Keynote Speakers

Title: Easy Authoring of Adaptive Tutoring Software
	Vincent Aleven Professor of Human-Computer Interaction Carnegie Mellon University Vincent Aleven is a Professor of Human-Computer Interaction at Carnegie Mellon University in Pittsburgh, Pennsylvania, USA, where he is also the Director of Undergraduate Programs in Human-Computer Interaction. He has 25 years of experience in research and development of adaptive learning technologies. His work is based on cognitive theory and self-regulated learning theory, with a focus on high-school and middle-school mathematics in the United States. He has investigated widely how such technologies can be most effective, with projects ranging from computer-based tutoring of help seeking, to a website with intelligent tutoring software for middle-school mathematics, to a real-time mixed-reality teacher awareness tool. He and his colleagues have also created easy-to-use, easy-to-learn authoring tools for adaptive learning technologies. Vincent Aleven has over 250 publications to his name. He is co-editor-in-chief of the International Journal of Artificial Intelligence in Education. He also was co-editor of the International Handbook on Metacognition in Computer-based Learning Environments. He and his colleagues and students have won 10 best paper awards at international conferences. He is or has been PI on 12 major research grants and co-PI on 11 others. He holds a PhD in Intelligent Systems from the University of Pittsburgh, Pennsylvania, USA, and an M.Sc. in Informatics from Delft University of Technology, Delft, the Netherlands. Keynote address Adaptive tutoring software based on AI technology is capable of adjusting to learners, specifically, their similarities, differences, and growth. For example, such systems might transition from explaining examples to solving open problems at just the moment where the examples start having diminishing returns, which may be different for each individual. Also, such systems might give feedback not only on task performance at the domain-level but also on how students self-regulate their learning (e.g., seek help as needed). Scientific studies show that many forms of adaptivity can be more effective than a “one-size-fits-all” approach to instruction. Given that adaptive learning technologies can be complex and have traditionally been hard to develop, it is important to lower the barriers to creating adaptive tutoring software, for example with easy-to-learn, easy-to-use authoring tools. But what forms of adaptivity should such tools support, and how might they make authoring as fast and easy as possible? In this talk, I present an "Adaptivity Grid" that helps categorize different forms of adaptivity in learning technologies. I then present a mature and proven set of authoring tools that my colleagues and I have created, namely, the Cognitive Tutor Authoring Tools (CTAT), which are freely available for non-commercial purposes. I illustrate how these tools support authors in creating many forms of adaptive tutoring captured in the Adaptivity Grid, without requiring extensive programming. I discuss lessons learned over 18 years, in building these tools, using them, and helping others use them. I close by discussing how authoring tools might be instrumental in bringing AI-based adaptive learning technologies to more classrooms.

Title: Measuring Self-regulatory Processes During Learning with Advanced Learning Technologies Using Multimodal Multichannel Process Data
	Roger Azevedo Professor Department of Learning Sciences and Educational Research University of Central Florida Roger Azevedo is a Professor in the Department of Learning Sciences and Educational Research at the University of Central Florida. He is also an affiliated faculty in the Department of Computer Science and the University of Central Florida and the lead scientist for the Learning Sciences Faculty Cluster Initiative. His main research area includes examining the role of cognitive, metacognitive, affective, and motivational self-regulatory processes during learning with advanced learning technologies (e.g., intelligent tutoring systems, hypermedia, multimedia, simulations, serious games, immersive virtual learning environments). More specifically, his overarching research goal is to understand the complex interactions between humans and intelligent learning systems by using interdisciplinary methods to measure cognitive, metacognitive, emotional, and motivational processes and their impact on learning, performance, and transfer. To accomplish this goal, he conducts laboratory, classroom, and in-situ (e.g., medical simulator) studies and collects multi-channel data to develop models of human-computer interaction; examines the nature of temporally unfolding self- and other-regulatory processes (e.g., human-human and human-artificial agents); and, designs intelligent learning and training systems to detect, track, model, and foster learners, teachers, and trainers’ self-regulatory processes. He has published over 200 peer-reviewed papers, chapters, and refereed conference proceedings in the areas of educational, learning, cognitive, educational, and computational sciences. He is the editor of the Metacognition and Learning journal and serves on the editorial board of several top-tiered learning and cognitive sciences journals (e.g., International Journal of AI in Education, European Journal of Psychological Assessment). His research is funded by the National Science Foundation, Institute of Education Sciences, National Institutes of Health, and the Social Sciences and the Humanities Research Council of Canada, Natural and Sciences and Engineering Council of Canada, Canada Research Chairs, and Canadian Foundation for Innovation. He is a fellow of the American Psychological Association and the recipient of the prestigious Early Faculty Career Award from the National Science Foundation. Keynote address Learning involves the real-time deployment of cognitive, affective, metacognitive, and motivational (CAMM) processes. Traditional methods of measuring self-regulatory processes (e.g., self-reports) severely limit our understanding of the temporal nature and role of these processes during learning, problem solving, etc. Interdisciplinary researchers have recently used advanced learning technologies (e.g., intelligent tutoring systems, serious games, simulations, virtual reality) to measure (i.e., detect, track, model) and foster self-regulatory processes during learning and problem solving. Despite the emergence of interdisciplinary research, much work is still needed given the various theoretical models and assumptions, methodological approaches (e.g., log-files, eye-tracking), data types (e.g., verbal data, physiological data), analytical methods, etc. In this presentation, I will present an interdisciplinary data fusion approach to measuring and fostering self-regulated learning with advanced learning technologies. More specifically, I will focus on: (1) presenting major theoretical and methodological challenges for a data fusion approach that focus on the real-time detection, tracking, and modeling of CAMM processes; (2) presenting recent multimodal multichannel data used to detect, track, and model CAMM processes while learning with advanced learning technologies; and, (3) outlining an interdisciplinary research agenda that has the potential to significantly enhance advanced learning technologies’ ability to provide real-time, intelligent support of learners’ CAMM processes.

