Dr. James Paul Gee is the Mary Lou Fulton Presidential Professor of Literacy Studies and a Regents’ Professor at Arizona State University. He is a member of the National Academy of Education. He earned his BA in philosophy at the University of California at Santa Barbara and his MA and PhD in linguistics from Stanford University. He has been a faculty member at Hampshire College in Amherst, Massachusetts; Boston University; University of Southern California; Clark University in Worcester, Massachusetts; and the University of Wisconsin, Madison. He works in both linguistics and education.
When anyone speaks or writes there are always two “authors”. One “author” is an individual who always speaks or writes as part of a social network of other individuals. This fact follows from the fact that there can be no “private languages” (following Wittgenstein). The other author is a (“big D”) Discourse that speaks and writes as an historical entity using human individuals as “carriers”. Discourses give (transformable) meaning to what individuals say, write, and do and individuals continually produce, reproduce, and transform Discourses.
Epistemic Network Analysis (ENA) can be seen as operating at three interacting levels: (a) the ways in which individual contributions gain meaning in an interactive social network of individuals; (b) the ways in which Discourses gain meaning in an interactive network of Discourses; and (c) how the two levels reciprocally interact to produce “specific universals”. What ties these three levels together are processes of “mind/society” recognition of socially situated identities and activities mediated by grammar (code) and situation (context).
Dragan Gašević is Professor of Learning Analytics in the Faculty of Education and Adjunct Professor in the Faculty of Information Technology at Monash University. Before the current post (Feb 2015-Feb 2018), he was Professor and Chair in Learning Analytics and Informatics in the Moray House School of Education and the School of Informatics and Co-Director of Centre for Research in Digital Education at the University of Edinburgh. He was the Canada Research Chair in Semantic and Learning Technologies and Professor in the School of Computing and Information Systems at Athabasca University between Jan 2007 and Jan 2015. He served as the immediate past President (2015-2017) of the Society for Learning Analytics Research and holds several honorary appointments in Australia, Canada, Hong Kong, UK, and USA.
This talk will explore connections between two emerging fields focused on harnessing the potential of data – learning analytics and quantitative ethnography. Learning analytics is focused on the analysis of data collected from user interactions with technology with the goal of advancing our understanding of and enhancing human learning. Despite some early success stories and widespread interest, producing meaningful and actionable results is still a top open research challenge for learning analytics. The talk will first explore how quantitative ethnography can offer promising approaches that can address this open challenge in learning analytics. The talk will next discuss how progress in learning analytics can be used to accelerate the development of the field of quantitative ethnography. The talk will finally outline promising directions for future research at the intersection of learning analytics and quantitative ethnography.
Golnaz Arastoopour Irgens is Assistant Professor of Learning Sciences in the College of Education at Clemson University. She earned her B.S. in Mechanical Engineering from the University of Illinois, M.A. in Mathematics Education from Teachers College at Columbia University, M.S. and Ph.D. in Learning Sciences from the University of Wisconsin, and postdoctoral fellowship at Northwestern University. Golnaz is a former middle school computer science and high school mathematics teacher. Her research focuses on designing inclusive STEM digital learning environments and measuring connected thinking.
In the last decade, researchers in a variety of domains have used Quantitative Ethnography (QE) in their work. With an initial following in learning sciences and learning analytics, QE is now being used by researchers in fields such as political science, neuroscience, computer human interaction, and anthropology. The main reason for this wide-spread application is because QE leverages the power of human interpretation and computational efficiency such that researchers can create “thick descriptions” of large datasets. In this keynote, I will review how researchers across domains are using QE in different ways, focusing on how QE can be an inclusive research method. After reviewing the current state of the field, I will propose future directions for the QE community.
Morten Misfeldt is a Professor at University of Copenhagen in the Center for Digital Education. He obtained his MS degree in mathematics from the University of Copenhagen. He was a visiting scholar at the MIT Media Lab, and in 2006 he got his Ph.D from Learning Lab Denmark, the Danish School of Education. His research concentrates on digitalization of the teaching and learning of mathematics. This includes how new media changes mathematical work and learning.
Karin Frey is a Research Associate Professor of Educational Psychology at the University of Washington in the College of Education. Her research focuses on contextual influences on revenge, helping behavior, self-identity and resilience. She earned her Ph.D in developmental psychology at the University of Washington and Post-doc in social psychology at Princeton University as a NIH fellowship. She is also the PI of the Sociomoral Action and Identity Lab (SAIL) that examines the influences of friends, cultural norms, and perceived peer norms in a sample of Indigenous-, Mexican-, European-, and African-Americans.
Jun is a professor at the Graduate School of Integrated Science and Technology at Shizuoka University, Japan. His research areas include the Learning Sciences, the design of learning environments, social network analysis of cognitive intelligence, regulation of collaboration, and design-based research on elementary science curriculum. In addition to these areas of research, he serves on the editorial boards of The Journal of the Learning Sciences and the International Journal of Computer-Supported Collaborative Learning. He earned his Ph.D. at the University of Toronto under the supervision of Professors Carl Bereiter and Marlene Scardamalia.
Adam Lefstein is Associate Professor in Education at the Ben-Gurion University of the Negev in Israel, where he conducts research and teaches about pedagogy, classroom interaction, teacher learning and educational change. He’s particularly interested in the intersection between research and professional practice, and how to conduct research that is meaningful, rigorous and helpful for educators. Among other activities he directs the Laboratory for the Study of Pedagogy, an interdisciplinary research group that is committed to rigorous investigation of Israeli schooling, pedagogy and educational policy; the development of innovative research tools for the study of these phenomena; and processes of knowledge sharing with education practitioners, policy-makers and the public.
David Williamson Shaffer is the Vilas Distinguished Achievement Professor of Learning Sciences at the University of Wisconsin in the Department of Educational Psychology. He is also the Obel Professor of Learning Analytics at Aalborg University in Copenhagen, and a Data Philosopher at the Wisconsin Center for Education Research. Professor Shaffer studies how to develop and assess complex and collaborative thinking skills. He is the author of How Computer Games Help Children Learn and Quantitative Ethnography.