Alan Turing Artificial Intelligence in Education Event
Date: 27th July 2022
Venue: Teaching and Learning Centre (Hybrid event)
Find out more about the project supporting this at: ATI@Durham Network – AIHS
|Prof. Alexandra I. Cristea and Prof. Brian Castellani
|Introduction to Alan Turing Intelligence in Education Event ATI@Durham Network – AIHS
Alan Turing Institute
Alan Turing Institute
Mathew Forshaw, Alan Turing Institute
|Panel session – ATI Research on AI in Education moderated by AI Cristea
AI and Data Science in Education at the Turing Institute / SIG
|AIED Society and the Alan Turing Institute
|EDM Society and the Alan Turing Institute
|Wayne Holmes, Council of Europe team
|The Council of Europe.
Artificial Intelligence and Education. A Critical View Through the Lens of Human Rights, Democracy and Rule of Law.
|Panel session – Engaging with international societies and policy organisations
Moderated by AI Cristea
|Nibbles and drinks – Welcome reception AIED’22
Meet the Speakers
Alexandra I. Cristea
Alexandra I. Cristea is a Professor, Deputy Executive Dean of the Faculty of Science, Deputy Head, Director of Research and Founder of the Artificial Intelligence in Human Systems research group in the Department of Computer Science at Durham University. Her research includes web science, learning analytics, user modelling and personalisation, semantic web, social web, and authoring, with over 300 papers on these subjects (over 5000 citations on Google Scholar, h-index 39). Especially, her work on frameworks for adaptive systems has influenced many researchers and is highly cited (with the top paper with over 200 citations). She was classified within the top 50 researchers in the world in educational computer-based research according to Microsoft Research (2015-02-10). Prof. Cristea has been highly active and has an influential role in international research projects. She leads and has led various projects – the ATI@Durham Research Network (2022); the Epistemological Engine (2021-22); Weizman Institute funded JANET (Joint Lab in Learning Analytics for Personalised Science Teaching) project (2020-2022); Predictive and prescriptive analytics for the media industry, Distinctive Publishing (2019-2022); Newton funded workshop on Higher Education for All (’14-’18), Santander funded Education for disadvantaged pupils (’14-18′), Warwick-funded project APLIC (’11-;12), EU Minerva projects ALS (06-09) and EU Minerva ADAPT (’02-’05); as well as participated as university PI in several EU FP7 projects – BLOGFOREVER (’11-’13), GRAPPLE (’08- ’11), PROLEARN (’07) and as co-PI in the Warwick-funded Engaging Young People with Assistance Technologies (’13-’15) also featured by the BBC.
Brian Castellani, Director DRMC Durham University
In addition to being Director of the Durham Research Methods Centre, I am Co-Director of the Wolfson Research Institute for Health and Wellbeing, Adjunct Professor of Psychiatry (Northeastern Ohio Medical University), Editor of the Routledge Complexity in Social Science series, CO-I for the Centre for the Evaluation of Complexity Across the Nexus, and a Fellow of the National Academy of Social Sciences. I am trained as a public health sociologist, clinical psychologist, and methodologist and take a transdisciplinary approach to my work. My methodological focus is primarily on computational modelling and mixed-methods. My colleagues and I have spent the past ten years developing a new case-based, data mining approach to modelling complex social systems and social complexity – case-based computational modelling – which we have used to help researchers, policy evaluators, and public sector organisations address a variety of complex public health issues, from depression and allostatic load to air pollution and brain health to the social determinants of health inequalities. We also developed COMPLEX-IT, designed to increase non-expert access to the tools of computational social science (i.e., cluster analysis, artificial intelligence, data visualization, data forecasting, and scenario simulation) to make better sense of the complex world(s) in which they live and work. As Director of the DRMC, my goal is to facilitate across the university a transdisciplinary and mixed-methods approach to social and health science, grounded in a complex systems perspective.
Manolis Mavrikis, Alan Turing Institute
Manolis Mavrikis is a Professor of Artificial Intelligence and Analytics in Education at the UCL Knowledge Lab and Innovation and Enterprise Lead and Turing Fellow at the Alan Turing Institute. He is also one of the Editors for the BERA journal British Journal of Educational Technology and a member of the Executive Committee of the International Artificial Intelligence in Education (AIED) Society. Manolis’ interest, experience, and research agenda for over 20 years bridge Artificial Intelligence, Human Computer Interaction and Learning Sciences to understand complex learning phenomena and design, create and evaluate adaptive technologies for learning, teaching and research. He has balanced academic and knowledge exchange activities with significant methodological and practical contributions in the field. Manolis has participated in and led several projects and partnered with schools, teachers, and other key stakeholders such as start-ups outside academia.