Title: Big Data and Education: Designing for Alternative Futures
	Rebecca Eynon Senior Research Fellow Oxford Internet Institute and Department of Education University of Oxford At the University of Oxford, Rebecca Eynon holds a joint appointment between the Department of Education and the Oxford Internet Institute (OII). Rebecca Eynon is a Sociologist of Education, specialising in the relationships between social inequalities, learning and technology. She has published over 75 books, articles and reports including Teenagers and Technology (with Davies, 2013) and Education and Technology: Major Themes in Education (with Davies, 2015). She has been co-editor of Learning, Media and Technology since 2011. Her work has been supported by a wide range of funders including the Bill and Melinda Gates Foundation, the British Academy, the European Commission, Google and the NominetTrust. Rebecca’s current research (and forthcoming book with Oxford University Press) examines how the use of data in schools is shaping the future of education. Keynote address A core feature of the Digital Age is the trillions of data traces that we leave as we go about our everyday lives: working, communicating, shopping, relaxing, exercising, and learning. Large scale data is now used to inform healthcare decisions, predict crime and prevent terrorism, inform energy decisions, plan cities, guide the financial markets, and influence shopping habits. Data is promoted as a foundational resource that will change our understanding of science and the world; transforming our lives by making decision making more efficient, accurate and effective. Education is no exception to this rule. Research and practice that utilise Big Data to inform decisions at all levels of Education is gaining ground. Yet, there remain many issues to explore in this exciting area. Taking a Sociological perspective this presentation will open up the ‘black box’ of the use of large scale data, to examine how the processes and uses of Big Data within Education are shaped by different actors. It will explore the different implications of such approaches for schools, teachers and students exploring the extent to which data may be reinforcing or changing educational futures; and suggest approaches to the development and use of data for assessment that shape education in ways that offer a positive and fair future for all.

Title: Applying Emerging Technologies in the Education System in China: Achievements and Challenges
	Jiyou Jia Professor & Director Department of Educational Technology Graduate School of Education Director, International Research Center for Education and Information Peking University Dr Jiyou Jia is Full Professor and Director at the Department of Educational Technology, Graduate School of Education, Peking University, China, and also the Founding Director of the International Research Center for Education and Information at Peking University. In 2017 and 2018, Dr Jia served as Distinguished Professor at the Institute for Research in Open and Innovative Education, the Open University of Hong Kong. Since 2015, he has served as a Visiting Professor at the School of Education, Technical University of Munich, Germany. Dr Jia received a BSc and a Master of Education from Peking University, and completed his PhD in artificial intelligence from Augsburg University, Germany. His research interests include educational technology and artificial intelligence in education, especially in TELL (Technology Enhanced Language Learning), math education with ICT, and decision making support system. He has been responsible for a dozen national projects and international cooperation projects. His research has won a number of national and international prizes, including the First Class Award of the Fifth National Award for Outstanding Achievements in Educational Research, from the Ministry of Education, China, in 2016, and IAAI (Innovative Application of Artificial Intelligence) Deployed Application Award by AAAI (Association of Advancement of Artificial Intelligence), USA, in 2008. Dr Jia has published more than 100 articles in international or national peer-reviewed journals and conferences including Computers and Education, and Knowledge-Based Systems. He has also edited and authored several books. Keynote address The application of emerging technologies including ICT (information and communications technology) and artificial intelligence in education has drawn much attention from the central and local government and enterprises in China in the past decades. With high expectations, corresponding policies and investments have been made to promote the application that has led to a wide range of achievements. Yet there are also challenges to overcome. This keynote will first review the developments and summarize the achievements in past years — covering the increasing use of rich open educational resources from video lecture portals to massive open online courses; modern ICT equipment and devices in the classroom from multimedia computers, interactive and electronic whiteboards or televisions, to tablet computers and smart phones; advanced computer, wireless and mobile networks from LAN, WLAN to 4G network; and educational software systems from course management systems, intelligent tutoring systems to management information systems. Then the speech will address the challenges confronting the nation and its education system, including the great demand for teacher training and more intelligent systems, as well as the unbalance in the development among geographical areas. Based on the experience in China, the future work for transforming its education delivery with technological advances will be discussed.

