AI-ADU: Pedagogy First | How AI Can Support Adult Learning
AI is already shaping adult learning environments. Learning platforms recommend activities and track progress, translation and speech-to-text tools are everywhere, and writing assistants are used by learners and educators alike. The question for adult educators is no longer whether AI will appear in their classrooms, but how to use it in a way that is learner-centred, inclusive and meaningful.
This article draws on Module 2 of the AI-ADU training programme. Its starting point is simple: the main question is not “Which AI tool should I use?” but “What learning need am I trying to address, and can AI help in a meaningful way?”
Used well, AI can make adult learning:
- More flexible – adapting content, pace, examples and practice activities to diverse adult learners.
- More accessible – supporting translation, speech-to-text, text-to-speech and alternative formats.
- More timely – assisting with formative feedback, revision tasks and learning resources.
- More reflective – helping educators analyse activities, anticipate barriers and improve lesson design.
Through all of this, the educator remains central: AI supports professional judgement; it does not replace it.
What does AI in pedagogy mean?
AI in pedagogy means using AI tools to support learning goals, learner needs and inclusive teaching decisions. It does not mean using AI just because it is new, replacing the educator, or letting the tool decide what learners need.
AI can support teaching in four ways:
- Tailor – adapt content, examples and practice to learner level and progress, for example by simplifying a text or offering more advanced challenges.
- Engage – create scenarios, prompts, activities and feedback that invite active learning, such as role plays and discussion questions.
- Include – reduce barriers through accessible formats, language support and flexible participation.
- Assess – support formative feedback and help identify learning needs early.
In short, AI in pedagogy is not “using a tool”. It is designing a learning process where AI has a clear educational role.
Pedagogy first: start with “Why?”, not “Which tool?”
Good AI use begins with “Why?” before “Which tool?”. Module 2 proposes a simple four-step design logic:
- Learning objective – What should learners understand, practise or produce?
- Learner context – Who are the learners? What barriers, motivations, abilities, digital skills or language needs matter?
- AI support – Which AI function could help without taking over the learning process: feedback, translation, simplification, practice, simulation or accessibility?
- Human judgement – How will the educator review, adapt and safeguard learning? Is the AI output accurate, fair, inclusive and aligned with the goal?
The tool only appears at step three. Before that, the focus is on the learners.
This matters especially in adult education. Adult learners bring life experience, work experience, personal goals and responsibilities. AI-supported activities should connect to real-life tasks, expand learner choice and self-direction, build on what learners already know, and never exclude people with lower digital skills, disabilities or language barriers. The test for every activity is: does it make learning more meaningful, accessible and learner-centred? If not, it needs redesigning – or perhaps no AI at all.
Five areas where AI can support learning
AI can support adult learning in five main areas. Each comes with tools that are already in use.
| Area | What AI does | Example tools |
|---|---|---|
| Personalisation | Adapts level, pace, pathway or practice task | Duolingo, Khan Academy, Coursera |
| Interaction | Supports dialogue, Q&A, role play and simulations; guides learners step by step | Carnegie Learning MATHia |
| Assessment | Drafts formative feedback, checks understanding, detects plagiarism | Turnitin |
| Accessibility | Creates alternative formats and removes barriers | I-STEM, Bookbot |
| Analytics | Highlights progress patterns and identifies learners at risk of dropping out | Canvas LMS, Moodle |
Generative AI adds a further layer. GenAI tutors can answer unexpected questions, give contextual explanations and guide learners through step-by-step Socratic questioning without immediately giving the answer. For teachers, GenAI can help create lesson plans, materials, feedback and classroom activities, with studies showing significant time savings without reducing teaching quality.
Whatever the tool, the adult education focus stays the same: AI should increase flexibility, relevance, autonomy and inclusion – while keeping learners active and educators accountable.
Getting started: prompting and inclusive design
Generative AI tools are guided by a “prompt”. The more specific the prompt, the more useful the result. A good prompt can:
- state the length, genre, style, tone and audience;
- ask the tool to act as a type of person, such as an experienced trainer or a critical colleague;
- stipulate the format, such as a lesson plan, a quiz or a table;
- set parameters on what to include or leave out;
- give examples of the desired output;
- be refined step by step, tweaking it with each new prompt.
For example: “Suggest places where this lesson might bottle-neck or become less engaging, and suggest alternative approaches to improve the flow of the lesson: [paste lesson plan].”
Not sure where to begin? Start small. Use GenAI as an assistant for engaging lesson starters, for exploring new methods such as visuals or scenarios for complex topics, or for differentiating materials – simplifying texts for struggling readers or adding challenges for advanced learners.
AI can also help make lessons more inclusive through Universal Design for Learning (UDL), an educational framework for flexible learning environments that accommodate individual differences. Educators can ask an AI tool to analyse an existing lesson plan and spot barriers, suggest ways to present information in several formats, propose different ways for learners to show what they have learned, and recommend assistive technologies or alternative formats.
Key takeaways
- AI is pedagogical only when it serves learning. Start from learner needs, outcomes and adult learning principles.
- The educator remains responsible. AI outputs require review, adaptation and human judgement.
- Inclusion is a design requirement. Every AI-supported activity needs accessibility and fairness checks.
A question to take away: where do your learners most need support – motivation, language, accessibility, feedback, confidence or personalisation? Try completing the sentence: “AI might help my learners by…”
This article is based on Module 2 of the training programme of the AI-ADU project “Building paths to the future” (2024-1-LT01-KA220-ADU-000255165).
Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the National Agency. Neither the European Union nor National Agency can be held responsible for them.