The ethical challenges of AI in education

Billie Jago
Billie Jago
A group of students stood around a teacher on a laptop
Czas czytania: 5 minutes

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.

How AI impacts language learning

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:

  • How does AI support learning, or does it (have the potential to) replace the learning process?
  • How can educators differentiate between genuine student ability and AI-assisted responses?

AI-integration strategies

There are many ways in which educators can integrate AI responsibly, while encouraging our learners to do so too.

1. Redesign tasks to make them more ‘AI-resistant’

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:

  • Adapt writing tasks to be hyperlocal or context-specific. Generative AI is less likely to be able to generate texts that are context-bound. Focus on local issues and developments, as well as school or classroom-related topics. A great example is having students write a report on current facilities in their classroom and suggestions for improving the learning environment.
  • Focus on the process of writing rather than the final product. Have students use mind maps to make plans for their writing, have them highlight notes from this that they use in their text and then reflect on the steps they took once they’ve written their piece.
  • Use multimodal learning. Begin a writing task with a class survey, debate or discussion, then have students write up their findings into a report, essay, article or other task type.
  • Design tasks with skill-building at the core. Have students use their critical thinking skills to analyse what AI produces, creatively adapt its output and problem solve by fact-checking AI-generated text.

2. Use AI so that students understand you know how to use it

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.

3. Use the GSE Learning Objectives to build confidence in language abilities

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.

  • Start by sharing the GSE Learning Objectives with students at the start of class to ensure they know what the expectations and language goals are for the lesson. At the end of the lesson, you can then have students reflect on their learning and find evidence of their achievement through their in-class work and what they’ve produced or demonstrated.
  • Set short-term GSE Learning Objectives for the four key skills – speaking, listening, reading and writing. That way, students will know what they’re working towards and have a clear idea of their language progression.

4. Design tasks that are not AI-dependent

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 – 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.

The path forward

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'?

About the author

Billie Jago is an ELT writer and teacher trainer specialising in digital learning and assessment. She has written for various Pearson 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 ELTcpd professional development platform and YouTube channel, providing AI expertise to educators.

More blogs from Pearson

  • Woman writing on whiteboard with two women watching her, smiling
    Writing your own English language materials with the GSE
    By Billie Jago
    Czas czytania: 4 minutes

    Being an English language teacher means you’re also probably (definitely) a materials writer. You likely tailor or create language materials for your students that are suited to their needs and interests, either as supplements to your course materials or for communicative lessons. Alternatively, you might be a teacher who creates paid, published materials available for students worldwide to enjoy.

    With this in mind, think of the materials you’ve developed and ask yourself the following:

    • How do you level your grammar or vocabulary for the content you write?
    • How do you find topic-related vocabulary to extend your students’ knowledge of language?
    • How do you contextualize new grammar or vocabulary?

    You can use many different resources, from online dictionaries to course workbooks to a Google search. Still, the Global Scale of English is a reference that provides everything you need to write great learning materials, all in one place. It can help save you valuable time as a teacher and materials writer.

    For me, the GSE was a game changer as an English teacher, and it continues to be as I write materials. The GSE is not just a tool; it’s a companion in the complex journey of material development, offering clarity and direction at every step. It can guide you in creating effective, engaging learning resources.

    How to use the GSE toolkit to create your own materials

    1. Establishing clear Learning Objectives

    The GSE helps you start with a clear roadmap. It provides detailed descriptors for language proficiency at every level, ensuring your materials align with specific learning objectives. For instance, if you’re creating a beginner-level reading comprehension activity, the GSE descriptors will guide you on the appropriate complexity of vocabulary and sentence structures.

    Take a look at the Learning Objectives tab in the GSE Toolkit to learn more.

    2. Designing level-appropriate content

    Once objectives are set, the GSE assists in tailoring the content difficulty to the targeted proficiency level. Its numerical scale, ranging from 10 to 90, allows you to pinpoint the exact level of language skills required and design your materials accordingly. This precision ensures that learners are neither overwhelmed nor under-challenged.

    You can set the level you are looking for by sliding the bar along the scale, so it corresponds to the appropriate CEFR level or GSE range.

  • Friends sat on a moving train together talking
    What is the hardest language to learn?
    By Charlotte Guest
    Czas czytania: 4 minutes

    It's incredible that thousands of languages are spoken worldwide, each with its own set of challenges for learners. A question that often pops up is: "Which language is the hardest to learn?". Today we take a closer look at this question and consider different factors that make learning a language challenging.

    What is the hardest language to learn? 

    Learning a language is a complex process that involves several components, including phonetics (sounds), morphology (word formation), syntax (sentence structure), semantics (meaning), and pragmatics (communication in context). These factors all contribute to the perceived difficulty of a language.

    Language difficulty

    The U.S. Foreign Service Institute ranks languages based on their difficulty for English speakers. Factors include similarity to English and script complexity.

    FSI Language Difficulty Rankings

    • Category I: Easiest languages (e.g. Spanish, French, Italian)
    • Category II: Moderately difficult languages (e.g. German, Indonesian)
    • Category III: Difficult languages (e.g. Russian, Hebrew, Arabic)
    • Category IV: Very difficult languages (e.g. Chinese, Japanese, Korean)

    In theory, you should also be able to apply this the other way around to work out how hard It would be for someone to learn English. But it isn't quite as simple as that in practice.

  • A man working on a laptop in a library smiling
    Are remote English tests lower standard?
    By Alice Bazzi
    Czas czytania: 2 minutes

    As digital testing becomes more widespread, a common perception still persists: that remote testing or at-home tests are somehow lower in quality than traditional test center exams. For institutions and governments, this raises an important question: does the delivery format impact the standard of assessment? 

    The reality is, the quality of the test is defined by design, scoring and security, not by location. 

    PTE Express is built on the same core principles as established English proficiency tests, including rigorous test development, validated content and standardized scoring processes. The academic integrity of the test remains consistent regardless of whether it is taken in a test center or from home. 

    In many ways, remote testing introduces additional layers of oversight. PTE Express incorporates advanced features such as biometric identity verification, AI-enabled monitoring and fraud detection algorithms to ensure that each test session meets strict security standards. These systems provide continuous monitoring and create detailed audit trails, offering institutions greater transparency into how tests are conducted and validated. 

    For US institutions evaluating large volumes of international applicants, this ensures that remote scores can be trusted to meet the same standards as in-person testing without limiting access based on geography.

    Governments also benefit from scalable, secure testing solutions that support broader participation while maintaining compliance and integrity. Agents, in turn, can confidently recommend remote testing options knowing they deliver both accessibility and credibility. 

    The bottom line 

    Remote testing is not a lower standard, but it is an evolution of English testing delivery. PTE Express demonstrates that it is possible to maintain high-quality, secure and globally consistent assessment in a fully online format.