custom bot is that they can play with it as much as they want - by giving it different topics and thesis statements. They can also be encouraged to ask the chatbot in the end whether their paragraphs were well-formed.

I’m actually pretty pleased with these two activities 😊 Let me know if you created similar AI-based in-class tasks!

And now it’s officially Christmas time! 😄 No posts until January! Enjoy your time off! 🎄

There were two super interesting posts on Linkedin last week. First, James Abela published a mind-blowing fact about AI use: It takes 5 AI queries to equal the energy of one A4 photocopy.

He then goes on to share other interesting comparisons as well, such as:

• 1 AI query uses around 10 times more energy than a normal Google search.

• Charging a smartphone is around 3-4 AI queries.

• Streaming an HD video for an hour uses 50-100 Wh, which is 17-33 AI queries.

What’s surprising in all of this is that we seemed to have been sure, so far, of the fact that whenever we prompt an LLM to do something for us, we’re punching the planet in the face. With Abela’s calculation (he’s created a cool interactive AI energy calculator with some help from Canva AI), the picture doesn’t get any better, to be honest. It simply means that we’re killing the planet either way, whether we’re asking ChatGPT to do something for us or not.

Is photocopying morally acceptable?

Connected to this, Amelia King posted her presentation prepared for Eco Week, which not only highlights the key role that one of our most important resources, water, plays in the existence and use of GenAI, but also attempts to debunk (or rather clarify) some common myths, such as:

• ChatGPT is the main reason more data centres are being built.

• Using AI is worse for the environment than Google/Youtube/flying/etc.

• If you care about the environment and/or climate change, you shouldn’t use AI.

Make it make sense

To me, the bottom line of these two posts is something that I keep saying whenever the question of AI’s impact on the environment comes up during my training sessions or workshops:

We’re harming the environment no matter what. All the luxuries that we can’t really live without (a warm home, big or cozy lights, streaming services, cell phones and laptops, social media, cars and travel, online shopping, lattes, good food, etc.) already use a significant amount of energy. And since AI is getting integrated into almost every single service we use, its impact is becoming ubiquitous and more unclear as such. What we can do is only try and harm the planet less by avoiding overconsumption, overindulgence, and making sure every scroll and click has a purpose.

The project task

So, let’s see this project task from our book (chapter 5.4, p. 89). The idea is that we ask students to do some research in teams to see either how AI technology can save the planet (by optimising farming, for example) or how it destroys the planet and whether there’s a way to stop it.

Nothing is black and white anymore, and AI can either be the destroyer or the savior, or both at the same time. Students are thus asked to look into this gray area, and by becoming more aware of the implications of this technology, hopefully, they will use it more purposefully.

People to follow

If you’re interested in environmental issues and sustainability, and would like to introduce them into your lessons, I wholeheartedly recommend this list of amazing people to follow:

• The absolute go-to name is Harry Waters, founder of Renewable English and author of Activities for a Greener Mindset by DELTA Publishing. He is truly an authentic person trying to fight for the planet and the climate both in and outside the EFL classroom.

• Jade Blue is a fantastic ELT professional, who authored the Sustainability Framework for ELT Activity Cards and who does workshops and trainings in this area.

• Emily Bryson does visuals and sketchnotes, and she has recently shared some amazing visual templates for environmental discussions.

I’m sure this list is not complete, so let me know if I missed someone!

Leave a comment

And don’t forget to buy our book! :-)

Buy the book

Click here to view the slides

Download them as a PDF

“What’s the highest peak in the world?”

“I don’t know, let’s Google it!”

“Oh, come on, you’re such a millennial, I’ll just ask ChatGPT instead.”

This little made-up dialogue might as well try to illustrate generational differences (a huge trend by the way on social media…) but it also shows a shift I’ve noticed in my environment: While Google used to be the go-to quick tool for finding information for long years, now more and more people (esp. the younger generation) asks ChatGPT instead.

Oh, but don’t think that Google is crying in the corner as the last pillar of “truth” because it is also aggressively integrating its own AI overview into the search results, pushing real websites in the background. And as AI-powered search engines, like Perplexity’s Comet or OpenAI’s Atlas, appear on the scene, it’s going to be more and more difficult to stay in control of finding, comprehending, and organising credible information. Many sources claim that AI browsing has broken the internet as we know it.

So what does this mean for us, educators?

To be honest, I’m also at a loss… Obviously, it means that we need to put an even bigger emphasis on developing critical thinking to wade our way through untrustworthy or just simply AI-generated information (of which we now seem to have as much as of human-generated), but now it seems to me like we’re trying to find our way in the ever growing darkness. At first, you can still make out shapes and figures, you can orient yourself but as the darkness is growing around you, you no longer see the edges of objects, and everything just becomes a complete black blob.

Some sources say that this will eventually bring us back to where it all started: a handful of (credible?) sources we trust. Because if you grow tired of constantly evaluating every single piece of information, you’ll either completely give up caring and will believe whatever you find just to keep going or you’ll abandon search engines (or the entire internet even) completely and choose one or two sources you decide to trust forever.

As educators, I believe our major task right now is to equip our students with some foundational knowledge and skills that help them notice if something is fishy. It’s certain that we can’t become walking encyclopaedias but we can enhance our senses that tell us that we need to look further for the right information.

Basic steps to improve critical thinking skills

The easiest way to develop our students’ critical thinking skills is if we make them work for the information they’d like to receive.

1. Use inductive teaching techniques instead of deductive ones. Let them find the rule themselves by noticing patterns instead of telling them yourself. Present the new language in context, use guided discovery sheets, ask many guiding questions.

2. Let students experiment until they find the right solution - don’t rush in with the correct answer right away. This could be especially useful in exam preparation classes, for example, in the case of multiple choice reading and use of English activities. There are of course parts of learning the language when it doesn’t do any good if you let them wander aimlessly, e.g., trying to remember irregular verbs.

3. Let them explore different viewpoints when discussing a question or during a debate. One easy way to do this is to give them different roles, such as in the Six Thinking Hats game.

