Papers on AI in education are two a penny at the moment, but there’s a particularly nice one that appeared recently in Frontiers in Education (30 Sept 2025). It takes a fresh look at AI-generated, scenario-based conversation practice for university EFL learners – one of perhaps the most obvious and widespread use cases for AI in language learning, but given a smart, systematic treatment by a team of scholars from Saudi Arabia, China and Pakistan.
The gist is simple: build realistic speaking scenarios with AI, let students interact in them over a term, and see what happens. Over 18 weeks with 130 first-years split into control vs. AI-scenario groups, the AI cohort came out ahead on pronunciation, accuracy and conversational flow. They also reported higher interest and better teacher–student interaction to boot.
The catch? Emotional thinness in AI dialogue, patchy content quality if you don’t curate, and a risk of learner over-dependence on the tech.
So, what can we pinch for our own learning? Well, the paper itself is full of useful nuggets and worth a careful read. But here are some key takeaways for avoiding “AI for AI’s sake” based on the team’s findings.
1) Make your speaking tasks scenario-first, not tool-first.
Before opening any chatbot, sketch a brief: Where am I? Who am I? What’s my goal? What counts as success? That mirrors the paper’s “input → interaction → output” design and stops generative models meandering (always an occupational hazard worth mitigating against).
2) Bake in “flow nudges”.
The study’s gains in conversational flow suggest prompts that push you to repair, clarify and keep turns moving. Add rules to your prompt like: “If I give a short answer, ask a natural follow-up; if I stall, offer two options.” That keeps the exchange discursive rather than Q&A-ish.
3) Add in a feedback micro-loop.
The report notes improvements in pronunciation, which is fine if you’re using AI in voice mode. If not, replicate that with a regular mini-feedback cycle that gives short explanations for tricky words of phrases.
4) Curate, don’t just generate.
A recurring warning was inconsistent or culturally off-kilter content when left unchecked. Make sure to describe your scenario frames in terms of function, time and place (e.g., returning a faulty purchase in Athens; arranging a GP appointment in Lille).
5) Add a human(-like) layer to keep things warm
Students benefitted from richer teacher–student interaction around the AI tasks. Translate that to solo study by doing a quick human check: post one 60-second recap to a study buddy, social feed or tutor each week. This ‘social accountability’ step compensates for the AI’s limited emotional range. Try recording the dialogue afterwards as a voice note, too, for some added spoken practice.
6) Watch the dependence trap.
The authors flag tech over-reliance. Give yourself “AI-off Fridays”: repeat a scenario from memory with real materials (voice notes, a friend, or even talking to your phone camera), then compare to your AI-assisted version for gaps.
AI in Practice
Bringing all that together, here’s a ready-to-use mini-format you can try for a 15-minutes role-play practice that isn’t crow-baring AI in for no real gain:
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Minute 0–2: Choose a vetted scenario card (place, role, goal, 3 key phrases).
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2–3: Prime the bot with constraints (stay in A2/B1, insist on follow-ups, correct only one thing per turn).
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3–10: Converse. Every third turn, ask for a meaning / explanatory nudge on one tricky word or structure.
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10–12: Bot summary with 3 personalised upgrade lines you could have said.
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12–15: Record a no-AI voice note version. Park it for a weekly human warm-layer check.
Pastable Prompt
We’ll do a short scenario-based speaking practice in French.
Follow these rules carefully:
1. Keep the level at A2–B1 CEFR.
2. Always stay in character and make the conversation feel natural – imagine we’re really there.
3. Insist on follow-up questions whenever my answers are too short or unnatural.
4. Correct only one thing per turn, briefly and gently, then move on.
5. Every third turn, give me a short “💡 Language note” explaining a tricky word or structure that came up.
6. After about 20 lines or so of dialogue (ideally when the conversation draws to a natural close), give a performance summary, including what I did well, some ‘upgraded’ versions of my sentences showing how I could sound more natural or advanced, and 2-3 new phrases worth learning from this conversation.
7. Keep the tone friendly, realistic, and mildly humorous if it fits the setting. When ready, start the conversation by greeting me in the target language and setting the scene.
The bottom line is that AI role-plays can be genuinely useful when we design around them: scenario first, small feedback loops, and human warmth stitched back in. Treat the model like a scene partner with good timing but flat affect, and you’ll harvest the fluency gains without outsourcing your judgement.
The paper’s results are encouraging; its realistic caveats are a gift that ground us back in practical realism. As always, build guardrails into your AI usage first of all, to ensure that you get the most from – and enjoy – the chat!