Title: The Representation of Disciplinary Activity in STEM Education
	Todd Campbell Professor of Science Education Department of Curriculum and Instruction Neag School of Education University of Connecticut Todd Campbell is a Professor of science education and faculty member in the Neag School of Education. He is currently Co-Editor in Chief for the Journal of Science Teacher Education, the flagship journal for the Association for Science Teacher Education, and Principal Investigator or Co-Principal Investigator on projects supported by the National Science Foundation and the U.S. Department of Agriculture. His research focuses on cultivating imaginative and equitable representations of STEM activity. This is accomplished in formal science learning environments through partnering with pre-service and in-service science teachers and leaders to collaboratively focus on supporting student use of modeling as an anchoring epistemic practice to reason about events that happen in the natural world. This work extends into informal learning environments through a focus on the iterative design of informal learning spaces and equity focused STEM identity research. Todd Campbell has published his research in venues ranging from the Review of Educational Research to the International Journal of Science Education in more than 70 peer reviewed manuscripts. He is a former middle school and high school science teacher. Keynote address Representing disciplinary activity in STEM education finds its importance when considered in the context of situated, sociocultural, and resource perspectives on learning. These theoretical perspectives of learning point to the central role of context, social negotiation, and fine-grained resources students draw on when reasoning. Given this, recent efforts to reform STEM education in the U.S. have focused on engaging students in representation of disciplinary activity in STEM education through positioning them to construct and critique explanations of events that happen in the world or solve problems of consequence. The problem space created by positioning students with aims similar to those pursued by disciplinary STEM professionals (e.g., scientists, engineers) provides students not only with a sense of the knowledge production practices of the disciplines (e.g., developing and using models, planning and carrying investigations), but also a sense of the explanatory power of disciplinary ideas and how and when they can be applied. Consequently, this keynote focuses on unpacking a theoretical basis for the representation of disciplinary activity in STEM education, while also providing examples of resources and tools useful for taking up these more innovative forms of teaching and learning in classrooms.

Title: Assessment of 21st Century Skills Key to the Fostering of STEAM Professionals in the Information Age
	Kwok-cheung Cheung Professor of Curriculum and Instruction Faculty of Education University of Macau Kwok-cheung Cheung is Professor of Curriculum and Instruction in the Faculty of Education at the University of Macau. He received his doctoral degree in Science Education from King’s College, the University of London. He is the Director of the Educational Testing and Assessment Research Centre in the University of Macau, and National Project Manager of the Macao-China PISA Study (with six cycles from PISA 2009 to PISA2021). His areas of specialization are: (1) educational evaluation of K-12 mathematics and science education; (2) assessment of 21st century skills; and (3) analysis of large-scale sampled survey data from an international comparative education perspective. He is now serving as: (1) Consultative Expert for the Macao Government Non-tertiary Education Mid- to Long-term Ten-year 2021–2030 Planning Committee; (2) Core Consultative Committee Member of the 2017 Chinese National Science Assessment, Collaborative Innovation Center of Assessment toward Basic Education Quality, Beijing Normal University, China; (3) Consultative Expert for the Mainland China-PISA 2018, Basic Education Quality Monitoring Centre, Ministry of Education, China. His publications are multifarious, including SSCI journal articles, books and monographs, and consultancy reports. (For details, see http://www.um.edu.mo/fed/staff/KCCheung/index.htm). Keynote address The past two decades — both locally and worldwide — have witnessed the promotion of STEAM (Science, Technology, Engineering, Arts and Mathematics) education in the K-12 formal school curriculum. The main aim of STEAM education across countries/economies is to educate qualified professionals to prepare them for lifelong careers related to the interdisciplinary STEAM fields. While there are different approaches to the practice of STEAM education in the mathematics, science and technology school curriculum, central to the classroom practices are the fostering of three 21st century skills considered vital for creative problem-solving in the information age, viz. collaboration, computational thinking, and creative thinking. This presentation is about how these three skills are to be assessed for the purposes of learning and development, based on the literacy assessment frameworks of the OECD’s PISA 2015 and PISA 2021 Studies, followed by elucidation of illustrative test units of STEAM activities.