4. Give them tasks which don’t have one correct answer. One of my favourites is when you ask them to classify a group of random vocabulary items. As long as they can justify their version of grouping, they have used their brains and they have engaged with the words.

5. My new favourite is the so-called thunk questions. I first learned about them thanks to Fiona and Theresa’s podcast, Tea with Fi an T. Thunk questions, created and collected by Ian Gilbert (check out his book), have no wrong answer and are designed to make you think and see the world differently.

   

Practicing critical thinking in the age of AI

Now, this is getting much more difficult day by day as AI-generated content is getting more and more convincing.

For example, look at this fantastic photo and the comment I found below it:

But I’ve got another one. It was a video of kangaroos jumping in the sea with the caption “Nature is so beautiful.” In the comments, people went wild trying to convince each other that kangaroos in Australia do hop into the sea or that the video is indeed AI-generated.

The most we can do at the moment is double-check everything:

• by doing a reverse image search on Google,

• by asking for and checking the sources the chatbot provides in its response,

• or by searching for the same thing on Google and checking how many and what kind of sources mention the same piece of information.

Still, this only works if 1. we take the time to check, 2. if we can still distinguish fake from real.

Activities from our book with this focus

• Apples to oranges (p. 61): In this activity students bring a text they have written to class and prompt an AI chatbot to create a version of the same text. They then use a set of criteria to critically compare their own writing with the AI-generated content. This process encourages students to reflect on their writing skills while also evaluating the AI as a tool.

• Deepfake dilemma (p.65): This activity raises students’ awareness of deepfakes and encourages critical thinking about their risks and potential positive applications. It also provides students with opportunities to learn relevant vocabulary connected to the topic of AI and media literacy, with terms such as synthetic media, disinformation, misinformation, and defamation naturally emerging during the lesson.

• Credibility officers (p. 67): This self-discovery activity helps students learn how to fact-check AI-generated responses using appropriate sources. This isn’t only useful for developing responsible AI usage, but it is also especially beneficial for students in academic English language courses, where understanding essay writing and properly crediting sources is a key focus.

• Perspectives hot seat (p. 104): This activity helps explore different stakeholders’ perspectives on using AI through roleplay. It can be used early in a

  workshop on teaching for AI literacy.

  

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Miért fontos egyáltalán egy MI ajánlás?

Jó kérdés. Egy szabályzat önmagában nem old meg minden problémát. Nem garantálja azt sem, hogy a diákok kidobják az ablakon a telefonjaikat, és boldogan folytatják a hosszú esszék írását.

Amiben viszont tud segíteni, az az, hogy világos(abb) iránymutatásokat adunk, valamint az osztályunkat vagy az iskolát a generatív MI oktatásban és tanulásban való használatával kapcsolatos attitűdskálán elhelyezzük.

Egy ilyen iránymutatás hiánya lényegében azt jelzi a diákoknak, hogy (legalábbis az intézményben vagy az osztályteremben) nincs egyértelmű konszenzus a GenAI használatának számos fontos kérdéséről, mint például az adatvédelem, a szerzői jogok, a tanulói autonómia, az eredetiség kérdése és a kritikus gondolkodás. Ez pedig azt jelenti, hogy a tanárok nagyrészt eltérő utakat fognak választani (a tudatlanságból vagy gondatlanságból fakadó vakmerő szabadság és a szintén tudatlanságból vagy félelemből fakadó teljes tiltás között terjedő széles skálán), ami valószínűleg negatívan fog hatni a diákokra tanulmányaik során.

Miért jó, ha közösen alkotjuk meg?

Egy ilyen technológia, amely még azok számára is bonyolult és homályos, akik úgy tűnik, hogy értik, elkerülhetetlenül megosztja az embereket (iskolai vezetők, tanárok, diákok és szüleik), különösen akkor, ha látszólag különböző céljaik vannak.

Egy egyoldalú MI iránymutatás csak az egyik csoportot fogja kielégíteni, a többiek pedig csalódottak és félreértettek lesznek. A közös megközelítéssel mindenki láthatja, hogy a másik fél hogyan látja a kérdést. Ez remélhetőleg segít nekik olyan magatartási kódexet kidolgozni, amely mindannyiukat kielégíti.

Könyvünkből, az AI Literacy in the Language Classroom c. könyvből, két szerepjátékos feladat tökéletesen alkalmas egy ilyen megbeszélés és közös brainstorming alapjainak lefektetésére:

Perspektívák hot seat (97. o.): ez a feladat segít a szerepjáték segítségével feltárni a különböző felek nézőpontjait az AI használatával kapcsolatban. Üljön le valaki a “hot seat”-re, nézzen a csoport felé, és játssza el a választott szerepet. Válaszoljon a csoport kérdéseire az aggályaival vagy érvelésével kapcsolatban, ügyelve arra, hogy a karakterében maradjon. Csoportként reflektáljanak az egyes felek perspektívájáról nyert betekintésekről. Ötleteljenek a szerepjáték során felmerült releváns aggályok megoldásának módjairól.

Scenarios (97. oldal): ez a feladat szerepjátékra és olyan helyzetek elemzésére ösztönöz, amelyek a diákokkal, szülőkkel és kollégákkal kapcsolatban felmerülhetnek az írástudás tanításával kapcsolatban. Döntsétek el, ki fogja játszani a tanárt, és ki fogja vállalni a többi szerepet. Ideális esetben a többi kolléga megfigyelheti a helyzetet a körön kívülről, és kritikus pillanatokban „megállíthatja” azt, hogy javaslatokat tegyen.

Hogyan kezdjünk hozzá? Segítő kérdések

Nézz meg az alábbi iránymutató kérdéseket (ezek a meglévő útmutatókban szereplő kérdések és a saját kérdéseink kombinációja alapján készültek [a könyv 104. oldalán található attitűdskálából és a 98. oldalon található értékelési folyamatábrából]), és gondold át a saját álláspontodat:

1. Korlátozni akarom a diákok GenAI használatát? Ha igen, mi pontosan az oka ennek?

2. Hogyan fogom biztosítani, hogy a diákok elsajátítsák az alapvető készségeket és ismereteket? (Ne feledd, hogy a nemrégiben kialakított munkamódszerek és tanulási módok teljes visszafordítása, azaz minden esetben a toll és papír használatához való visszatérés végül demotiválja és elidegeníti a diákokat.)

