AI as a Rehearsal Space: Rethinking Assessment in Healthcare Education

The Challenge

Assessment in healthcare education asks students to demonstrate more than what they know. This is particularly important in Motivational Interviewing (MI), where the quality of the conversation matters. Empathy, active listening, curiosity and partnership are essential, as is the ability to respond to ambivalence without rushing to offer advice. In an asynchronously taught Masters module, this presented a curriculum challenge. Online learning offered flexibility for students balancing study with professional and personal commitments, but it also meant fewer live opportunities to rehearse challenging conversations before assessment. MI cannot be fully understood through theory alone. It needs practice, reflection, repetition and the opportunity to notice how communication choices may feel from the client’s perspective.

Innovative Solution

To address this, I developed a tailored AI client within BodySwaps as part of the module’s assessment design. BodySwaps is an AI powered immersive learning platform that allows learner to practice communication and interpersonal skills through realistic virtual conversations, with personalised feedback to support reflection and confidence building. This was accessed through the department’s simulation technical specialist Daniel Ashton.

My intention was not to introduce AI simply because the technology was available, but to use it as a purposeful pedagogic tool: enabling online learners to practise and demonstrate communication skills in a structured, accessible environment.

The AI client was designed for the needs of this Masters cohort; aligned with the module outcomes, and communication challenges students may encounter in practice. Students engaged with a responsive virtual client, making decisions in real time and reviewing feedback on empathy, reflective listening, open questions and responses to change talk. BodySwaps featured a further reflective dimension, encouraging students to consider how the interaction may have felt from the client’s perspective.

Importantly, the simulation was not a standalone activity. It formed the first component of a two-part assessment, followed by a structured reflective journal. Students were asked to analyse their communication choices, identify strengths and areas for development, connect their experience to MI principles and professional standards. Rather than describing effective communication, they had an opportunity to put it into practice and critically examine their decisions.

For me, one of the most important aspects of this work was the alignment between technology, curriculum and assessment. The focus was not on using AI simply because it was available, but on addressing a specific educational challenge: enabling online students to rehearse and demonstrate interpersonal skills beyond a written assessment. BodySwaps provided a flexible, repeatable rehearsal space where students could revisit conversations, explore different approaches and reflect on their practice, while maintaining alignment with assessment requirements and the importance of educator judgement, ethical design and reflective learning.

Reflections on this approach

This approach also raises important questions about how we use AI in assessment more broadly. Assessment should be meaningful, inclusive and connected to the realities of practice. AI-supported simulation offers possibilities, particularly for students who cannot readily access live role-play. Yet its value depends on thoughtful educational design. It cannot replace educator judgement, professional accountability, reflective debrief or the human relationships at the heart of healthcare.

Yet this assessment development is not evidence of improved student outcomes. As module leader, I made applied MI practice accessible to asynchronous learners, helping students prepare through interaction rather than theory alone. The next step is to seek ethics approval to explore students’ experiences, confidence, perceived authenticity and the value of repeated practice, with findings informing a follow-up on impact.

Developing this AI client reinforced my belief that assessment innovation need not replace educational principles. Used purposefully, AI may extend what good teaching offers: opportunities to practise safely, think critically, reflect and prepare for conversations central to practice.

Author

Leisa Anderton, School of Health and Social Care, College of Health, Wellbeing and Life Sciences