Content
Open learning and research content from the lab
A collection of materials we publish openly: a guide to the research process, a field map of educational AI, lecture notes, and more. The aim is to make the knowledge produced in our research and teaching usable beyond the lab itself — by students joining the group, students at other universities, researchers entering this field, and teachers in the classroom.
A systematic guide to the research process — from picking a topic through writing and presenting. The starting point of the lab's methodology.
A cross-disciplinary map of educational AI research bridging cognitive science, learning science, knowledge engineering, and HCI. Sister volume to the research guide.
Lecture notes for undergraduate courses at Kanagawa University — Python, algorithms, programming languages, and more.
Suggested reading order
- Undergraduates and first-year graduate students new to research should start with How to Conduct Research, then read the chapters of A Field Map of Educational AI that relate to their topic to locate themselves in the field.
- Course participants should start with the Lecture Notes, following along with the schedule of the course. If research becomes interesting, move on to How to Conduct Research.
- Researchers from other fields and classroom teachers can enter through A Field Map of Educational AI and use the chapter most relevant to their interests as a bridge to the lab’s research themes and papers.
More to come
We plan to keep growing this collection. New material will be reachable from this page as it is published.