3. Ha elfogadom, hogy a diákok mindenképpen használni fogják az MI-t, hogyan tudom azt integrálni a tanulásukba? Milyen ember-MI együttműködést képzelek el?

4. Hogyan fogja befolyásolni a generatív MI használata az értékelési gyakorlatomat? Hogyan fogom átalakítani a meglévő feladatokat, és hogyan fogom ezt közölni a diákokkal?

5. Hogyan szeretném, ha a diákjaim elismernék az MI használatát?

6. Hogyan fogom biztosítani, hogy kritikus, etikus és felelősségteljes módon használják az AI-t? Hová fordulhatnak további útmutatásért?

7. Mi fog történni, ha gyanítom, hogy egy diák GenAI eszközöket használt a munkájában? Mi lesz az eljárás? És mennyi használat a már túl sok?

Hogyan kezdjünk hozzá? Meglévő sablonok

TeachAI

Az abszolút legjobb és legátfogóbb útmutató, amit ismerek, a TeachAI AI Guidance for Schools Toolkit-je. Ez tartalmaz mindent, amire szükség lehet, az MI megértésétől és bemutatásától kezdve, a korábban említett nehéz témákkal kapcsolatos irányadó kérdéseken át, a mintakézikönyvekig és a szülőknek szóló beleegyező levelekig.

A TeachAI továbbá az AI-ismeretek elsajátítását támogató megközelítést követ, vagyis az MI felelősségteljes, etikus és célszerű használatát szorgalmazzák.

Összeszedtem a leghasznosabb linkeket:

• Szerkeszthető Google dokumentum sok irányadó kérdéssel, az MI oktatási rendszerbe való beépítésének keretrendszerével és sok példával (útmutató, levél a szülőknek, levél a személyzetnek, diákok beleegyezése)

• MI az oktatásban című prezentáció: ez a ppt kulcsfontosságú és közérthető üzeneteket, legfrissebb statisztikákat és alapvető háttérinformációkat tartalmaz az MI-ről az oktatásban

• MI az oktatáspolitikában című beszélgetési témák

• Gyönyörű infografikák több témáról, pl. a mesterséges intelligencia a munkaerőpiacon, az EU mesterséges intelligencia törvényjavaslatáról szóló feljegyzés, és mi is az a mesterséges intelligencia?

Microsoft

Egy másik útmutató, amit érdemes megosztani, a Microsoft osztálytermi/tanulmányi szerződés sablonja. Emellett egy eszköztárat is kínálnak a generatív MI biztonságos és felelősségteljes használatához.

Stanford Egyetem

Ez az oldal hasznos lehet azoknak a tanároknak és egyetemi oktatóknak, akik saját szabályzatot szeretnének összeállítani. Bár eredetileg csak oktatók számára készült, megbeszélhetjük közösen a diákokkal is. Még egy feladatlapot is készítettek, amelyben olyan példamondatok és példakérdések találhatók, amiket egy MI chatbotba berakva MI segítséggel állíthatjuk össze a szabályzatot.

A mi könyvünk

Könyvünkben is szerepel egy feladat, amely segít az AI-magatartási kódex közös kidolgozásában. Ezt a feladatot a 3. fejezetben, a 61. oldalon találjátok.

Biztos vagyok benne, hogy még sok más útmutató és sablon létezik. Írjátok meg kommentben, melyiket ajánlanátok!

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* Ez a poszt eredetileg angolul íródott. A DeepL fordító segítségével fordítottam le, majd én magam dolgoztam át. *

Why should I care about an AI policy?

Good question. A policy by itself won’t solve all your problems. It also won’t guarantee that your students throw their phones in the trash and start writing long essays with a smile on their faces.

What it can do, however, is lay down some clear(er) guidance and position your classroom or your school on the attitude spectrum toward using Generative AI in teaching and learning.

A lack of such a policy essentially signals to your students that there is no clear consensus (at least in your institution or classroom) regarding many crucial points of using GenAI, such as data protection, copyright, learner autonomy, the question of originality, and critical thinking. And this in turn means that teachers will take largely different routes (i.e., reckless freedom due to ignorance or carelessness vs. complete prohibition due to ignorance again or fear), which will probably negatively affect students during their studies.

What’s the point of co-creation?

Such a technology, which is complicated and murky even for those who seem to understand it, inevitably divides people (school administrators, teachers, students, and their parents), especially when on the surface they have different agendas.

A one-sided policy will only satisfy one of these groups and will leave the others disappointed and misrepresented. With a collaborative approach, everyone can see how the other side views the question. And that will hopefully help them come up with a code of conduct that satisfies all of them.

Two role-play activities from our book, AI Literacy in the Language Classroom, is perfect for laying the groundwork for such a discussion and collaborative brainstorming session:

Perspectives hot seat (p.97): this activity helps explore different stakeholders perspectives on using AI through role-play. Sit in the hot seat, facing the group, and act in your chose role. Answer questions from the group about your concerns or reasoning, ensuring you stay in character. As a group, reflect on the insights gained about each stakeholder’s perspective. Brainstorm ways to address relevant concerns arisen during the role-play.

Scenarios (p.97): this activity encourages you to role-play and analyze scenarios that may occur with students, parents and colleagues related to teaching for a literacy. Decide who will play the teacher, and who will take on the other role or roles. Ideally, other colleagues could observe and “pause” the scenario at critical moments to provide suggestions.

How to get started? Guiding questions

Take a look at this list of guiding questions (a combination of ones in existing guides and those of our own [taken from our attitude scale on p. 104 and the assessment flowchart on p.98 in the book]), and think through your position:

1. Do I want to limit students’ GenAI use? If yes, what exactly is my reason for doing so?

2. How am I going to ensure that students learn foundational skills and knowledge? (Remember that doing a full 180 on previously established work and study modes, i.e. going back to pen and paper in all cases will eventually demotivate and alienate students.)

