Benedict DU BOULAY
University of Sussex, UK
Title: Artificial Intelligence in Education – the next 10 years (C1)
Wednesday, November 28, 2018
10:00-11:00, Hall A&B
Artificial Intelligence plays two main roles in Education. First is in its provision of a wide variety of techniques that underpin various kinds of learning environment, including intelligent tutoring systems. These techniques enable the modelling of the domain of learning itself and of the learner’s fine-grained progress in developing the skills and understanding in that domain. These techniques also enable the system to conduct a dialogue (in the most general sense of that word) with the learner through an interface, and model and execute a pedagogic strategy and tactics that can drive forward a productive interaction between learner and system.
The second main role of Artificial Intelligence in Education is in the provision of techniques to search for patterns in learner data of many kinds to help develop our understanding of learning itself, of effective and ineffective teaching strategies and tactics, as well as detecting learning and teaching issues with specific systems.
Over the last few years a number of meta-analyses and meta-reviews of AI in Education systems have revealed a generally positive story about the effectiveness of such systems as compared to more traditional classroom learning across a range of STEM domains. These reviews have also shown that the field is still some way from meeting the challenge of Bloom’s 2 sigma analysis of skilled, human, one-to-one mentoring.
This talk will explore the current state of AI in Education and anticipate the next decade’s progress. It will focus on the broadening of learner modelling to include not just knowledge and skill, but also metacognition, affect and motivation. This broadening brings with it the need to develop the scope of pedagogic strategies and skills to include this extended sense of the learner as a whole person, and not just as a disembodied cognitive entity. Likewise, educational data-mining and learner analytics have similar opportunities to explore learner and teacher behaviour in a more rounded fashion.
Bio: Benedict du Boulay is an Emeritus Professor of Artificial Intelligence in the School of Engineering and Informatics at the University of Sussex and Visiting Professor at University College London. Following a Bachelors degree in Physics at Imperial College London, he spent time both in industry and as a secondary school teacher before returning to university to complete his PhD in 1978 in the Department of Artificial Intelligence at the University of Edinburgh working on Logo.
He has two main research areas. The first is the Psychology of Programming where his main work has been in the area of novices learning programming and the development of tools to assist that process. The second is the application of Artificial Intelligence in Education. Here he is particularly interested in issues around modelling and developing students’ metacognition and motivation.
He has co-organised various workshops on the above areas. These have included the 1st and 2nd International Workshop on Affect, Meta-Affect, Data and Learning (AMADL 2015 in Madrid, and AMADL 2016 in Zagreb) and the workshop on “Les Contes du Mariage: Should AI stay married to Ed?”, also in Madrid in 2015. He has successfully supervised 25 PhD students in the above areas.
He was President (2015-2017) and is currently Treasurer and Secretary of the International Society for Artificial Intelligence in Education and an Associate Editor of its International Journal of Artificial Intelligence in Education.
He has edited/written 9 books and written some 190 papers in the areas indicated above.
Title: Thinking about Computational Thinking and How Learning Sciences Can Shape Deeper Learning of Computer Science in Schools (C2)
Thursday, November 29, 2018
09:00-10:00, Hall A&B
As nations begin to scale computer science (CS) in primary and secondary school education, Computational Thinking (CT) and programming are being recognized as key 21st century skills. In the first part of her talk, Dr. Grover will reflect on CT, its evolution, meaning, relationship to programming, and vision for enriching learning of CS and other subjects. The second part of Dr. Grover’s talk will address the question: how and what can we draw from learning theory to help the next-generation of problem-solvers develop this emerging competency? Bridging learning theory, research, and practice, Dr. Grover will share how CT and CS curricula can leverage pedagogical ideas from the learning sciences as well as computing education research to design for deeper learning. Through varied examples drawn from research for curriculum design, pedagogy, and assessments that aim for deeper learning, Dr. Grover will synthesize learning principles that can serve to guide future designs for CT and CS teaching and learning.
Bio: A computer scientist and learning scientist by training, Dr. Shuchi Grover’s work in computing education in both formal and informal learning settings has spanned US, India and Europe. Her current research centers on computational thinking (CT), computer science (CS) education, and STEM+Computing integration mainly in formal K-12 settings.
Formerly a senior research scientist at SRI International, Dr. Grover is a recipient of several grants from the US National Science Foundation to conduct research on CT learning and assessment in varied PK-12 contexts including introductory CS education and STEM classrooms that integrate CS and CT. She also works at the intersectional space between learning, assessment and big data analytics to shape future environments for deeper learning with embedded assessment.
Dr. Grover’s commitment to shaping both research and practice is evident in her outreach work. She has authored highly cited scholarly papers, book chapters, blog posts, and mainstream articles on the topic of CT and CS education in K-12 education. She is advisor to the national K-12 CS Framework (k12cs.org) in the US, a member of the ACM Education Council and the Computer Science Teachers Association’s task force on Computational Thinking, on the editorial board of ACM Transactions on Computing Education, and an advisor to K-12 school districts on CS implementation/integration.
