Whither or wither the AI of AIED?

This position paper explores the relationship between the historic roots of AIED and the challenges of restricting our vision to EdTech that has AI. It argues that the founders of AIED had a broad vision of the field, primarily driven by the goals of creating advanced technology for personalised learning. They were not wedded to a techno-centric view, demanding use of particular techniques that are now thought of as “AI”. The paper argues that we have accepted work with no AI, notably in Open Learner Modelling. We discourage, either directly or just because of our name, work that is true to the AIED founders’ vision. In doing so, we miss many exciting and promising ways to create better technology for education. 1 What was the AI in the initial vision of AIED? So how did we come to be called AIED in the first place? In the early days of computing research, AI had a very broad brief. It was driven by the vision that computers would one day be able to emulate the actions we describe as intelligent when people do them. What a bold vision this was --at a time when computers were very slow, expensive and available only in research labs, military and business contexts. AI research stood in stark contrast to other the major areas of computing, such as hardware, operating systems, programming languages and numerical analysis. It was AI that looked to real world applications and creating the visions of science fiction. AIED was born in the 1970s, with its first conferences in the 1980s (Self, 2015). It aspired to create applications that could help people learn. This was long before it was possible for most learners to even see, let alone use, a computer. A widely cited driver for our AIED research was the vision that computers could help achieve Bloom’s famous 2-sigma learning benefits from personalized teaching by an expert teacher (Bloom, 1984). Our community is still committed to this goal. But it is useful to consider what it meant. AIED 2015 Workshop Proceedings Vol 4 1 The classic early work in AIED identified four key elements: