Programme
Prof. Dirk Ifenthaler
Chair of Learning, Design and Technology
University of Mannheim
UNESCO Deputy Chair of Data Science in Higher Education Learning and Teaching
Curtin University
Abstract
Learning analytics, a socio-technical data mining and analytic practice in educational contexts, show promise in supporting learning processes and enhancing study success in higher education, through collecting and analysing data from learners, learning processes, and learning environments to provide meaningful feedback and scaffolds when needed. However, learning analytics have seen a dominance in data-driven analytics approaches, not necessarily focussing on learning or psychological theory. Accordingly, data indicators for learning analytics identify a majority of data-driven approaches. This presentation will review learning analytics indicators from several systematic reviews grounded in learning and psychological theory. Further, the challenges of implementing indicators into productive higher education ecosystems will be highlighted.
Bio
Dirk Ifenthaler is Professor and Chair of Learning Design and Technology at the University of Mannheim, Germany, and UNESCO Deputy Chair on Data Science in Higher Education Learning and Teaching at Curtin University, Australia. Dirk's research focuses on the intersection of cognitive psychology, educational technology, data analytics, and organisational learning. He is the Editor-in-Chief of the Technology Knowledge and Learning and Senior Editor of the Journal of Applied Research in Higher Education (www.ifenthaler.info • dirk@ifenthaler.info)
Date
19 December 2022
(Monday)
Time
5:00 pm–6:00 pm
(HK Time)
Prof. Shane Dawson
Executive Dean of UniSA Education Futures
Professor of Learning Analytics
University of South Australia
Abstract
The field of Learning Analytics (LA) brings together expertise from a range of disciplines to collect, explore and analyse student data to understand and optimise learning processes. The field has grown rapidly, advancing in both research and application through the use of emergent technologies, policies, measures of education quality, and general teaching practice. This talk unpacks the development of LA and changes in focus of research from predictive models to sensemaking and more recently assessment of learner capabilities. Although there has been much LA research undertaken – the challenge in realising how LA can have a positive impact on education systems remains. Research in LA is a combination of discovery and application. There is a vast array of discovery and exploratory research that details the potential for LA to have a system wide impact. However, to date, systemic change has not occurred – education systems remain resilient to change and LA has largely failed to realise its much touted potential. Without a purposeful pursuit to understand the applied nature of LA and specifically, the socio-technical dimensions the field will not produce the required system-level change. This presentation will detail the role of learner profiles and a tighter LA discovery-application nexus to demonstrate how a systems research orientation can better influence education policy and practice and realise the potential of LA to promote the institutional adoption of personalised learning models.
Bio
Shane Dawson is the Executive Dean of UniSA Education Futures and Professor of Learning Analytics at the University of South Australia. He has published widely on topics from creative capacity to social network analysis and the application of learner ICT interaction data to inform and benchmark teaching and learning quality. His current research interests relate to complex systems and academic leadership to aid adoption and application of advanced technologies and analytics in education. With the support of many talented colleagues, Shane has been involved in the development of numerous open source software including the Online Video Annotations for Learning (OVAL), OnTask (a personalised learner feedback tool), and SNAPP, a social network visualisation tool designed for teaching staff to better understand, identify and evaluate student learning, engagement, academic performance and creative capacity.
He is a founding executive member of the Society for Learning Analytics Research, past program and conference chair of the International Learning Analytics and Knowledge conference and inaugural co-editor of the Journal for Learning Analytics. Shane has been deeply involved with supporting the development of the field of Learning Analytics for well over a decade.
Date
9 December 2022
(Friday)
Time
5:00 pm–6:00 pm
(HK Time)
Prof. Sanna Järvelä
Professor
Learning sciences and educational technology
Department of Educational Sciences and Teacher Education
University of Oulu, Finland
Abstract
Learners should be active participants when studying, learning and living with AI, not algorithms, and to do that, they need to develop their self-regulated learning (SRL) skills. New AI-enhanced technological solutions are needed to develop self-regulated learners across the globe. In this talk I will introduce SRL and socially shared regulation (SSRL) and how digital data, multimodal analytics and AI-based methods have helped us to progress in this area of research. I stress that systematic understanding of human learning process is needed to leverage full potential of data to help learners and AI to collaborate and learn together.
