Education Futures in collaboration with DER will host the workshop on epistemic network analysis for quantitative ethnography. The ability to teach and assess the development of complex thinking skills is crucial for 21st century educational research. In the age of educational games and the Big Data they generate, we have more information than ever about what students are doing and how they are thinking. But as the sheer volume of data available can overwhelm traditional qualitative and quantitative research methods. Quantitative Ethnography is a set of research methods that weave the study of culture together with statistical tools to understand learning — a way to go beyond looking for arbitrary patterns in mountains of data that games and simulations generate and begin telling textured stories at scale. The foundational method under the umbrella of Quantitative Ethnography is Epistemic Network Analysis, a network modeling technique for modeling learning in Big Datasets.1pm – 4pm, 2 Aug 2018
Learning + Teaching Building
19 Ancora Imparo Way, Room 2.43
No registration needed!
Vitomir Kovanović is a Research Fellow in the School of Education at University of South Australia and a Data Scientist in the Teaching Innovation Unit at the University of South Australia. 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. He 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. He serves as an executive member of the Society for Learning Analytics Research (SoLAR) which is the leading research society focused on promotion and development of the field of Learning Analytics. He received his Ph.D. in Informatics from the University of Edinburgh in 2017.
Srećko Joksimović is a Research Fellow in the School of Education at University of South Australia and a Data Scientist in the Teaching Innovation Unit at the University of South Australia. His research interests center on the analysis of teaching and learning in networked learning environments. He is particularly interested in developing theory-driven, data-informed analytics models for assessing the quality of learning in computer-mediated context, generating insights into factors that promote effective collaborative learning, and informing the design of digital environments in which collaborative learning occur. He is an executive committee member and the Chair of the Website Portfolio of the Society for Learning Analytics Research (SoLAR). He received his Ph.D. in Learning Analytics from the Moray House School of Education at the University of Edinburgh in 2017.
