dates de séjour
projet de recherche
The Development of Multimodal Epistemic Network Analysis
This project will develop a network modeling tool to assess complex thinking through gestures and shared diagrams captured in video recordings. In modern workplaces and learning environments, mastery of basic facts and skills are not an effective measure of expertise. Therefore assessments need to focus on performance in context rather than on tests of abstracted and isolated skills and knowledge. Complex thinking in a domain requires a shared base of knowledge and skills, but also values and epistemology: the understanding of how to make decisions and justify actions in the field. More important, complex thinking does not just mean having a set of knowledge, skills, values, and ways of making decisions. It means understanding how these different elements of problem solving are connected to one another: which values to consider before taking a certain action; what knowledge to gather before making a particular kind of decision. Complex thinking is thus means having an effective network of connections between the skills, knowledge, values, and ways of making decisions in a domain. Epistemic Network Analysis (ENA) is a tool that measures complex thinking by creating a quantitative model from data about how subjects work in complex domains. These models take data from novices and experts, and use automated coding algorithms and network representations to extract key dimensions of complex thinking that characterize problem solving in a domain. The result is a technique for quantifying and visualizing complex thinking in a domain, and the different ways that learners do (and do not) develop it. However, much of this work has focused on the analysis of digital log files. In contrast many workplaces and learning settings rely heavily on multimodal situational cues for communication of meaning, development of shared understanding, and generation of productive collaboration. Such cues include looks, gestures, movements, actions, objects, and aspects of the physical environment that are typically recorded in video. A team from l’Institut Français de l’Education (IFE) and Le Laboratoire des Interactions, Corpus, Apprentissage, Représentations (ICAR) at l’Ecole Normale Supérieur de Lyon, as well as Le Laboratoire Sciences pour la conception, l’optimisation et la production de Grenoble (G-SCOP) at l’Université de GrenobleMultimodal ENA (mENA) will combine ENA and multimodal analysis into a common analytic framework that can be used to assess complex thinking and learning in collaborative workplace and learning environments.
David Williamson Shaffer is a Professor at the University of Wisconsin-Madison in the Department of Educational Psychology and a Game Scientist at the Wisconsin Center for Education Research. Before coming to the University of Wisconsin, Dr. Shaffer taught grades 4-12 in the United States and abroad, including two years working with the Asian Development Bank and US Peace Corps in Nepal. His M.S. and Ph.D. are from the Media Laboratory at the Massachusetts Institute of Technology, and he taught in the Technology and Education Program at the Harvard Graduate School of Education. Dr. Shaffer was a 2008-2009 European Union Marie Curie Fellow. He studies how new technologies change the way people think and learn, and his most recent book is How Computer Games Help Children Learn.