Supporting and Understanding Mathematics Learning with Technology

Dr Manolis Mavrikis is a researcher at the London Knowledge Lab – Institute of Education, University of London. He has been conducting research in the field of Artificial Intelligence and Mathematics Education for the last 10 years. This talk will showcase research and development projects that he has been involved. Starting from some earlier work in higher education that allowed the provision of support to undergraduate students studying first year mathematics topics, the talk will continue with more recent work that investigates how to scaffold students’ interaction in exploratory learning environments and, in particular, mathematical microworlds. Through the example of MiGen, a learning and teaching environment where young students undertake algebraic generalisation tasks, Manolis will present the different types of adaptive feedback that the system can provide helping students not only to interact with the environment but also to develop mathematical ways of thinking. The last part of the talk will highlight the twofold potential of artificial intelligent techniques in helping us deepen our understanding of mathematics learning. From one hand the development of such systems requires precision that obliges us to make explicit what is often known implicit in teaching and learning. From the other hand, students' interactions with these environments and the digital traces they leave behind provide amble opportunities for data collection and analysis, which can help answer questions that are not possible with traditional methodologies. Manolis will present these using some examples from his research.