3. If I accept the fact that students will use GenAI no matter what, how can I integrate that in their learning? What sort of human-AI collaborative work do I envision?

4. How is their GenAI use going to affect my assessment practices? How am I going to redesign existing assignments and how is it going to be communicated to students?

5. How do I want my students to acknowledge their use of AI?

6. How will I ensure that they use AI critically, ethically, and responsibly? Where can they turn for additional guidance?

7. What’s going to happen if I suspect that a student has used GenAI tools in their work? What can actually happen? And how much of this use is already too much?

How to get started? Existing AI policy guides

TeachAI

The absolute best and most comprehensive guide out there I believe is TeachAI’s AI Guidance for Schools Toolkit. It has everything that you could possibly need from understanding what AI is and demonstrating it to other stakeholders, through guiding questions with regard to all the previously mentioned difficult topics, to sample guidances and letters to parents.

They also follow a pro-AI literacy approach, meaning they are for using GenAI in a responsible, ethical, and purposeful way.

I’ve collected their most useful links here:

• Editable Google Doc with lots of guiding questions, a framework for incorporating AI into the education system, and lots of samples (guidance, letter to parents, letter to staff, student agreement)

• AI in Education presentation: this AI in Education slide presentation provides key messages, latest statistics, and essential background on AI in education

• AI in Education Policy talking points

• Beautiful infographics about several topics, e.g. AI in the workforce, EU AI Act memo, and what is AI?

Microsoft

Another one I think is worth sharing is Microsoft’s Classroom Agreement template. They also offer a toolkit on unlocking generative AI safely and responsibly.

Stanford University

This page could be useful for teachers and professors who are aiming to put together their own policies. Even though it’s meant to be used by the educator only, you can still share it and discuss it together with student. They have even prepared a worksheet with sample lines and also sample prompts so that you can ask an AI chatbot to help you draft the policy.

Our book

We have also prepared an activity in our book that helps you collaboratively prepare an AI code of conduct. Look for this activity in Chapter 3, on p.61.

There are many more out there, let me know which ones you’d recommend!

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First, I always read what the much quicker and keener testers have got to say (who also tend to have access to the paid versions, too). I follow Darren Coxon, Amanda Bickerstaff from AI in Education, Leon Furze, and Philippa Hardmann. After all, I can’t test everything all at once and I don’t have the time :)

So, what I can see from these hot takes so far is that this new release isn’t as impressive as it promises to be. While its main message and promise is “thinking” it doesn’t really seem to be doing what we’d consider thinking. And while the study modes (or Gemini’s Guided Learning mode) promise to study with you, they still study for you.

So I think it’s time to revisit my talk at this year’s Global Teachers' Festival for Macmillan, which takes a balanced look at GenAI tools, and tries to predict what’s going to come after the so-called Honeymoon Phase.

The never-ending hype train

Our relationship with new experiences has been described by several researchers, and they seem to follow a similar pattern. Oberg’s original four stages of culture shock (honeymoon, anxiety / frustration, adjustment, acceptance) or Gartner’s hype cycle (innovation (trigger), peak of inflated expectations, trough of disillusionment, slope of enlightenment, plateau of productivity) are some of the most famous ones out there.

These theories all say that we first get into a kind of trance because we’re so excited about the new thing. But then we slowly come to our senses, start to see the negatives along with the positives, and eventually find our balanced stance.

The problem with GenAI advancements is that this hype train never seems to end. There’s always a new model, a new release, a new feature. And what will that lead to? I’m not sure about others but my best guess is burnout.

At least that’s what’s definitely happening to me. I learned how I can use chatbots in general for my needs, I’m familiar with their main functions, so I find myself more and more difficult to be convinced that this one is THE ONE. The constant addition of new tweaks makes you tired and fatigued after a while, and you just stop caring anymore. I can definitely imagine that most practitioners feel this way.

Getting a bit too comfortable and forgetting about AI ethics

What this sort of leads to is that most teachers get a bit too comfortable with how they use GenAI tools. After all, “If the chatbot can do it, why shouldn’t I do it?” - you might think.

But after almost 3 years’ of chatting away with ChatGPT and co., we should really start meeting the standards of ethical, responsible, and critical use. Let me show you a couple of beliefs teachers might still hold but which should be reconsidered asap.

1. Using a chatbot for every single thing

Yes but we need to pay attention to the huge environmental impact of using GenAI for every single possible thing. Let’s try and think first about what we could do without it and only use it when we really need it.

The other downside of overuse is the slow deterioration of our creative thinking capabilities. If we don’t even try to rack our brains at least for a second, which is a muscle after all, we’re going to find it harder and harder to do some cognitive work.

That’s one of the reasons why ChatGPT now has Study mode and Gemini has Guided Learning. The developers have also noticed (or business analysts told them to pretend that they noticed it) that adding a couple of layers before giving you the answer straight away might lead to better understanding and higher retention.

But then again, we now have a thing called “zero click internet”, which means that you don’t even have to click on a search result to find the answer to your question, Google AI search answers the question right away. That’s not going to help you develop your critical thinking skills, is it?

2. Uploading whatever you can into the chatbot

I couldn’t believe my eyes but I can still find websites that listed prompts that suggest you upload entire books to get summaries, multiple choice questions, study guides and so on.

That’s not a problem per se, Google Notebook LM offers this service in a neat package, too. The problem is if you upload copyrighted material. So make sure you upload open source texts only!

The other thing to pay attention to is data protection. Don’t upload anything that contains sensitive or personal data, such as doctor’s notes, personal photos, contracts, etc.

3. Getting two machines have a nice chat

There are so many memes about this! Not without a reason. And that’s actually the part that makes me feel a little happy inside - because I think this could finally shed some light on the hypocrisy of our daily lives.

Most of what we do is just a ritual. And instead of doing what matters, we dance around it in circles, wrapping all of it into nice costumes of irritatingly long and complicated texts. So, what I’d do personally is get rid of whatever seems to be done only to get some boxes ticked (for example, essays without a real and authentic purpose).

