Developing AI literacy in professional education

Everyone is talking about the need to develop AI literacy in students and staff at higher education institutions, and I worry that this is going to become a series of mandatory training events for all students in higher education around the world. I think that this will be a huge waste of time because people don’t care about going to mandatory training; they care about solving real problems in their working and learning.

So, what does ‘developing AI literacy’ look like in practical terms?

First of all, I think you need a baseline level of understanding, so there’s nothing wrong with a little lecture. This is generative AI. This is basically how it works. This is what it can do. Here are a few examples relevant to you. Here are some principles for how to think about using it.

And then you should just start using it, to solve a real-world problem.

I’ve recently finished supervising some physiotherapy students on a research placement, and I was struck by how structured their portfolio of learning needs to be. Thinking back to my own experience as an undergraduate student, I think I would have initially found this helpful, and then very soon started treating it as a tick box exercise. Because the form is literally a series of tick boxes. I also noted that every portfolio looks the same, regardless of the placement (which is challenging when I’m trying to complete the form for a research placement, when it’s clearly designed to work on a clinical placement).

So, this is the kind of problem I think might be useful to explore by having students engage in an activity that:

• helps them develop AI literacy;
• by using AI to build a personalised learning programme;
• that’s unique to each of their placements;
• and that maps onto the outcomes they need to document in their portfolios.

I’d start by asking colleagues who support students on their placements to write a unique prompt for every single placement in the programme. I’d give everyone the same template and ask them to edit it to reflect the specific placements they’re going to be supervising.

The template might look something like this:

I am a [YEAR] physiotherapy student about to start my first practice placement. The placement is a [DESCRIBE THE PLACEMENT]. I am expected to assess and manage patients and service-users with [DESCRIBE CONDITIONS, ETC]. My learning portfolio needs to show how I’ve demonstrated the following professional behaviours and responsibilities: 1) fit to practice safely and effectively, 2) promotes and protects the interests of others, 3) assesses risks accurately, [AND SO ON]. I also need to demonstrate levels of proficiency in the following learning domains: 1) independent learning, 2) seeking, reflecting on, and responding to feedback, 3) organisation and prioritisation, [AND SO ON]. On reflection, I think that my professional strengths are [LIST STRENGTHS], while my weaknesses include [LIST WEAKNESSES]. For this placement, I would like to achieve the following learning outcomes: [LIST OUTCOMES]. Personally, I am feeling quite anxious about this placement, as I feel it will push me out of my comfort zone. I’m also nervous about the travel component, as I will be relying on public transport, and I know that being on time is important. I’ve tried to prepare for the placement by [LIST PREPARATION ACTIVITIES]. I also work some nights and on the weekend, to support my studies, and I’m worried that I won’t have the time I need to focus on my learning when I get home from placement. Given all of these variables, please help me draft a personal learning programme I can use to make the most of my time on this placement. Suggest a few placement-specific activities I can undertake during the placement that will help me use my strengths to improve on my weaknesses.

You could have another template for second year students, which would have updated expectations around what ‘success’ looks like at that year-level. And the subsequent placement prompts could include space for reflections on the first placement, as well as specific feedback from the supervisor and practice educator. The student could even upload the outcome reports to the AI as part of the context-setting for the next placement.

The description of the placement would include how long it lasts, what kind of setting it is, where it’s located, what the sociodemographic characteristics of the population looks like, and so on.

The lists of professional behaviours and responsibilities, and learning domains (with the level descriptors, and marking rubrics) could be uploaded as additional context for the AI, as well as any other relevant documentation, like regulatory body requirements.

The student will then have a draft of a learning plan for the duration of the placement that can be used to inform discussion and planning with the practice educator and supervisor. They can edit and refine it together over time, as the placement unfolds.

It will also:

• map onto the outcomes for the placement (because we’ve specified in advance what we are looking for);
• be unique to the placement (because we have a unique description of what that placement looks like);
• is specific for the students’ personal context (because they’ve described what their challenges, anxieties, strengths, weaknesses, etc. are);
• has used AI to support learning (and thus played a small part in helping develop AI literacy).

I think that this would be so useful because the student is learning how to provide the kind of context the AI needs to help them address personally meaningful problems. And it supports student learning in a way that we don’t need to worry about ‘cheating’. We also don’t need to worry about hallucination, because the plan is, by definition, adaptable and subject to change over time. And it’s also an inherently creative activity, where we don’t need to worry about accuracy.

I think that this is what professional education will (should?) look like in the near future; students, lecturers, supervisors, and AI, all collaborating to support student learning.

What do you think?