Prof. Rose Luckin Professor of Learner Centred Design UCL Knowledge Lab University College London UK
Topic: How can we build an AI for Education Ecosystem?
Abstract:
COVID-19 has precipitated a major experiment for education systems across the world and this provides an amazing opportunity for AI to assist in the beneficial transformation of teaching and learning that remote and hybrid approaches are likely to catalyse. However, how can educators be ready to leverage AI and how can AI developers be ready to support educators? Each community must help the other to learn and develop their thinking about what kinds of AI technology can best be used for education and training. The research community also has a vital role to play in helping the AIED ecosystem develop. In this talk, I will consider the current stage of AI's application in education and the ways in which AI has supported teachers and learners during the pandemic. I will then look towards the future and consider how AI could be used to support a COVID-compliant transformation for our education systems - a transformation that seeks to enable all learners to achieve their full potential. Throughout the talk I will draw on examples from different AI systems to illustrate what is happening in the present and what could happen in the future. I will suggest a way on which we can bring together educators, developer and researchers to create a healthy and vibrant AIED ecosystem and I will suggest ways in which education systems can become truly 'AI ready.'
Biography:
Rosemary (Rose) Luckin is Professor of Learner Centred Design at UCL. Her research involves blending theories from the learning sciences and techniques from Artificial Intelligence (AI). Rose is author of ‘Machine Learning and Human Intelligence: the future of education in the 21st century’ (2018). Rose is also Director of EDUCATE: a London hub for Educational Technology StartUps, researchers and educators to work together on the development of evidence-informed Educational Technology; Specialist Adviser to the UK House of Commons Education Select Committee for their inquiry into the Fourth Industrial Revolution, Co-founder of the Institute for Ethical AI in Education; a member of the UK Office for Students Horizon Scanning panel, an adviser to the Topol review into the future of the NHS workforce; a member of the European AI Alliance, holder of an International Franqui Chair at KU Leuven; one of the 20 most influential people in Education (Seldon List 2017).
Prof. Xiao-Li Meng Whipple V. N. Jones Professor of Statistics Department of Statistics Harvard University USA
Topic: Ensuring a Healthy Data Science Ecosystem: Pedagogical Challenges and Opportunities
Biography:
Prof. Xiao-Li Meng, the Whipple V. N. Jones Professor of Statistics, and the Founding Editor-in-Chief of Harvard Data Science Review, is well known for his depth and breadth in research, his innovation and passion in pedagogy, his vision and effectiveness in administration, as well as for his engaging and entertaining style as a speaker and writer. Prof. Meng was named the best statistician under the age of 40 by COPSS (Committee of Presidents of Statistical Societies) in 2001, and he is the recipient of numerous awards and honors for his more than 150 publications in at least a dozen theoretical and methodological areas, as well as in areas of pedagogy and professional development. He has delivered more than 400 research presentations and public speeches on these topics, and he is the author of “The XL-Files," a thought-provoking and entertaining column in the IMS (Institute of Mathematical Statistics) Bulletin. His interests range from the theoretical foundations of statistical inferences (e.g., the interplay among Bayesian, Fiducial, and frequentist perspectives; frameworks for multi-source, multi-phase and multi- resolution inferences) to statistical methods and computation (e.g., posterior predictive p-value; EM algorithm; Markov chain Monte Carlo; bridge and path sampling) to applications in natural, social, and medical sciences and engineering (e.g., complex statistical modeling in astronomy and astrophysics, assessing disparity in mental health services, and quantifying statistical information in genetic studies). Prof. Meng received his BS in mathematics from Fudan University in 1982 and his PhD in statistics from Harvard in 1990. He was on the faculty of the University of Chicago from 1991 to 2001 before returning to Harvard, where he served as the Chair of the Department of Statistics (2004-2012) and the Dean of Graduate School of Arts and Sciences (2012-2017).
Prof. Gwo-Jen Hwang Chair Professor Graduate Institute of Digital Learning and Education National Taiwan University of Science and Technology Taiwan
Topic: Applications and Research Issues of Artificial Intelligence in Education
Abstract:
The advancement of artificial intelligence (AI) technologies has attracted the attention of researchers in the globe. However, it remains a challenging task for educational technology researchers to apply AI technologies to school settings, not to mention designing AIED (Artificial Intelligence in Education) studies. In this talk, Prof. Hwang is going to introduce the basic conceptions and applications of AI; following that, potential research issues of AIED are presented. In addition, several examples are given to demonstrate how AI can be used to promote teaching and learning outcomes.
Biography:
Prof. Gwo-Jen Hwang is Chair Professor of Graduate Institute of Digital Learning and Education in National Taiwan University of Science and Technology. He serves as an editorial board member and a reviewer for more than 40 academic journals of educational technology and e-learning. Currently, he is the Editor-in-Chief /Lead Editor of Australasia Journal of Educational Technology (SSCI), International Journal of Mobile Learning and Organisation (Scopus, Q1), Journal of Computers in Education (Scopus, ESCI) and Computers & Education: Artificial Intelligence (Elsevier).