What’s going to come in 2026?

Good question, really :D No clear idea yet but these are my guesses:

• GenAI tools trying to dominate a big chunk of education - private and state, and trying to shape the way we learn.

• Instructional design is also going to make use of AI practitioners in various ways. The question is whether human and AI will be able to work together in innovative ways or whether we’re going to let AI take the lead.

• Teachers will slowly lose interest in the new releases and trends, so their AI use might need readjustment and recalibration.

• Publishers might start including GenAI features into their ebooks and classroom e-packages to let students and teachers customise the material on the go, right in the classroom.

• Connected to this previous point, highly personalised and better quality AI-generated learning content might appear within language learning apps.

• There is going to be an even greater need for critical thinking skills, which will hopefully help us weed our way through all the deepfakes and other fake information that already started to proliferate in social media.

• And of course something that’s already out there but I still have little clue about how it’s going to crash the gates: agentic AI. An AI agent can basically solve complex tasks autonomously. It can create a series of actions, which it can then carry out, and finally present the end result to you while you have been taking a nap.

What do you think the trends will be in 2026?

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You can also watch the recording of my talk here.

The question is indeed a rhetorical one because it’s hard to say. The fact that now everyone is capable of designing their own activities might mean that course books become less of a go-to choice (to be honest, I don’t remember the last time I used a course book for teaching but it’s true that I mostly do corporate classes or one-to-ones).

Also, I guess the more tailored and more up-to-date your materials are, the less you’re going to want to buy published materials. But I think in institutional settings, books will remain a staple for longer to provide consistency and reliability to the stakeholders (parents, students, clients).

But my real proposition is that publishers will have to step up their game to stay in business, because the competition might not come in the form of self-published EFL teachers but in the form of declining demand. The bigger the company, the slower it can adapt to changes and the less likely it can include more diverse topics.

Who owns what in the world of AI-generated content?

Still, if we take freelance teachers designing their own materials and thinking about copyrighting and selling them, can this actually be done legally?

I looked at the Terms of Use of several AI generators, and this is what I’ve found. It’s definitely not a complete list but we can still draw some conclusions from it.

Text generators

I checked OpenAI and Anthropic, and regarding user input, they say that the user should make sure they own the rights to all the content they upload into the chatbots. This means that it’s your responsibility to make sure that what you use as input is entirely yours. So, pay attention not to upload or type in any already published or copyrighted materials.

Regarding output, both companies say that if you co-created something with ChatGPT or Claude, you are entitled to all the rights, titles and interest that come with the generated product. In other words, you’re free to publish, own copyright to, and sell your creations as long as they are the result of a joint effort with a chatbot (it’s unclear how much of your input actually makes it unequivocally yours). This also means that if you ask for something to be created “in the style of…”, it’s not yours.

Check my conversation about this with ChatGPT here.

Image generators

Again, regarding input, Midjourney and Tengr say that you need to make sure you upload content that’s legally yours or royalty free. You also need to guarantee that you don’t upload anything that violates copyright or trademark rights or ethical considerations.

The output is entirely yours. However, Midjourney states that “if you are a company or any employee of a company with more than $1,000,000 USD a year in revenue, you must be subscribed to a “Pro” or “Mega” plan to own Your Assets.”

Song generators

While song generators, Suno and Udio, give you ownership rights (including commercial use rights) and don’t even require you to credit them if you’re on a paid plan, it’s even more complicated and controversial to decide whether the generated products are entirely unique and belong to you. But more on this later.

These generators also let you upload a sample of your own voice, which you can then use for creating songs that sound just like you. But what you need to bear in mind is that once you uploaded your voice, it belongs to the companies.

Stay safe, stay transparent

The best approach to dealing with AI-generated material is to be transparent about its use. You may want to use the following templates for this:

• Created with Midjourney based on prompt XYZ.

• This resource was co-created with the assistance of an AI language model (ChatGPT) and adapted by the author for English language teaching purposes.

• Some elements in this worksheet were developed with help from ChatGPT and refined by the teacher for classroom use.

• Image generated using Adobe Express (Premium) from the prompt brown owl in a forest. (source)

• Image generated using Dall-E from the prompt ‘futuristic cityscape.’ (source)

Artists’ fight against scraping and data mining

There have been many legal cases against various companies owning generative AI tools. Artists rightfully believe that training models on their creative works constitutes copyright infringement and, therefore, companies should either stop this activity completely or reimburse artists for all the financial damage they have caused.

The problem is that, again, nothing is black and white. Two recent cases (Bartz v. Anthropic PBC (Judge Alsup, June 23, 2025) and Kadrey v. Meta Platforms, Inc. (Judge Chhabria, June 25, 2025)) show that what seems to matter the most is whether the use of training data is transformative enough. If it is, as it was how the judges ruled in both cases, then the companies showed fair use and no copyright infringement happened. The models don’t memorize the training data in order to produce the exact same result but they learn from these texts to produce something new. I’m not sure how consoling this is to writers but I do hope that LLMs won’t be able to produce texts that are hauntingly similar to real authors’ works.

The picture is even more complicated in the case of images, videos, and audio because it’s much more obvious if similar or the same product has been generated. And there are still many ongoing cases without a clear ruling or decision. What seems to be the direction forward is to include opt-out schemes that artists can use to prevent their work from being used in training. Whether this is going to be legally binding is an interesting question.

What artists have been trying to do lately is “poison” their works. During data poisoning, “the attacker introduces misleading information, modifies existing data, or deletes important data points. The goal of the attacker is to mislead the AI into making incorrect predictions or decisions” (source). Or they can also edit the metadata to try and protect their works from copyright infringement.

Activities in our book

We’ve got several activities that deal with the gray area of ownership. Since the question is definitely not easy to answer, these activities include lots of discussion and debate.

Buy the book!

Plagiarism or not?

Students need clear guidance on using AI tools responsibly for schoolwork without unintentionally cheating. In this activity, students review a list of possible ways to use AI in their studies and decide which are acceptable and which aren’t. This is followed by a class discussion on ethical use, fairness, and originality.