Nick Holliman, Alan Turing Institute
Nick Holliman is a Professor of Computer Science in the Department of Informatics at King’s College London and Director of CUSP London. Nick researches the science and engineering of visualization and visual analytics, addressing the fundamental challenges of visualization in successful human-machine teaming. He has demonstrated how novel visualization methods work in practice in scalable cloud-based software tools and award-winning 3D visualizations. Nick has experience delivering global commercial impact from research outputs of both industrial and academic laboratories. He is a Fellow of the Alan Turing Institute, where he co-founded and co-convenes the Visualization Interest Group.
Mathew Forshaw, Alan Turing Institute
Matt is Senior Advisor for Skills to The Alan Turing Institute, and Reader in Data Science at Newcastle University. His work in AI skills includes working with the Government on the skills pillar of the National Data Strategy, the leadership of skills policy initiatives through the Data Skills Taskforce, and developing national curriculum standards with the Alliance of Data Science Professionals. He is passionate about democratising access to, and widening participation into, data skills training.
Vania Dimitrova, AEID Society
Vania Dimitrova leads research activity on human-centred artificial intelligence which builds intelligent systems that help people make sense of data, take decisions in complex settings, expand their knowledge, learn from experience, and develop self-regulation skills. Her research explores the use of data and knowledge models to get insights into user-generated content, understand users and influence behaviour, capture knowledge and support information exploration. Her research is conducted in cross-disciplinary collaboration with researchers from Medicine and Health, Engineering, Social Science, Education and Psychology, and actively involving end users. She is currently President of the International AI in Education Society and Co-Director of the UKRI Centre for Doctoral Training in AI for Medical Diagnosis and Care. She was Co-Director of the Leeds Research Centre in Digital Learning and was Director of Technology Enhanced Learning Strategy at the Leeds Institute of Medical Education. She is Associate Editor of the International Journal of AI in Education, and Frontiers of AI: AI for Human Learning and Behavior Change. She was Associate Editor of IEEE Transactions on Learning Technologies (IEEE-TLT) and a member of the editorial boards for the personalisation journal (UMUAI). She chaired the premier international conference on user modelling (ACM UMAP) and key conferences in intelligent learning environments (AIED, ECTEL, ICCE), as well as a series of international workshops on key topics related to intelligent mentoring, user modelling, social systems, intelligent exploration.
Kenneth R. Koedinger, EDM Society
KENNETH R. KOEDINGER is a professor of Human Computer Interaction and Psychology at Carnegie Mellon University. Dr Koedinger has an M.S. in Computer Science, a Ph.D. in Cognitive Psychology, and experience teaching in an urban high school. His multidisciplinary background supports his research goals of understanding human learning and creating educational technologies that increase student achievement. His research has contributed new principles and techniques for the design of educational software and has produced basic cognitive science research results on the nature of student thinking and learning. Koedinger directs LearnLab (learnlab.org <http://learnlab.org>), which started with 10 years of National Science Foundation funding and is now the scientific arm of CMU’s Simon Initiative (cmu.edu/simon <http://cmu.edu/simon>). LearnLab builds on the past success of Cognitive Tutors, an approach to online personalized tutoring that is in use in thousands of schools and has been repeatedly demonstrated to increase student achievement, for example, doubling what algebra students learn in a school year. He was a co-founder of Carnegie Learning, Inc. (carnegielearning.com <http://carnegielearning.com>) has brought Cognitive Tutor based courses to millions of students since it was formed in 1998 and leads LearnLab (see learnlab.org), now the scientific arm of CMU’s Simon Initiative (see cmu.edu/simon). Dr Koedinger has authored over 250 peer-reviewed publications and has been a project investigator on over 45 grants. In 2017, he received the Hillman Professorship of Computer Science and in 2018, he was recognized as a fellow of Cognitive Science.
Wayne Holmes, Council of Europe team
Wayne Holmes (PhD, University of Oxford) is a learning sciences and innovation researcher who teaches at University College London, is a consultant researcher on Artificial Intelligence (AI) and education for UNESCO, and is a member of the Education Scientific Committee for IRCAI (the International Research Centre for Artificial Intelligence under the auspices of UNESCO). Wayne’s research interests focus on a critical studies perspective to the connections between AI and education, and their ethical, human and social justice implications. Having been involved in education throughout his life, Wayne brings a critical studies perspective to the connections between AI and education, and their ethical, human and social justice implications. His recent publications include “Artificial Intelligence in Education. Promise and Implications for Teaching and Learning.” (2019), “Ethics of AI in Education: Towards a Community-Wide Framework.” (2021), “The Ethics of AI in Education: Practices, Challenges and Debates” (in press), and, for UNESCO, “AI and Education: Guidance for Policy-makers.” (2021). Wayne has advised the ministries of education of Portugal (MOOC on AI and education for teachers) and the UK (evaluating AI tools for education), co-authored the EU’s DigComp 2.2 Annex “Citizens Interacting with AI Systems” (2022), is co-leading the Council of Europe’s work on AI and education, and has given invited talks on AI and education in Brazil, China, Croatia, Denmark, Germany, Greece, India, Japan, Oman, Slovenia, Spain, and the US (and online to audiences in many other countries around the world).