AI Educational Innovation
TU Delft continuously introduces the latest AI, data & digitalisation innovations into its educational programmes. We develop and drive educational projects that lead to horizontal knowledge transfer, including support and connections with AI teachers so that the latest knowledge is embedded into students’ learning.
AI Teachers’ Programme
This project aims to develop a broad programme where ‘in-AI’ and ‘with-AI’ teachers are supported in developing AI education. It may involve exchanging knowledge on how to teach AI within a specific subject area, but will also include focus groups so that teachers can together take stock of what it takes to integrate AI into the curriculum. AI staff members will emerge with a better understanding of AI and its applications within education. They will be able to keep pace with the impact of AI within their discipline, and tailor the curriculum accordingly.
Within this programme, the Machine Learning Teachers Community was established in 2023. At TU Delft, machine learning courses have been developed at each faculty – ranging from fundamental machine learning to applications within the different knowledge domains. The community aims to exchange experiences and best practices in machine learning education, and introduce each other to the discipline’s numerous possibilities. All TU Delft lecturers who teach machine learning are welcome to join this community.
Open Educational Resources
Developing open educational resources is a central TU Delft policy, and the AI Initiative's education working group is driving this for AI educational materials. In cooperation with other educational institutions, we want to develop a repository of AI educational materials that every AI teacher can use. For this, we need clear frameworks of how AI can be applied within different subject areas.
Many teaching materials come from different institutes and application areas and are developed for students from different backgrounds. As a result, different standards, languages and notations are in use. It is important to work with different institutions – because from their differences we can work towards a common understanding of AI and identify application areas. In this way, we can make existing material accessible to a wider student population. Divergent starting points also provide an especially strong basis for ensuring the quality of OERs.
Publishing educational materials freely and openly online for a broad student population will ultimately attract more students to develop their AI knowledge within their domain.
PhD candidates attached to a TU Delft AI lab have an extra year of time instead of the usual four years. This extra time is focused on teaching. A PhD training programme has been developed that focuses on broadening and deepening teaching knowledge and skills.
We are developing several online courses on AI, data and digitalisation on the edX platform. These MOOCs (Massive Open Online Courses) are accessible to people around the world.