Bio
Sanna Järvelä is a professor in learning sciences and head of the Learning and Educational Technology Research Lab (LET) in the University of Oulu, Finland. Her research interests deal with self-regulated learning, computer supported collaborative learning and AI in education. Järvelä and her research group is internationally recognized in theoretical and methodological advancement of social aspects of self-regulated learning (socially shared regulation in learning) and multimodal research methods. She has published extensively and her google scholar h-index is 66. She is currently the co-Chief Editor in the International Journal of Computer Supported Collaborative Learning. Järvelä has been invited for the member of the Finnish Academy of Science and Letters in 2015 and she is the past European Association for Research on Learning and Instruction (EARLI) president. She is a member of the OECD PISA 2025 'Learning in the Digital World' expert team and co-PI of the Center for Learning and Living with AI (CELLA) funded by Jacobs Foundation.
Date
22 November 2022
(Tuesday)
Time
3:00 pm–4:00 pm
(HK Time)
Prof. Gwo-Jen Hwang
Chair Professor, Graduate Institute of Digital Learning and Education
Dean, College of Liberal Arts and Social Sciences
National Taiwan University of Science and Technology
Abstract
Most of experimental e-learning studies adopt tests and questionnaires to examine learners' achievements and perceptions before and after receiving different learning approaches, while their behaviors and interactive content during the learning process are often ignored. Knowing what have happened during the learning process is important for researchers to explain why an intervention is effective. It also provides valuable information for instructors to improve their learning designs. To further investigate the factors affecting students' learning outcomes and to provide supports to individual students, it is important to analyze the data generated by them during the learning process. In this talk, Prof. Hwang is going to present the methods and tools for analyzing the data collected from the students' learning process, such as their learning logs and interactive content recorded by the system, to identify the problems the learners have encountered. Several authentic examples will be given to demonstrate how the value of an e-learning study can be promoted with learning analytics.
Bio
Dr. Gwo-Jen Hwang is currently a Chair Professor at the National Taiwan University of Science and Technology. Dr Hwang serves as an editorial board member and a reviewer for more than 50 academic journals of educational technology and e-learning. He is currently editor-in-chief of Computers & Education: Artificial Intelligence (SCOPUS), editor-in-chief of International Journal of Mobile Learning and Organisation (Scopus, Q1), editor-in-chief of Journal of Computers in Education (Scopus, ESCI), associate editor of PLOS ONE (SCI), and associate editor of IEEE Transactions on Education (SCI). He has also been the principal investigator of more than 150 research projects funded by Ministry of Science and Technology as well as Ministry of Education in Taiwan. His research interests include mobile and ubiquitous learning, flipped learning, digital game-based learning, and artificial intelligence in education.
Dr. Hwang has published nearly 800 academic articles, including more than 350 papers published in SSCI journals. Owing to the 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 of 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).
Date
10 November 2022
(Thursday)
Time
11:00 am–12:00 nn
(HK Time)
Prof. Dragan Gasevic
Distinguished Professor of Learning Analytics
Department of Data Science and Artificial Intelligence
Faculty of Information Technology
Director of the Centre for Learning Analytics
Monash University
Abstract
Since its emergence, learning analytics has attracted much attention across all levels of education and beyond. While some exciting results have been achieved, the widespread impact is yet to be fully unlocked. This talk will focus on the cutting-edge research trends that aim to address critical challenges the field of learning analytics is presently facing. The talk will first discuss the approaches aiming to improve the quality of data that are collected and used in learning analytics. The talk will then discuss novel approaches for data analysis that harness the potential of advances in artificial intelligence. Finally, the talk will discuss the promising approaches such as personalized feedback and data storytelling that seek to support stakeholders in transforming their practice.
Bio
Dragan Gasevic is Distinguished Professor of Learning Analytics in the Department of Data Science and Artificial Intelligence of the Faculty of Information Technology and the Director of the Centre for Learning Analytics at Monash University. He is a founder and served as the President (2015-2017) of the Society for Learning Analytics Research (SoLAR). He has also held several honorary appointments in Asia, Australia, Europe, and North America. In 2022, he received the Life-time Member Award as the highest distinction of SoLAR. In 2019-2021, he was recognized as the national field leader in educational technology in The Australian's Research Magazine. He led the EU-funded SHEILA project that received the Best Research Project of the Year Award (2019) from the Association for Learning Technology. Dragan's research interests center around data analytic and design methods that advance understanding of self-regulated and collaborative learning.
Date
20 October 2022
(Thursday)
Time
11:30 am–12:30 pm
(HK Time)
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