Prof. Hwang has published more than 700 academic papers, including more than 200 SSCI journal papers. Owing to his reputation in academic research and innovative inventions in e-learning, he received the annual most Outstanding Researcher Award from the National Science Council of Taiwan in the years 2007, 2010 and 2013. Moreover, in 2016, he was announced by Times Higher Education as being the most prolific and cited researcher in the world in the field of social sciences:
https://www.timeshighereducation.com/news/ten-most-prolific-and-most-cited-researchers.
Prof. Marcelo Milrad Professor, Vice-Dean Department of Computer Science and Media Technology Linnaeus University Sweden
Topic: A historical view on the evolution of Artificial Intelligence in Education: perspectives, challenges and opportunities
Abstract:
The field of Artificial Intelligence in Education, usually referred to as AIED, can be defined as the use of AI (Artificial Intelligence) techniques and applications utilized in different educational contexts with the purpose of supporting learning, teaching and training. While recent advancements of information and communication technologies have accelerated the implementation of AIED applications, the field itself has existed for more than three decades. In this presentation I will give an overview of how the field of AIED has evolved over the last 30 years with the purpose of identifying the educational, technological and application areas that have been at the core of this evolution. The outcomes of this analysis will be presented and discussed in order to propose some initial considerations regarding current implementations of AI in educational settings. I will also outline some emerging challenges and research issues in this field that can help guide educational researchers interested in carrying out AIED studies. A few examples of work under way at Linnaeus University will be presented in order to illustrate some of these ideas.
Biography:
Prof. Marcelo Milrad is a Full Professor of Media Technology at Linnaeus University (LNU) in Sweden. His current research interests include the areas of Technology-Enhanced Learning (TEL), advanced human-computer interaction and novel uses of Big Data techniques and mobile technologies in the fields of Education & Health Care. Since March 2020, he acts as the main scientific coordinator of LNU´s complete knowledge environment Digital Transformations. Prof. Milrad is also actively involved also in a new initiative at LNU together with colleagues at the Faculty of Arts and Humanities called Digital Humanities. Professor Milrad conducts his research in very close collaboration with industrial partners and the public sector. He has published numerous articles in international journals, refereed conferences, books and technical reports. Prof. Milrad has also been presenting and giving lectures about his work in more than 45 countries worldwide. https://lnu.se/en/staff/marcelo.milrad/
Keynote Speakers
Prof. Rose Luckin
Professor of Learner Centred Design
UCL Knowledge Lab
University College London
UK
Topic:
How can we build an AI for Education Ecosystem?
Abstract:
COVID-19 has precipitated a major experiment for education systems across the world and this provides an amazing opportunity for AI to assist in the beneficial transformation of teaching and learning that remote and hybrid approaches are likely to catalyse. However, how can educators be ready to leverage AI and how can AI developers be ready to support educators? Each community must help the other to learn and develop their thinking about what kinds of AI technology can best be used for education and training. The research community also has a vital role to play in helping the AIED ecosystem develop. In this talk, I will consider the current stage of AI's application in education and the ways in which AI has supported teachers and learners during the pandemic. I will then look towards the future and consider how AI could be used to support a COVID-compliant transformation for our education systems - a transformation that seeks to enable all learners to achieve their full potential. Throughout the talk I will draw on examples from different AI systems to illustrate what is happening in the present and what could happen in the future. I will suggest a way on which we can bring together educators, developer and researchers to create a healthy and vibrant AIED ecosystem and I will suggest ways in which education systems can become truly 'AI ready.'
Biography:
Rosemary (Rose) Luckin is Professor of Learner Centred Design at UCL. Her research involves blending theories from the learning sciences and techniques from Artificial Intelligence (AI). Rose is author of ‘Machine Learning and Human Intelligence: the future of education in the 21st century’ (2018). Rose is also Director of EDUCATE: a London hub for Educational Technology StartUps, researchers and educators to work together on the development of evidence-informed Educational Technology; Specialist Adviser to the UK House of Commons Education Select Committee for their inquiry into the Fourth Industrial Revolution, Co-founder of the Institute for Ethical AI in Education; a member of the UK Office for Students Horizon Scanning panel, an adviser to the Topol review into the future of the NHS workforce; a member of the European AI Alliance, holder of an International Franqui Chair at KU Leuven; one of the 20 most influential people in Education (Seldon List 2017).