Who owns it?

This activity encourages students to think critically about the consequences of using AI to generate ‘creative products’ such images, music, or text. By engaging in debate, students will explore important concepts such as copyright, intellectual property, and what should be available for everyone to use for free.

What could go wrong if…?

Sometimes, it is hard to realise how small actions, like uploading private or copyrighted documents online, can lead to illegal or harmful misuse. This activity helps students understand the risks of uploading fi les that shouldn’t be shared or asking unethical or unsafe questions to an AI chatbot, such as how to print money.

This was my very first time in the Metaverse, and it was definitely a shocking experience :D but I’m glad I could deliver my talk in a shortened form!

You can access the entire presentation by clicking here.

I want my assessment to make sense, so first, what I want to create is a valid and reliable test.

A valid test measures what it's supposed to measure. The reading my students have to do for next week is about Lexical Chunks in English Language Teaching. If I ask about anything else that's not related to the topic or that's not in the reading, my test is not valid.

A reliable test should provide consistent, replicable information about the test takers' performance. If there's high inconsistency in who takes the test, when or where they take it, or who assesses them (typical case of strict teacher in a bad mood vs nice and lenient teacher), then the test is unreliable.

Question types - time to create vs. time to evaluate

Something that we can easily agree on is that there seems to be a tendency that questions that are easier to create take longer to evaluate.

For example, it's much easier to come up with an open-ended question that asks students to reflect on their reading but it takes much more time to read everyone's answers and to provide reliable and consistent feedback.

The typical issue with open ended questions is that it's hard to define what makes someone's response a 10 out of 10, or a 7, or a 4, and so on. What you'd really need in this case is a well-designed rubric that explains each and every criterion and provides a score for various performance levels (e.g., unsatisfactory, satisfactory, excellent). But that's a lot of work!

There are question types which are much easier and quicker to grade (closed questions, such as multiple choice, multiple selection, matching, true or false) but they are typically more difficult to produce. Why? Because you still want to create a valid test.

If the wrong answer options are too easy to spot or the whole question is too easy to answer, then what's the point of the test? So, you need to think hard to come up with the right distractors, which are plausible but still incorrect.

Question types - authenticity vs. reliability

We can look at the issue above from a slightly different perspective. If I ask open-ended and personalised questions, then I will probably get more authentic answers that truly show not just whether my students understood the main concepts but also if they can apply this knowledge. However, there is the problem of reliable grading. How do you decide if one student's answer is more creative than another's? Or do they get the same score for saying something creative? Where do you draw the line between average and above average?

OK, let's do closed questions. They are super reliable, they are quicker to grade (which means less workload for you), but the questions are not very authentic, and they don't tell you much about your students' understanding. These tests typically just scratch the surface.

So, your best option would be to include both types.

Test creation

1. Starting out

First, I acted as a traditional teacher. I read through the entire article and tried to come up with my own questions. Based on the previous points, these were my guiding principles:

• no questions about people's names, publication dates and other such data, as these are at the lowest of Bloom's taxonomy (remembering), and they don't really serve a real purpose in terms of understanding

• mostly closed questions because I want this quiz to be machine-graded but I might still include one open question to learn more about my students' knowledge

• if closed questions, then I will choose from multiple choice, multiple selection, true-false and short answer questions

• short answer questions are best if the answer is indeed short (1-3 words), otherwise you have to provide all kinds of possible answer options (capital vs. lower-case, word order, with or without linking words, punctuation...), and that takes a lot of time and forward-thinking

• multiple choice and multiple selection questions require good distractors that are sometimes difficult to come up with

2. (How) Can AI help?

So, I drafted my own questions and answer options, then used 3 AI tools (Quizbot, Quizgecko, ChatPDF) to do the same for me. I used their free versions. These are the things I noticed:

2.1. Speed!!!

AI generated quizzes are a dream! You upload the file (if the free version lets you) or paste the text (character limits are in place), select the age level, the difficulty, the language, and the number of questions, and bam! They generate questions in seconds and provide the answer key as well.

2.2. Closed question types

The free versions typically give you closed questions only (and within that category, multiple choice). But the questions are not bad and the wrong answers are also not blatantly wrong. Quizbot definitely won this round because it not only gives you complete answer feedback but the questions are more complex (Quizgecko asked some simple fact-recall questions). It also has more options for question creation, including questions from video or picture input, Bloom's taxonomy-ready questions, and Gardner's Learning Style-ready ones.

2.3. Open ended questions

As I already said, I would like to include at least one open-ended question too, so for that I got inspiration from ChatPDF, which came up with pretty good complex questions.

2.4. Teacher revision is a must

After all this work, the most important thing I'd add is that without your revision as a teacher, you might end up with a weak collection of questions. They won't be bad because they all focus on the content of the reading and are relevant. But they might grasp something different from what you think is important. Or there's still the possibility that they misunderstand something.

UPDATE: Thank you, Julie Moore, for pointing out that in the Quizbot test, in question 4, both b) and c) could work. And while this is true, the text only contained information about c), so AI thought that nothing's wrong. That's why double-checking is super important. I really like Jules's comment: "a proper editor is always invaluable ... however the content was created."

Conclusion

I would never hand out an AI-generated quiz without actually reading the text myself and double-checking all the questions and answers. However, I'm definitely going to work together with such tools because they are so much quicker in generating answer options, which I'm the slowest at. And I think I might buy the premium subscription for Quizbot.

Further reading:

https://www.thoughtco.com/blooms-taxonomy-questions-7598

Wei, L. 2013. Language Assessment. Applied Linguistics. Wiley Blackwell.

Chiappini, R. (author), Szoke, J. (consultant), Taylor, L. (consultant) (2025). The Impact of Assessment on Teaching and Learning: creating positive washback [PDF]. Oxford University Press. https://elt.oup.com/feature/global/expert/positive-washback

Title: Lesson planning and materials writing with AI

Place: online

Time: July 17, 9:30-11:30 (GMT-3)

Blurb: In this short but content-rich session, we’ll explore some practical examples of how Generative AI can help us create up-to-date, personalised, differentiated, and interactive materials. Of course, there’s always another side to every story—so we’ll also highlight key concerns around copyright, AI ethics, built-in biases, and data safety. We’ll end with a glimpse into the future: What does AI mean for the ELT publishing industry—and where do teacher-writers fit in?

