|Angela Liegey Dougall, Ph.D. | Psychology
Angela Liegey Dougall, PhD is an Associate Professor in the Department of Psychology at the University of Texas at Arlington. She received her doctorate at the University of Pittsburgh in Health Psychology and completed post-doctoral work as a biostatistician and research assistant professor at the University of Pittsburgh Cancer Institute and the University of Pittsburgh. As a faculty member at the University of Texas at Arlington, her lines of programmatic research focus on identifying biological, psychological, behavioral, and social mechanisms and risk factors for outcomes, such as behavior change, academics, and physical and mental health. She is currently examining the impact of technology on socioemotional processes of learning. In particular, she is examining the use of smartphones as both a possible hindrance and a possible facilitator of academic and health outcomes among college students.
|Henry Anderson | Language Analytics
Henry is a research scientist and the resident Language Analyst at LINK. He holds a bachelor’s degree from Rice University in Physics and Linguistics. He is interested in how big language data can be leveraged to provide insight and solutions to a wide range of problems, as well as language use in digital contexts, especially how it is used to construct and reflect identity in online communities and how digital media create unique structures and patterns of communication. LINK Research Projects: IDEAS Center, COCOA.
|Dragan Gasevic, Ph.D. | Research Scientist
Dr. Gasevic is a Professor and the Canada Research Chair in Semantic and Learning Technologies in the School of Computing and Information Systems at Athabasca University. Dragan is a co-founder and the current President-Elect of the Society for Learning Analytics Research. He is also an Adjunct Professor in the School of Interactive Arts and Technology at Simon Fraser University, Associate Adjunct Professor in the Learning and Teaching Unit at the University of South Australia, and an IBM CAS Faculty Fellow. A computer scientist by training and skill, Dragan considers himself a learning and information scientist developing computational methods that can shape next-generation learning and software technologies and advance our understanding of information-seeking, sense-making, self-regulated and social learning. The award-winning work of his team on the LOCO-Analytics software is considered one of the pioneering contributions in the growing area of learning analytics.
|Shane Dawson, Ph.D. | Research Scientist
Associate Professor Shane Dawson is the Director of the Learning and Teaching Unit, and Associate Professor of Technology Enhanced Learning at the University of South Australia. His research activities focus on learning analytics and social networks to inform teaching and learning theory and practice. Shane’s research has demonstrated the use of learner interaction and network data to provide lead indicators of self-regulated learning, student sense of community, academic success and course satisfaction. Shane has also been involved in developing pedagogical models designed to build student creative capacity. He is a co-founder and executive member of the Society for Learning Analytics Research and was co-chair of the 2012 Learning Analytics and Knowledge conference in Vancouver, Canada.
|Abelardo Pardo, Ph.D. | Research Scientist
Dr. Pardo is the Associate Head of Teaching and Learning and a Senior Lecturer at the School of Electrical and Information Engineering, at the University of Sydney. He has a PhD in Computer Science from the University of Colorado at Boulder. He is the director of the Learning and Affect Technologies Engineering Laboratory, specialized in the design of adaptive and personalized software systems for learning. His areas of research are learning analytics, software tools for collaboration and personalized learning processes, and software systems to improve teaching practice and student outcomes. He has participated in national and international projects funded by the Office for Teaching and Learning (Australia), the National Science Foundation (USA), and the European Union. He serves as member of the editorial boards of the IEEE Transactions on Learning Technology and the Journal of Social Media and Interactive Learning Environments. He is also member of the executive board of the Society for Learning Analytics Research (SoLAR).
|Ryan Baker, Ph.D. | Research Scientist
Ryan Baker is Associate Professor of Cognitive Studies and Program Coordinator for Learning Analytics at the University of Pennsylvania. He earned his Ph.D. in Human-Computer Interaction from Carnegie Mellon University. Baker was previously Assistant Professor of Psychology and the Learning Sciences at Worcester Polytechnic institute, and he served as the first Technical Director of the Pittsburgh Science of Learning Center DataShop, the largest public repository for data on the interaction between learners and educational software. He was the founding President of the International Educational Data Mining Society, and is Associate Editor of the Journal of Educational Data Mining and Associate Editor of the International Journal of Artificial Intelligence in Education. His research combines educational data mining and quantitative field observation methods in order to better understand how students respond to educational software, and how these responses impact their learning. He studies these issues within intelligent tutors, simulations, multi-user virtual environments, and educational games, within populations from pre-schoolers, to middle school students, to military trainees.
|Nia Dowell, Ph.D. | Research Scientist
Nia Dowell is a postdoctoral research fellow in the School of Information and Digital Innovation Greenhouse at the University of Michigan. She completed her Ph.D. at the Institute for Intelligent Systems in the University of Memphis under the advisement of Professor Arthur Graesser. Her primary interests are in cognitive psychology, discourse processing, group interaction dynamics, and learning sciences. In general, her research focuses on using language and discourse to uncover 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 areas.
|Vitomir Kovanović, Ph.D. | Research Fellow
Vitomir Kovanović is a research fellow at the University of South Australia. He recently completed his Ph.D. at the University of Edinburgh in the School of Informatics. He has also worked as a research assistant for the Learning Innovation and Networked Knowledge (LINK) Research Lab at the University of Texas at Arlington. Vitomir’s research in Learning Analytics and Educational Data Mining focuses on the development of novel learning analytics methods based on the trace data collected by learning management systems and their use to improve inquiry-based online education. He currently serves on the executive committee of the Society for Learning Analytics Research (SoLAR).
|Srećko Joksimović, Ph.D. | Data Scientist
Srećko Joksimović is a data scientist at the University of South Australia. He recently completed his Ph.D. at the Moray House School of Education at the University of Edinburgh, United Kingdom, working under the supervision of Prof. Dragan Gašević (University of Edinburgh), in the Learning Analytics research field. He is an executive committee member of the Society for Learning Analytics Research (SoLAR) and worked as a research assistant for the Learning Innovation and Networked Knowledge (LINK) Research Lab at the University of Texas at Arlington. With a background in computer science, Srećko’s research interests center around the analysis of teaching and learning in networked learning environments.