This track welcomes submissions on the topic of interdisciplinary education in the domain of FAT* computing. Participants may begin from any disciplinary perspective, including computer science, law, the social sciences (including education studies) and the humanities, with a focus on how translation and mutual enrichment can occur between disciplines in relation to education and learning. Accounts and evaluations of approaches, proposals and experience of interdisciplinary education including lessons from experimental and innovative structures and approaches are particularly welcome, given the emerging nature of the field. Submissions that seek to incorporate insights from educational theory and scholarship are particularly welcome and strongly encouraged.
Each paper will be reviewed by 3 program committee members from Tracks 1-3 and from this track. The evaluation criteria for the review will include:
These papers should help to develop a clear and well argued vision on how interdisciplinary education and learning can enable FAT* computing in practice, for instance focusing on law and computer science, or on data science and ‘values by design’. Papers could address part(s) of the entire spectrum from minors across disciplinary borders (such as Human Computer Interaction, and Legal Design), single courses (law for computer scientists; computer science for lawyers; explainable ML, etc.) to joint and interdisciplinary graduate degree programs in law and computer science (e.g. dual degree programs).