I’ve already replayed that bit five times now. From about 2:50 to 3:30 into the track ‘Ghost Eyes in the Fire Light’ by the black metal band Panopticon. Guest vocalist Jordan Day sings with a fragile, heartfelt quality. It’s not perfect, a bit off-key at times, but it’s brilliant, so human. I love imperfection. I love it when things don’t go perfectly, when we fall and get back up again. I love students who struggle with an assignment, take a wrong turn in their work, and yet manage to get everything back on track together. I love the graduate or PhD student who first submits a chapter or paper on which I have a great deal of feedback, and then presents a beautifully rewritten piece. And I love the student who initially thought they weren’t cut out for education, but who nevertheless ends up at our university after, for example, a pathway from vocational college through higher professional education. I’ve got a soft spot for them.
How many times have I told my children that you learn from your mistakes? They shape who we are, teach us that things can sometimes go terribly wrong, and build our confidence for when we find ourselves in similar situations again. Unfortunately, in our education system, we have narrowed the margin for error so much that students do everything they can to avoid making mistakes. After all, failing a course can be very costly. Last week, the TLC organised a ‘show and tell’ session where students talked about how they and their fellow students use (gen)AI in their learning process. Of the many interesting things they said, one keeps niggling at me: students are using AI to avoid making mistakes. For example, some students would rather submit a text to Academic Skills that has been ‘made academic’ by AI than receive feedback from their lecturer on their text and work on improving it. And this is despite the fact that the vast majority of students are well aware that using AI has consequences for their learning process.
Learning is painful. That’s what we like to tell our students. But our education system is geared towards enabling students to complete their studies within the standard time frame, not towards successfully navigating pitfalls, making mistakes, and falling down and getting back up again. Learning is not a linear process. It sometimes requires taking a step back, thinking about a different strategy, and seeking advice on how to do things differently. It is our job, that of the university and its lecturers, to guide them through this process. In that context, students’ use of AI is perhaps telling. Just like the fact that I see so few students around our offices in EOS. Do students prefer to consult AI rather than us? A rather unsettling thought occurs to me. Could it be that students now see us as an institution that assesses their progress in their learning process, rather than a place that guides that process? Given the focus on efficiency and learning assurance, it is certainly starting to look that way. I think I speak for many colleagues when I say that I would much rather be that mentor. I’d rather be the lecturer students can turn to when they’ve taken a wrong turn, where they’re helped when they don’t understand something. Where they’re allowed to sing out of tune and see the beauty in that themselves. Because I think that’s the most wonderful thing there is.