Digital Garden
A collection of growing thoughts on higher education, edtech, and the future of learning
Hebben we de term “Onderwijstechnologie” nog nodig?
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."
Do We Still Need the Term “Educational Technology”?
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."
What Comes First? Pedagogy or Technology?
Conversations about pedagogy and technology in higher education tend to produce a quick consensus: pedagogy first, technology second. Define the learning goals, then choose the tools. It is a position most educators feel comfortable with, and for good reason — it keeps the focus on purpose rather than on the tool itself. What is worth exploring, though, is whether that sequence actually holds up in practice.
What Do We Actually Know About GenAI and Learning?
Every few months a new headline announces that AI is about to transform education: sometimes as breathless optimism, sometimes as creeping alarm. Both reactions share the same flaw: they are running well ahead of the evidence, and, more importantly, ahead of our current capacity to properly study the question.
What Actually Makes Teacher Professional Development Work?
Most universities offer their academic staff some form of teaching development. A workshop on active learning. An induction session for new starters. A seminar series that appears in the calendar each year. The intentions behind these programmes are genuine. The evidence that they change teaching practice is, on the whole, thin.
AI Feedback: Automate Tasks, Not Trust
Conversations about educational technology often orbit around efficiency, but the rapid rise of generative AI has forced universities into a long-overdue reckoning with a much deeper question: what exactly are we doing when we provide feedback? If feedback is merely the transfer of corrective information, then large language models have already won. They can parse essays, spot logical flaws, and debug code with astonishing speed. However, reducing feedback to a glorified diagnostic tool misses the fundamental reality of how university students actually learn.
Slowly but steadily it is happening
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.
Cultivating Shared Vision in an Era of Radical Complexity
Step into the lobby of almost any university, and you will likely find a mission statement etched onto the glass façade. It usually speaks of "excellence", "innovation", and "global citizenship". Yet, a mere few hundred metres away in a lecture hall, the reality often feels worlds apart from those lofty aspirations.
Leading, Not Managing
The landscape of higher education is increasingly defined by complexity. As institutions navigate financial pressures, technological disruption, and shifting student demographics, the nature of academic leadership is being actively renegotiated. While strategic plans frequently emphasise "transformation" and "agility", the operational reality often reveals a different trajectory: one characterised by intensified management and data-driven oversight.
How I actually used GenAI in 2025
If you feel a bit overwhelmed by the sheer number of AI tools out there right now, you are certainly not alone. With a new model or breakthrough announcing itself every week, simply figuring out what to actually use this technology for has become a task in itself.