By Keith Taynton (Learning Technology Support Officer)
We hear a lot about Artificial Intelligence transforming higher education, but what does that actually look like on the ground? How do we move from abstract potential to practical application, especially when teaching nuanced, human-centric skills? I recently had a fascinating chat with Dr. Michelle Whitworth, an academic wrestling with exactly this challenge in her postgraduate Employment Relations module. Her story offers valuable insights for any of us considering how AI might genuinely enhance, rather than disrupt, our teaching.
Michelle’s focus was clear: equipping her students with the confidence and capability to handle discipline and grievance issues. These are notoriously difficult conversations, the kind that many experienced managers never look forward to. Traditional role-play helps, but finding sufficient time and creating truly low-stakes environments for repeated practice is always a hurdle. Added to this, Michelle noted the pervasive fear surrounding AI – “If I use AI, does that mean people will think I’m incompetent in a real-world scenario and my skills inauthentic?” – a sentiment likely familiar to many staff and students alike.
This confluence of the requirements of the curriculum and understandable trepidation led Michelle to explore the AI Roleplay tools embedded within platforms like Blackboard and LinkedIn Learning. Could AI offer a safe, scalable safe area for students to hone these nuanced communication skills? The initial results were promising. Students could engage in simulated disciplinary chats or grievance hearings, testing different approaches without the pressure of performing in front of peers or their tutor.
Of course, student engagement with these tools isn’t uniform. Some students dive in readily, experimenting with different tones and strategies, pushing the boundaries of the simulation. They might quickly grasp the AI’s capabilities, discovering how it adapts (or fails to adapt) to different conversational tactics. Others might approach it more tentatively, perhaps initially treating it like a simple chatbot or feeling unsure about how ‘realistic’ the interaction should be. This range of experience is natural; students arrive with varying levels of confidence and understanding of Generative AI.
This variability highlights the importance of guidance. Students benefit from understanding that the tool allows them to safely explore consequences, for example, what happens if they take a very direct approach versus a more empathetic one? They can retry scenarios multiple times, refining their phrasing and approach without the social risk inherent in live role-play. Observing how the AI responds to these different inputs becomes a learning experience in itself, offering immediate, albeit artificial, feedback on their communication style.
However, integrating the technology wasn’t just about finding the right button to press. It sparked crucial pedagogical conversations. Michelle was clear with her students: AI is a tool for augmentation, not replacement. “There’s that message… that we’re trying to get across,” she explained, “that you can use it, but you have to assess how you’re using it and how good the information is. And the only way you can do that is if you have well-developed subject knowledge. So, ultimately it’s your knowledge that you’re critiquing and reflecting on.”
This framing is vital. It shifts AI from a potential shortcut to a catalyst for deeper learning, demanding students deploy their existing knowledge to evaluate the AI’s performance and their own interaction with it. This isn’t just about teaching Employment Relations anymore; it’s about developing essential graduate AI literacy – the ability to use these powerful tools effectively and critically.
Imagine students using the University’s Copilot AI chatbot during a lecture to clarify a concept, engaging with an AI-powered chatbot transcript after class to review key points, and then using role-play tools to apply their learning. This isn’t science fiction; it’s available now! The challenge is to weave AI digital literacy into the very fabric of the learning experience, whilst preparing students for professional contexts already grappling with AI adoption.
But simply using AI isn’t the endgame. There is a critical need for structured reflection. It’s important to have an explicit process for reflective practice. Students need prompting to consider how they used the AI, how it responded, and what they learned about both the subject matter and the process of interacting with the AI itself. Students can use AI to get feedback on their written reflections – a meta-cognitive loop with powerful potential. Learning to prompt effectively, to dialogue with these systems, is an emerging skill in its own right.
Perhaps the most encouraging part of the conversation was Michelle’s honesty about her own journey. “I am not an expert in this,” she admitted freely. “I wasn’t when I started… I am impressed and I am amazed at what it can do and that it didn’t take a lot of input from me. It took some thought as to how I was going to fit in… But it’s actually a lot more straightforward to use than I think people realise.”
This is a powerful message for colleagues perhaps hovering on the edge, unsure where to begin. Michelle’s experience suggests that starting small, focusing on a specific pedagogical challenge, and leveraging accessible tools can yield significant benefits without requiring deep technical expertise – just subject knowledge. Her experiment evolved from addressing a specific skills gap to embracing a broader philosophy of AI augmentation, critical evaluation, and reflective practice.
As UK universities navigate the complexities of AI – from assessment integrity to shifting graduate employment expectations – stories like Michelle’s are invaluable. They remind us that amidst the hype and anxiety, there are practical, thoughtful ways to harness these technologies to enrich student learning and develop crucial future-facing competencies. It’s a journey of experimentation, reflection, and shared learning – one we are all embarking on together.
Inspired by Michelle? Getting Started with AI Role-Play Tools:
If Michelle’s experience has sparked your interest in exploring Blackboard or LinkedIn Learning’s AI role-play features, here’s a simple, low-stakes way to begin which mirrors her pragmatic approach:
- Identify Your ‘Difficult Conversation’: Think about a specific communication skill or scenario relevant to your discipline where students could benefit from practice. It could be anything from providing constructive feedback or handling a client complaint to practising interview techniques or navigating ethical dilemmas. Keep it focused initially.
- Locate the Tools: The AI Roleplay feature is enabled in Blackboard (found within course content areas). For LinkedIn Learning, explore the ‘Role Play’ section which allows you to talk directly with the coaching tool.
- Have a Go Yourself: Before involving students, try setting up and running through a scenario yourself. Define a simple persona and goal for the AI. As Michelle found, the setup might be more straightforward than you expect. See what it feels like from a user’s perspective.
- Reflect on Your Trial: What was the experience like? Did the AI respond realistically? How easy was it to guide the conversation? Consider its strengths and limitations for your specific learning outcomes. This personal test drive is invaluable.
- Consider a Small Pilot: If your trial feels promising, think about introducing it to a small group of students. Frame it clearly as a practice tool for augmentation and skill development, emphasising, like Michelle, the need for critical evaluation and reflection on the interaction afterwards. Guide students on exploring different approaches within the simulation.
- Keep it Simple: Remember Michelle’s point – it doesn’t require deep technical expertise to begin your AI journey. Focus on the pedagogical value, your subject level expertise and learn alongside your students.
Experimentation is key. By taking these small steps, you can begin to explore the potential of these AI tools to enhance your teaching practice in meaningful ways.
Resources
AI Conversation tool in Blackboard