The focus of this workshop is on the potential benefits and challenges of using specific computational methods to analyze interactions in networked learning environments, particularly with respect to integrating multiple analytic approaches towards understanding learning at multiple levels of agency, from individual to collective. The workshop is designed for researchers interested in analytical studies of collaborative and networked learning in socio-technical networks, using data-intensive computational methods of analysis (including social-network analysis, log-file analysis, information extraction and data mining). The workshop may also be of interest to pedagogical professionals and educational decision makers who want to evaluate the potential of learning analytics techniques to better inform their decisions regarding learning in technology-rich environments.
This workshop continues the themes of “connecting levels” and
“multivocality” that have characterized two series of workshops at
several conferences (ARV, CSCL, ICLS, LAK). We have taken a
multi-disciplinary perspective on learning as involving the agency
of individuals, groups and communities, and sought to understand
learning across these levels by integrating multiple methods and
granularities of analysis (cf. [
The workshop for LAK 2014 focuses on specific computational
methods and their potential for analyzing interactions in
networked learning communities from different perspectives.
Social network analysis (SNA, cf. [
Although the workshop is focused on (new) computational
methods or new applications of such methods, we are also
interested in discussing computational approaches in a conceptual
and/or theoretical context. In this perspective, Suthers et al. [
How to detect emergent phenomena and patterns in traces of collective/collaborative learning activities by using a plurality of computational methods? How do we interconnect these methods? What practical techniques such as different types of triangulation or visualization can help to connect different levels and approaches of analysis? How can we integrate SNA with content analysis methods (including LDA, LSA, Network Text Analysis) and with the detection of interaction patterns? How can conceptually/theoretically grounded interpretation schemes for collaborative activities be adequately operationalized and automated? What are the prospects of technical integration of analysis tools through a kind of “open analysis workbench” (open architecture, GUI metaphors). The workshop includes a mixture of presentations, interactive demos, and group discussions. The following contributions will be presented in the workshop: Daniel Suthers and Nathan Dwyer: Multilevel Analysis of Uptake, Sessions, and Key Actors in a Socio-Technical Network Agathe Merceron: Connecting Analysis of Speech Acts and Performance Analysis - An Initial Study Hiroaki Ogata, Songran Liu and Kousuke Mouri: Ubiquitous Learning Analytics Using Learning Logs Hiroaki Ogata: Supporting Science Communication in a Museum using Ubiquitous Learning Logs Tilman Göhnert, Sabrina Ziebarth, Per Verheyen, and H. Ulrich Hoppe: Integration of a Flexible Analytics Workbench with a Learning Platform for Medical Specialty Training H. Ulrich Hoppe, Tilman Göhnert, Laura Steinert, and Christopher Charles: A Web-based Tool for Communication Flow Analysis of Online Chats Wanli Xing and Sean Goggins: Automated CSCL Group Assessment: Activity Theory based Clustering Method Cindy Hmelo-Silver, Carolyn Rosé, and Jeff Levy: Fostering a Learning Community in MOOCs
H. Ulrich Hoppe holds a full professorship for “Cooperative and Learning Support Systems” in the Department of Computer Science and Applied Cognitive Science at the University of Duisburg-Essen, Germany. With his research group COLLIDE, Ulrich Hoppe has been engaged in several European projects in the area of advanced computational technologies in education since 1998. Ulrich Hoppe has been program chair of AIED and CSCL 2003, ICCE 2007 and CRIWG 2012. His current research interests include: interactive and collaborative media for learning and knowledge construction; analysis, modelling, and intelligent support of interactive and collaborative learning processes; social network analysis and community support.
Daniel D. Suthers is Professor in the Department of Information and Computer Sciences at the University of Hawai`i at Manoa, where he directs the Laboratory for Interactive Learning Technologies. Dr. Suthers’ research is generally concerned with cognitive, social and computational perspectives on designing and evaluating software for learning, collaboration, and community. Dr. Suthers initiated and chaired a series of five workshops on Productive Multivocality in Analysis of Collaborative Learning, involving dozens of researchers in a long term collaboration leading to a book in press. Subsequently he led workshops on Connecting Levels of Analysis at the CSCL 2011 and 2013 and LAK 2012 conferences. He has also served as program chair for LAK, ICCE, and two CSCL conferences, and has had steering committee roles (e.g., workshop chair, interactive events chair) for numerous other conferences.
x Tilman Göhnert, University of Duisburg-Essen, Germany x Sean Goggins, Drexel University, USA x Vanda Luego, Université Joseph Fourier, France x Agathe Merceron, Beuth University of Applied Sciences,
Germany x Hiroaki Ogata, Kyushu University, Japan x John Stamper, Carnegie Mellon University, USA x Chris Teplovs, Problemshift Inc., Canada