More info and registration

September 23: Klett Sprachen webinar

Title: AI Literacy in the Language Classroom

Place: online webinar

Time: September 23, 17:00-18:00 (CET)

Blurb: In this workshop we`ll explore how AI literacy development can be integrated into English lessons with upper primary, secondary and adult students. Following a quick, 3-minute introduction about what AI literacy is, we`ll be trying out fun, practical activities, all taken from the book AI literacy in the language classroom, published by DELTA Publishing. The activities focus on different areas of AI literacy, such as critical use, ethical use, and understanding the future implications of AI technologies.

Register here

October 3: The 2025 Freelancers’ Awayday

Title: Tech with purpose: making it work for learning

Place: Oxford, voco® Oxford Spires Hotel​

Time: October 2, 10:10-10:40 (GMT+1)

Blurb: In this interactive plenary talk, we’ll explore the many roles technology can play in and beyond the classroom. The key question is not whether we should use technology or AI—but how we can use it meaningfully and critically to support learning. This session invites educators and publishers alike to revisit digital tools with a fresh lens: moving beyond buzzwords and flashy design to focus on the purpose these tools are meant to serve.

Programme and registration

October 16: Klett Sprachen webinar

Title: AI Literacy in the Language Classroom

Place: online webinar

Time: October 16, 17:00-18:00 (CET)

Blurb: In this workshop we`ll explore how AI literacy development can be integrated into English lessons with upper primary, secondary and adult students. Following a quick, 3-minute introduction about what AI literacy is, we`ll be trying out fun, practical activities, all taken from the book AI literacy in the language classroom, published by DELTA Publishing. The activities focus on different areas of AI literacy, such as critical use, ethical use, and understanding the future implications of AI technologies.

Register here

October 18: VI. Oktatásinformatika konferencia és szakkiállítás (HU)

Cím: MI vagy mi? - Az MI válaszainak értő használata az egyetemen

Helyszín: Reviczky utca 6., Budapest, Hungary

Időpont: 15:30 - 17:00 (CET)

Leírás: A mesterséges intelligencia válaszai sokszor meggyőzőek – de vajon ugyanolyan megbízhatóak is? A workshop során kritikus szemmel vizsgáljuk meg az MI által generált tartalmakat: felismerjük az esetleges torzításokat, utánanézünk a chatbotok által használt forrásoknak, és kialakítjuk a hatékony együttműködés alapjait. Célunk nem elutasítani vagy vakon követni, hanem tudatosan és megalapozottan használni az MI-t az egyetemi tanulmányokban és a kutatás világában.

Regisztráció

The Impact of Assessment on Teaching and Learning: Creating positive washback, written by Riccardo Chiappini, lets you explore research on how testing and assessment shape classroom practices, and gives practical guidance on how teachers can prepare their students for exams.

Download the paper

It also comes with a practical toolkit, written by ME 🤩 😄, which contains 5 printable activities you can immediately use in your classroom:

1. Quality and quantity checklist

2. AI-powered speaking practice

3. My language learning journal

4. Quest cards

5. Persuasive project: 'We want change'

Download the toolkit directly

0. Planning essentials

Something to already jot down on your running order are two/three important stages of the lesson. One tends to get way too much spotlight, while the other is usually completely forgotten. I’m talking about warmers, lead-ins, and coolers (or reflection stages).

Warmers as energy meters

Every lesson is better with a warmer, which basically helps students feel at ease in your lesson, in your space. This is when you can connect to them a bit and gauge their energy levels by asking a couple of questions about how they are. Try to make this short stage genuine and meaningful, and do listen to what your students have to say.

Keep lead-ins short and to-the-point

A lead-in then, as the name suggests, leads students to the next stage, which is the main activity. Again, don’t forget this stage because it makes the lesson flow naturally without any abrupt changes. Lead-ins usually start from a wider perspective: they pose general questions in connection with the topic or they introduce words that are probably new but important for the task. But don’t make them too long. They’re there to support, not to take the main stage.

Coolers are more than just a “goodbye”

This happens to me almost every single time no matter how many blog posts or lecture slides I write about the importance of coolers: I simply forget about them. I get so caught up in the moment that this stage completely slips my mind. But a cooler or reflection stage has a good reason to be in your lesson. They let students calm down, take stock of what they’ve learned, and retain new information a bit longer than 10 seconds.

And with these stages, you already have about 15 minutes from a 45-minute lesson! Now let’s see the my go-to main activity types!

1. Variations on dictation

Dictation can be great to improve multiple skills at once. It activates listening skills, memory, writing skills (including spelling, coherence, and cohesion), reading skills (=making sense of what you’ve written), and speaking skills.

Opinion dictation

The way I’ve learned to play this game is:

• Ask students to draw a table like the one below. Make sure the cells are big enough to write in.

• Tell students that they’re going to hear a number of statements twice. They need to decide how much they agree with these statements. They should note down maximum 3 key words from the statements and put those key words into a box on the disagree-agree scale. They cannot write complete phrases or sentences.

• Once you’ve read out the statements, put students in pairs or small groups and ask them to try and reconstruct the statements from the words they have written down. They should try and make them sound as much like the original ones as possible.

• When they think they have the statements, ask them to discuss why they decided to agree or disagree with them.

• Finally, check the statements in open class by asking students to read out their versions. Let them argue about various ways of phrasing the statements before showing them the actual sentences.

• Variation: You can also have students prepare and read out sentences to each other in smaller groups.

Running dictation

• You will need a text that you cut up into shorter sections. These should be around 1-2 sentences long.

• Place these cards around the room. Make sure they’re not easy to read from a distance.

• Put students into pairs. One of them will be the scribe, while the other is the runner. They can switch at half time.