She has a Ph.D. in Learning Sciences and Technology Design (focused on computer science education) from Stanford University, an Ed.M (Technology, Innovation, and Education) from Harvard University, and undergraduate and graduate degrees in computer science.
Cher Ping LIM
Education University of Hong Kong, Hong Kong
Title: ICT-enabled Teacher Professional Development at Scale for Quality Access to Education (C7)
Wednesday, November 28, 2018
13:30-14:30, Hall A&B
Teachers have a pivotal role in the learning environment to engage all students in their learning, support them to monitor and manage their own learning, and provide opportunities for them to enhance their learning outcomes. For teachers to provide students with such quality access to learning and develop students’ lifelong learning skills, they have to possess the competencies to carry out such a role. Continuous professional development of teachers ensures that teachers develop this set of competencies and are kept current with curriculum and assessment reforms; when such professional development opportunities are provided for teachers, Sustainable Development Goal (SDG) 4 (quality education for all) is more likely to be realized. However, there is a “massive global teacher shortage” that acts as a critical bottleneck to achieving SDG 4. The 2016 Global Education Monitoring report found that nearly one quarter of secondary school teachers in sub-Saharan Africa had no formal training. Furthermore, continuous teacher professional development for all teachers across the entire school system poses a challenge for many countries, especially developing ones with significant rural-urban and regional gaps, and limited resources.
From the equity, quality and efficiency perspectives, Information and communication technologies (ICTs) have the potential to provide all teachers with cost-effective and quality access to continuous professional development. This presentation discusses the different models of ICT-enabled teacher professional development at scale (TPD@Scale) that have been developed and implemented in China, Colombia, India and the Philippines. It shows how ICT-enabled courses and resources are implemented to ensure consistency of quality and access for all teachers, irrespective of their location and circumstances. It also shows how ICT enables professional learning communities of teachers to network, share and collaborate across schools and regions, and hence, supporting one another as they apply what they have learnt to their practices and reflect on these practices to enhance the quality of their student learning. Therefore, ICT-enabled TPD@Scale is more likely to support school systems to realize SDG4.
Bio: Cher Ping Lim is the Chair Professor of Learning Technologies and Innovation at The Education University of Hong Kong and the Editor-in-Chief of The Internet and Higher Education. He is the lead of the Digital Learning for Development network. He was the Director of the Centre for Learning, Teaching and Technology at the university until 2014 and have been leading and supporting various quality enhancement initiatives in the university. Before joining the university in 2010, he was a Professor of Education, Director of International Partnerships and Director of the Asia-Pacific Centre of Excellence for Teacher Education and Innovations in Western Australia. Over the last two decades, he has engaged major education stakeholders at the national and international levels – UNESCO, Asian Development Bank, Microsoft, World Bank, Inter-American Development Bank, International Development Research Centre, USAID, HEAD Foundation, Sampoerna Foundation, and government agencies – as his research and development partners.
Antonija (Tanja) MITROVIC
University of Canterbury, New Zealand
Title: Towards Personalized Support for Learning Transferable Skills via Active Video Watching (C3)
Friday, November 30, 2018
09:00-10:00, Hall A&B
Intelligent Tutoring Systems and other adaptive learning systems have been shown to provide significant improvement in learning effectiveness in many formal instructional domains. Much less research has been done on supporting training of transferable (a.k.a. soft) skills. In this talk, I will present the research our team has done on providing personalized support for training of presentation skills. Transferable skills are difficult to teach in classrooms, as they are time consuming and it is difficult to collect evidence of learning. Such skills require the learner to appreciate other points of views, and to contextualize learning in their own experience. We implemented the AVW-Space platform, which supports learning from videos supported via micro-scaffolds for reflection during note-taking. Our initial studies showed significant improvements in conceptual understanding of presentation skills for students who watched and comments on videos, and also rated comments written by others. However, other behaviours, such as passive watching of videos, did not result in learning. Using various forms of learning analytics, we identified important differences between students exhibiting various learning behaviours, which allowed us to formulate requirements for adding intelligence to AVW-Space. I will also present the results of a study we are currently conducting, with the version of AVW-Space enhanced with interactive visualizations and personalized nudges.
Bio: Antonija (Tanja) Mitrovic is a professor at the Department of Computer Science and Software Engineering at the University of Canterbury, Christchurch, New Zealand. She is the leader of the Intelligent Computer Tutoring Group. Dr Mitrovic received her PhD in Computer Science from the University of Nis, Yugoslavia, in 1994. She is an associate editor of the following journals: International Journal on Artificial Intelligence in Education, IEEE Transactions on Teaching and Learning Technologies, and Research and Practice in Technology Enhanced Learning (RPTEL). She has published more than 240 journal and conference papers, and was awarded the Distinguished Researcher Award in 2011 by the Asia-Pacific Society for Computers in Education. Professor Mitrovic was the President of the International Society for Artificial Intelligence in Education from 2013 to 2015, and is President Elect of APSCE. Her primary research interests are in student modeling.