AI is revolutionising every industry, and language learning is no exception. AI tools can provide students with unprecedented access to things like real-time feedback, instant translation and AI-generated texts, to name but a few.
AI can be highly beneficial to language education by enhancing our students¡¯ process of learning, rather than simply being used by students to ¡®demonstrate¡¯ a product of learning. However, this is easier said than done, and given that AI is an innovative tool in the classroom, it is crucial that educators help students to maintain authenticity in their work and prevent AI-assisted ¡®cheating¡¯. With this in mind, striking a balance between AI integration and academic integrity is critical.
Generative AI tools such as ChatGPT and Gemini have made it easier than ever for students to refine and develop their writing. However, these tools also raise concerns about whether submitted texts are student-produced, and if so, to what extent. If students rely on text generation tools instead of their own skills, our understanding of our students¡¯ abilities may not reflect their true proficiency.
Another issue is that if students continue to use AI for a skill they are capable of doing on their own, they¡¯re likely to eventually lose that skill or become significantly worse at it.
These points create a significant ethical dilemma:
There are many ways in which educators can integrate AI responsibly, while encouraging our learners to do so too.
No task can be completely ¡®AI-resistant¡¯, but there are ways in which teachers can adapt coursebook tasks or take inspiration from activities in order to make them less susceptible to being completed using AI.
For example:
Depending on the policies in your institution, if you can use AI in the classroom with your students, they will see that you know about different AI tools and their output. A useful idea is to generate a text as a class, and have students critically analyse the AI-generated text. What do they think was done well? What could be improved? What would they have done differently?
You can also discuss the ethical implications of AI in education (and other industries) with your students, to understand their view on it and better see in what situations they might see AI as a help or a hindrance.
Sometimes, students might turn to AI if they don¡¯t know where to start with a task or lack confidence in their language abilities. With this in mind, it¡¯s important to help your students understand where their language abilities are and what they¡¯re working towards, with tangible evidence of learning. This is where the GSE Learning Objectives can help.
The Global Scale of English (GSE) provides detailed, skill-specific objectives at every proficiency level, from 10 to 90. These can be used to break down complex skills into achievable steps, allowing students to see exactly what they need to do to improve their language abilities at a granular level.
While AI can generate full essays or summaries in seconds, it¡¯s far less effective as a shortcut for productive skills like speaking, especially when tasks are spontaneous, interactive and happen in real time. This makes speaking one of the best areas to focus on for genuine language production in the classroom (without the use of AI).
To reflect real-world communication, we should focus on designing tasks that encourage active listening, responding to others, justifying their opinions and adapting their ideas as the conversation evolved ¨C none of which AI can do for them.
That being said, AI can be helpful for speaking preparation tasks. If students know they have a speaking class or discussion task coming up in their lesson, you could guide them towards using AI to give them some ideas for how to link their points, generate useful and functional phrases around a certain topic, or generate arguments to personalise and adapt. In this way, AI becomes a ¡®rehearsal partner¡¯ rather than something students rely on.
By designing tasks that are unscripted, authentic and collaborative, we shift language production into real-time, boosting confidence, building fluency and helping students to develop their speaking skills authentically.
AI is here to stay, and its capabilities will only improve from where they are now. This will inevitably give rise to more and more ethical considerations as time goes on. With that in mind, educators and institutions should begin to shape its role in language learning and understand that the key question should not be ¡®Should AI be allowed?¡¯ but rather, ¡®How can AI be used responsibly to enhance learning, while ensuring a true reflection of student ability'?
is an ELT writer and teacher trainer specialising in digital learning and assessment. She has written for various ɫèAV titles including Gold Experience, Roadmap, Rise and Shine and PTE Expert, and is a regular item writer for the PTE-Academic exam. Alongside materials writing, she delivers international teacher training sessions and workshops and is the founder of the professional development platform and providing AI expertise to educators.
Watching films can be a great way for people to learn English. We all have our favourite movie moments and, even as passive viewers, they're probably teaching you more than you realise. Here's a selection of our favourite scenes, along with the reasons why they're educational as well as entertaining.
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Why does progression seem to slow down as an English learner moves from beginner to more advanced skills?
When presenting at ELT conferences, I often ask the audience ¨C typically teachers and school administrators ¨C ¡°When you left home today, to start your journey here, did you know where you were going?¡± The audience invariably responds with a laugh and says yes, of course. I then ask, ¡°Did you know roughly when you would arrive at your destination?¡± Again the answer is, of course, yes. ¡°But what about your students on their English learning journey? Can they say the same?¡± At this point, the laughter stops.