• Runners will have to run around the room, read what’s on the cards, try and remember as much as possible, run back to their pairs, and dictate everything they can remember. It’s important that they cannot shout across the room.

• Scribes have to write down whatever they get from the runners. They can ask for clarification.

• Once the pairs are done, they can sit down and start making sense of the sentences they’ve written down. They need to make sure the text makes sense, everything’s spelled correctly and is grammatically correct.

• Give them or show them the original text to let them double check.

• Ask additional opinion or language-related questions to follow up the text they’ve just worked with.

Dictogloss

• This is another complex favourite. Ask students to work in pairs or groups.

• You read out a text two or three times and ask students not to write down anything but listen closely.

• When you’re done, ask students to try and reconstruct the text from memory.

• The point is not to get the exact copy of the text but something that resembles it as much as possible. What you’re actually doing with this activity is that you make students focus on the meaning of new expressions or a new grammar point rather than on the form or the rule. They’re probably not going to remember the new items but they might understand how they’re used. So they’re probably going to end up with synonymous expressions instead.

• When students are done, give them the text in a printed format. Ask them to compare their versions with the original, and highlight anything that’s new or different.

• Follow up this part by asking them what they think the highlighted parts mean and what the rules are. This can then lead into a vocabulary or grammar-focused lesson.

2. Pyramid discussion

This is basically a simple speaking activity that can go on forever 😄. Another name for it is “snowball discussion.”

• You will need something that needs to be organised or agreed on, like a birthday party, office restructuring, school renewal, what to bring on a desert island etc.

• Ask students to work in pairs and come up with a number of ideas (let’s say 5) for organising whatever needs to be organised. Give them 5-ish minutes.

• When they’re done, put two pairs together, and ask them to share their ideas with each other. Make sure to ask them to agree on a limited number of ideas (6 or 7). Which means they will have to agree, compromise, and reduce their 10 ideas to fewer.

• When they’re done, put two groups of 4 together, and repeat the previous stage. More ideas, more arguments, more negotiations follow. And this could basically go on forever or until you run out of students.

  

• When your entire group is now taking part in the discussion, you can still introduce further cuts to the number of ideas by having them vote on certain things. The aim is to arrive at a final idea, plan, or list. Ask students to summarise the final solution bit by bit one by one.

3. Alibi game

Such a classic! The alibi game is basically the best example of a communicative task, which means that it creates an authentic and genuine need to communicate, there is some kind of information gap that needs to be bridged, and students can rely on whatever linguistic resources they have to solve the task (so they’re technically not required to use a specific tense).

• Put students into two groups, Detectives and Criminals. Or, alternatively, select just a few (maximum 4 students) students to be criminals.

• The context is that some kind of crime (you decide) was committed the previous day. Detectives need to find the culprits, while Criminals have to craft the best alibi that no detective can break.

• Ask the Criminals to step outside of the classroom (if possible) to create their bulletproof alibi. At the same time ask the Detectives to come up with a list of good and cunning questions that could catch the Criminals.

• Ask the Criminals to come back. Create two mixed groups: a number of Detectives with a couple of Criminals twice.

• Let the Detectives interview (=roast) the Criminals for about 10 minutes. If you have time, you can also ask the Criminals to switch between the two Detective teams and have another round of an interview.

• Once the interviews are over, ask the Detectives whether they have found any convincing evidence that the Criminals committed the crime. If their arguments don’t match up logically, they have failed and the Criminals have won. But if the Criminals have been telling different stories and their alibis don’t match up, they have lost.

Let me know what your favourite go-to activities are in the comments!

Leave a comment

Sources and further reading

• Methodology: using dictation in English language teaching by Tim Bowen

• Running classroom dictation activity by Anthony Tyrrell

• 101 low-prep ideas for exploiting coursebook activities by Sandy Millin

• Three Low Prep Ideas to Liven Up Your Class by Jo Gakonga

• Adapting the alibi game by Mike Astbury

…you may wonder. Well, we’re wondering it, too.

Nobody really knows, and that’s the scary part. The other scary part is that during the industrial revolution, machines took many blue collar jobs by automating lots of tasks. It sparked a number of angry responses like uprises and revolutions, but the sad thing is that since the ruling and more well-off classes weren’t affected, nobody really cared. But now the machines are coming for the white collar jobs. Jobs that we thought could never be replaced by anyone or anything because human qualities have been necessary for them to be performed.

Watch this TikTok video by caroline_easom that illustrates this kind of fear.

But is AI really going to take our jobs?

That’s a good question. And that’s what the activity “AI in my future job” in our book is about! Students get to do some research and think critically about how AI is going to affect certain jobs, professions, and the entire job market.

One side hopes (we’re part of this team) that with certain adjustments, we can still remain important, and AI is only going to serve as an assistant. It may also perform repetitive and menial tasks, leaving the more creative and complex parts to humans.

But the other side (they have really good arguments, too) believes that if AI is so good at generating ideas and creative products, finding the main point in long texts, analysing data, predicting future outcomes, and making sense of things, then what else is left for us to do?

I still want to be hopeful. But I’m also realistic and I know that there are certainly going to be changes in the very near future in the way we work and what we do for work.

The project

In this project task, students work together in groups to do some research on how AI is going to affect future professions and the way we work. Some guiding questions they can follow are:

1. Which jobs will disappear due to AI, and which new jobs will be created?

2. How will AI change the way people work day-to-day?

3. What skills will be most important for workers when AI handles routine tasks?

4. Will AI do all the jobs and universal income become a thing?

5. How can students prepare now for jobs that don't exist yet?

They have the chance to use various AI tools in the process:

• chatbots to find information (ChatGPT deep research, Perplexity, Gemini deep research…)

• to generate posters, infographics, visualizations and presentation slides (Gamma, Canva, Napkin)

• to generate voiceovers, videos (Elevenlabs, HeyGen, Synthesia)

And here’s the poster!

In action

We’re actually going to test this project in a couple of weeks with some motivated teenagers who take our AI literacy course at Engame Academy Hungary. Come back for the updates to see how it went!