Prof. Xiao-Li Meng
Whipple V. N. Jones Professor of Statistics
Department of Statistics
Harvard University
USA
Topic:
Ensuring a Healthy Data Science Ecosystem: Pedagogical Challenges and Opportunities
Biography:
Prof. Xiao-Li Meng, the Whipple V. N. Jones Professor of Statistics, and the Founding Editor-in-Chief of Harvard Data Science Review, is well known for his depth and breadth in research, his innovation and passion in pedagogy, his vision and effectiveness in administration, as well as for his engaging and entertaining style as a speaker and writer. Prof. Meng was named the best statistician under the age of 40 by COPSS (Committee of Presidents of Statistical Societies) in 2001, and he is the recipient of numerous awards and honors for his more than 150 publications in at least a dozen theoretical and methodological areas, as well as in areas of pedagogy and professional development. He has delivered more than 400 research presentations and public speeches on these topics, and he is the author of “The XL-Files," a thought-provoking and entertaining column in the IMS (Institute of Mathematical Statistics) Bulletin. His interests range from the theoretical foundations of statistical inferences (e.g., the interplay among Bayesian, Fiducial, and frequentist perspectives; frameworks for multi-source, multi-phase and multi- resolution inferences) to statistical methods and computation (e.g., posterior predictive p-value; EM algorithm; Markov chain Monte Carlo; bridge and path sampling) to applications in natural, social, and medical sciences and engineering (e.g., complex statistical modeling in astronomy and astrophysics, assessing disparity in mental health services, and quantifying statistical information in genetic studies). Prof. Meng received his BS in mathematics from Fudan University in 1982 and his PhD in statistics from Harvard in 1990. He was on the faculty of the University of Chicago from 1991 to 2001 before returning to Harvard, where he served as the Chair of the Department of Statistics (2004-2012) and the Dean of Graduate School of Arts and Sciences (2012-2017).
Prof. Gwo-Jen Hwang
Chair Professor
Graduate Institute of Digital Learning and Education
National Taiwan University of Science and Technology
Taiwan
Topic:
Applications and Research Issues of Artificial Intelligence in Education
Abstract:
The advancement of artificial intelligence (AI) technologies has attracted the attention of researchers in the globe. However, it remains a challenging task for educational technology researchers to apply AI technologies to school settings, not to mention designing AIED (Artificial Intelligence in Education) studies. In this talk, Prof. Hwang is going to introduce the basic conceptions and applications of AI; following that, potential research issues of AIED are presented. In addition, several examples are given to demonstrate how AI can be used to promote teaching and learning outcomes.
Biography:
Prof. Gwo-Jen Hwang is Chair Professor of Graduate Institute of Digital Learning and Education in National Taiwan University of Science and Technology. He serves as an editorial board member and a reviewer for more than 40 academic journals of educational technology and e-learning. Currently, he is the Editor-in-Chief /Lead Editor of Australasia Journal of Educational Technology (SSCI), International Journal of Mobile Learning and Organisation (Scopus, Q1), Journal of Computers in Education (Scopus, ESCI) and Computers & Education: Artificial Intelligence (Elsevier). Prof. Hwang has published more than 700 academic papers, including more than 200 SSCI journal papers. Owing to his reputation in academic research and innovative inventions in e-learning, he received the annual most Outstanding Researcher Award from the National Science Council of Taiwan in the years 2007, 2010 and 2013. Moreover, in 2016, he was announced by Times Higher Education as being the most prolific and cited researcher in the world in the field of social sciences: https://www.timeshighereducation.com/news/ten-most-prolific-and-most-cited-researchers.
Prof. Marcelo Milrad
Professor, Vice-Dean
Department of Computer Science and Media Technology
Linnaeus University
Sweden
Topic:
A historical view on the evolution of Artificial Intelligence in Education: perspectives, challenges and opportunities
Abstract:
The field of Artificial Intelligence in Education, usually referred to as AIED, can be defined as the use of AI (Artificial Intelligence) techniques and applications utilized in different educational contexts with the purpose of supporting learning, teaching and training. While recent advancements of information and communication technologies have accelerated the implementation of AIED applications, the field itself has existed for more than three decades. In this presentation I will give an overview of how the field of AIED has evolved over the last 30 years with the purpose of identifying the educational, technological and application areas that have been at the core of this evolution. The outcomes of this analysis will be presented and discussed in order to propose some initial considerations regarding current implementations of AI in educational settings. I will also outline some emerging challenges and research issues in this field that can help guide educational researchers interested in carrying out AIED studies. A few examples of work under way at Linnaeus University will be presented in order to illustrate some of these ideas.
Biography:
Prof. Marcelo Milrad is a Full Professor of Media Technology at Linnaeus University (LNU) in Sweden. His current research interests include the areas of Technology-Enhanced Learning (TEL), advanced human-computer interaction and novel uses of Big Data techniques and mobile technologies in the fields of Education & Health Care. Since March 2020, he acts as the main scientific coordinator of LNU´s complete knowledge environment Digital Transformations. Prof. Milrad is also actively involved also in a new initiative at LNU together with colleagues at the Faculty of Arts and Humanities called Digital Humanities. Professor Milrad conducts his research in very close collaboration with industrial partners and the public sector. He has published numerous articles in international journals, refereed conferences, books and technical reports. Prof. Milrad has also been presenting and giving lectures about his work in more than 45 countries worldwide.
https://lnu.se/en/staff/marcelo.milrad/