All too often English learners find themselves without a clear picture of the journey they are embarking on and the steps they will need to take to achieve their goals. We all share a fundamental need for orientation, and in a world of mobile phone GPS we take it for granted. Questions such as: Where am I? Where am I going? When will I get there? are answered instantly at the touch of a screen. If you¡¯re driving along a motorway, you get a mileage sign every three miles.
When they stop appearing regularly we soon feel uneasy. How often do English language learners see mileage signs counting down to their learning goal? Do they even have a specific goal?
The key thing about GPS is that it¡¯s very precise. You can see your start point, where you are heading and tell, to the mile or kilometer, how long your journey will be. You can also get an estimated time of arrival to the minute. As Mike Mayor mentioned in his post about what it means to be fluent, the same can¡¯t be said for understanding and measuring English proficiency. For several decades, the ELL industry got by with the terms ¡®beginner¡¯, ¡®elementary¡¯, ¡®pre-intermediate¡¯ and ¡®advanced¡¯ ¨C even though there was no definition of what they meant, where they started and where they ended.
The CEFR has become widely accepted as a measure of English proficiency, bringing an element of shared understanding of what it means to be at a particular level in English. However, the wide bands that make up the CEFR can result in a situation where learners start a course of study as B1 and, when they end the course, they are still within the B1 band. That doesn¡¯t necessarily mean that their English skills haven¡¯t improved ¨C they might have developed substantially ¨C but it¡¯s just that the measurement system isn¡¯t granular enough to pick up these improvements in proficiency.
So here¡¯s the first weakness in our English language GPS and one that¡¯s well on the way to being remedied with the Global Scale of English (GSE). Because the GSE measures proficiency on a 10-90 scale across each of the four skills, students using assessment tools reporting on the GSE are able to see incremental progress in their skills even within a CEFR level. So we have the map for an English language GPS to be able to track location and plot the journey to the end goal.
When it comes to pinpointing how long it¡¯s going to take to reach that goal, we need to factor in the fact that the amount of effort it takes to improve your English increases as you become more proficient. Although the bands in the CEFR are approximately the same width, the law of diminishing returns means that the better your English is to begin with, the harder it is to make further progress ¨C and the harder it is to feel that progress is being made.
That¡¯s why many an English language-learning journey gets abandoned on the intermediate plateau. With no sense of progression or a tangible, achievable goal on the horizon, the learner can become disoriented and demoralised.
To draw another travel analogy, when you climb 100 meters up a mountain at 5,000 meters above sea level the effort required is greater than when you climb 100 meters of gentle slope down in the foothills. It¡¯s exactly the same 100 meter distance, it¡¯s just that those hundred 100 meters require progressively more effort the higher up you are, and the steeper the slope. So, how do we keep learners motivated as they pass through the intermediate plateau?
We have a number of tools available to keep learners on track as they start to experience the law of diminishing returns. We can show every bit of progress they are making using tools that capture incremental improvements in ability. We can also provide new content that challenges the learner in a way that¡¯s realistic.
Setting unrealistic expectations and promising outcomes that aren¡¯t deliverable is hugely demotivating for the learner. It also has a negative impact on teachers ¨C it¡¯s hard to feel job satisfaction when your students are feeling increasingly frustrated by their apparent lack of progress.
Big data is providing a growing bank of information. In the long term this will deliver a much more precise estimate of effort required to reach higher levels of proficiency, even down to a recommendation of the hours required to go from A to B and how those hours are best invested. That way, learners and teachers alike would be able to see where they are now, where they want to be and a path to get there. It¡¯s a fully functioning English language learning GPS system, if you like.
It's 6 AM on a Monday morning. Ms. Lopez wakes up early to prepare for the day ahead. She spends the morning reviewing lesson plans, making sure everything is ready for her students. By lunchtime, she is preparing for the afternoon, grabbing a quick bite between classes... but it doesn¡¯t stop there. The school day finishes but Ms. Lopez stays late marking assignments. Finally, on Sunday night, she sits at her kitchen table, surrounded by papers, course books and lesson plans.
Does this sound familiar? You are not alone.
In 2024, ɫèAV research found that?76% of teachers spend at least one hour of their personal time on lesson planning each week, with 43% spending more than three hours. This is a lot of time that could be spent on other important tasks. Teachers need a solution that helps them plan lessons fast, is connected to their course books and is built by learning experts.
