Governance

Abelardo Pardo is Professor and Dean Academic at the Division of Information Technology, Engineering and the Environment at the University of South Australia. His research interests include the design and deployment of technology to increase the understanding and improve digital learning experiences. More specifically, his work examines the areas of learning analytics, personalized active learning, and technology for student support.

Maren Scheffel is a junior-professor for educational data science at the Ruhr University Bochum, Germany. With a background in computational linguistics she started to work in the field of technology-enhanced learning in 2009. For her PhD that she obtained from the Open University of the Netherlands in 2017, she developed the Evaluation Framework for Learning Analytics (EFLA). Next to progressing this work further, her research also delves into the connection of learning analytics and learning design as well as visualisation techniques for dashboards. Maren is currently Program Chair of LAK21, member of the editorial board of the Journal of Learning Analytics, and co-chair of the SoLAR Inclusion working group.

Sasha Poquet is a postdoctoral researcher at the Institute for the Application of Learning Science and Educational Technology (ALSET) and the School of Computing at the National University of Singapore. In her role at ALSET, she bridges educator track staff with academic domain experts and IT specialists. Sasha combines her social science background and computational approaches to research peer effects and learning networks in digital settings. Within SoLAR, Sasha chairs a Membership working group that enables information exchange between SoLAR institutional members. She is interested in how institutions adopt learning analytics through the lens of complexity theory, as well as how educators transfer learning analytics to their everyday practices.

Dr. Vitomir Kovanovic is a Research Fellow at the School of Education, University of South Australia and a Data Scientist at the Teaching Innovation Unit, University of South Australia. Vitomir obtained his Ph.D. in Informatics, at the University of Edinburgh, United Kingdom in 2017 for his work on learning analytics within online learning. His research focuses on the development of novel learning analytics systems using learners' trace data records collected by learning management systems with the goal of understanding and improving student learning. Vitomir is particularly interested in students' self-regulation of learning and understanding how trace data can be used to gain a deeper understanding of learning processes. Vitomir is also an Academic Editor at PLOS One journal, for the pedagogy and education sections.

Craig is a Research Analyst in the Centre for Teaching, Learning, and Technology at the University of British Columbia. He works with students, staff, instructors, and administrators to pilot test solutions to teaching and learning challenges through the applied use of learning analytics. Craig holds a Masters degree in Computer Science from the University of Saskatchewan.

Shibani Antonette is a Doctoral Candidate in Learning Analytics at the Connected Intelligence Centre, University of Technology Sydney (UTS), Australia. Her PhD is on Writing Analytics for automated feedback and its integration in higher education practice to improve student writing. More broadly, her research cuts across the fields of data science and education using text analytics to improve teaching and learning contexts. Shibani has been awarded scholarships from ACM-Women in Computing, SoLAR, Asia-Pacific Society for Computers in Education, and UTS to present her research work. She currently chairs the Special Interest Groups within SoLAR. More information at: https://antonetteshibani.com/

Simon Buckingham Shum is Professor of Learning Informatics at the University of Technology Sydney, where serves as inaugural director of the Connected Intelligence Centre. Prior to this, he was Professor of Learning Informatics and Associate Director (Technology) at the UK Open University’s Knowledge Media Institute. He brings a background in Psychology, Ergonomics and Human-Computer Interaction, and a career-long fascination with making thinking visible using software. He has been active in shaping the field of Learning Analytics, and was a founding member of the Society for Learning Analytics Research (SoLAR), with whom he has served as an elected Executive Member and Vice-President. He was Co-Founding Editor of the Journal of Interactive Media in Education, his books include Visualizing Argumentation, Knowledge Cartography and Constructing Knowledge Art, plus journal special issues spanning learning analytics, educational technology, hypermedia and human-computer interaction.

Bodong Chen is an Associate Professor at the University of Minnesota–Twin Cities. He holds the Bonnie Westby Huebner Endowed Chair in Education & Technology and co-directs the Learning Informatics Lab. His research sits at the intersection of learning sciences, learning analytics, online learning, and network science. He develops digital learning environments, analytics applications, and pedagogical practices for collaborative learning. He derives graph metrics to capture discourse patterns, applies relational event modeling to examining socio-temporal dynamics in online discussions, and uses data mining to investigate teacher professional learning in MOOCs.

Nia Dowell is an Assistant Professor in Education at UC-Irvine and director of the Learning Analytics Laboratory (LA-Lab). Her primary interests are in cognitive psychology, discourse processing, group interaction, and learning analytics. Her research focuses on using quantitative measures of language and discourse to reveal the dynamics of socially significant cognitive and affective processes. She is currently applying computational techniques to model discourse and social dynamics in a variety of environments including small group computer- mediated collaborative learning environments, collaborative design networks, and massive open online courses (MOOCs). Her research has also extended beyond the educational and learning sciences spaces and highlighted the practical applications of computational discourse science in the clinical, political and social sciences.

Isabel Hilliger is the Associate Director for Assessment and Evaluation at the Engineering School in Pontificia Universidad Católica de Chile (PUC-Chile). Isabel received a BEng from PUC-Chile and a MA in Policies, Organization and Leadership Studies from Stanford Graduate School of Education in U.S.A. Between 2011 and 2013, Isabel led the development of indicators to evaluate school support programs in Chile as the Associate Coordinator for Pedagogical Technical Assistance in the Ministry for Education. Since then, she has been involved in diverse research projects on educational policy and technology enhanced learning in different countries, including a research fellowship at Laspau, a Harvard-affiliated organization. She is currently a PhD candidate in Computer Science at PUC-Chile and her research focuses on the development of processes and learning analytics tools for continuous improvement of higher education in Latin America. In this context, she has served as a researcher in a project titled ‘Building Capacity to Use Learning Learning Analytics to Improve Higher Education in Latin America-LALA Project’. This project is financed by the European Commission, and Isabel has actively participated in the development of a framework to guide the design and implementation of Learning Analytics tools in Latin American universities.

Yi-Shan Tsai is a research associate at the School of Informatics at the University of Edinburgh, with an affiliation to the Centre for Research in Digital Education. She holds a PhD and an MPhil degree in Education from the University of Cambridge. As an interdisciplinary researcher, her research interests span from learning analytics and digital storytelling to reading cultures and multimodal texts. Her current research focuses on investigating social and cultural factors that influence institutional adoption of learning analytics.