Archives: Seedlings

Since 2023, nearly every educational AI tutor has adopted the same design philosophy: withhold the direct answer and offer a guiding question in return. Khanmigo, ChatGPT's study mode and Gemini's Guided Learning all rely on this approach. The underlying pedagogy is sound, yet two recent trials suggest we have been focusing on the wrong thing entirely.

As a native Flemish speaker, I am often disarmed by the way my neighbours in the Netherlands use language. They have a distinct knack not just for coining brilliant terms, but for casually dusting off older, deeply resonant words that I had entirely forgotten existed. Together, these words capture the messy human reality of work, cutting straight through standard corporate jargon.

Someone called me visionary in a meeting recently. I said thank you, the way you do, before realising it was a polite way of parking my ideas. The praise felt complicated. It was like being handed a description of myself that I recognised, yet I couldn't quite shake the sense that it doubled as something less flattering: a polite way of saying my input didn't need dealing with just yet.

We don't reason our way into new behaviour. We act, uncertainly and messily, and then make sense of it by telling a story about what happened. I keep coming back to this when I watch institutions respond to AI and other challenges. Sensemaking is retrospective. Strategy is prospective. The gap between them is where people get lost.

At some point, every conversation about GenAI in education lands on the same question: who is responsible for figuring this out? Senior leadership? IT? The faculty development office? A working group with a mandate expiring in June?

Mijn eigen diploma is in de Onderwijstechnologie. Januszewski en Molenda (2013) definieerden dat vakgebied als "de studie en ethische praktijk van het faciliteren van leren en het verbeteren van prestaties door het creëren, inzetten en beheren van gepaste technologische processen en middelen."

My own degree is in Educational Technology. Januszewski and Molenda (2013) defined it as "the study and ethical practice of facilitating learning and improving performance by creating, using, and managing appropriate technological processes and resources."

Three years in. That's where we are now with generative AI in higher education. ChatGPT's arrival in late 2022 feels like both yesterday and a lifetime ago. The initial panic ("How do we AI-proof assessment?") has given way to something more interesting, more nuanced, and dare I say it, more hopeful.

For the past few years, I've been experimenting with various large language models (LLMs) and tools to better understand the sense and none-sense of generative AI (GenAI). In my quest for meaningful and efficient uses, I've created various tools for personal and professional use (think: article collector and personal home voice assistant). My sixth iteration of an LLM-based qualitative analysis tool is a prime example of where these models can be quite handy. Here’s what I've learned through trial, error and extensive reading.

Looking for your next read? These eight books won't all sit comfortably together on a shelf—which is exactly the point. They range from scathing critiques of neoliberal universities to surprisingly practical guides on networked learning, instructional design, and (plot twist) no-dig gardening. Each one challenged how I think about teaching, learning, and what actually makes institutions flourish.