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Program

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February 27, 2011

FINAL CONFERENCE PROGRAM is available here (.pdf)


Keynote Speakers:

Tony Hirst

Pragmatic analytics: insight, representation and structure

In the days of the face to face lecture, if no-one turned up the lecturer might might be expected to notice. Of those who did, some might be expected to sit together in the same small group, week on week. With an increasing number of formal education courses at the Higher Education level making more and more use of online learning environments, does the same hold true? How good a feeling does the instructor have about the social dynamics of their online cohort, or the way in which they are engaging with the course material as it's delivered to them in bits?


Website analytics and social network analysis provide two ways in which we can start to get a feel for how our students are engaging with course resources, and each other, in an online environment. But what sort of data is available, in principle, if not in fact, and in practical terms, if not the ideal case? Once we have the data, what sort of stories can it tell us? And how might we set about finding those stories?


This talk will explore some practical - and pragmatic - ways of obtaining and analysing data, particularly in a visual way, as a starting point for understanding how our our online course environments are used. It will also introduce some simple models that can help us tease out the different stories that may be interwoven through any particular data set, and see how we may be able to use data as a driver of adaptive learning environments.

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Xavier Ochoa

Learnometrics: Metrics for Learning (Objects)
The field of Technology Enhanced Learning (TEL) in general, has the potential to solve one of the most important challenges of our time: enable everyone to learn anything, anytime, anywhere. However, if we look back at more than 50 years of research in TEL, it is not clear where we are in terms of reaching our goal and wether we are, indeed, moving forward. The pace at which technology and new ideas evolve have created a rapid, even exponential, rate of change. This rapid change, together with the natural difficulty to measure the impact of technology in something as complex as learning, have lead to a field with abundance of new, good ideas and scarcity of evaluation studies. This lack of evaluation has resulted into the duplication of efforts and a sense of no “ground truth” or “basic theory” of TEL. This talk is an attempt to stop, look back and measure, if not the impact, at least the status of a small fraction of TEL, Learning Object Technologies, in the real world. The measured apparent inexistence of the reuse paradox, the two phase linear growth of repositories or the ineffective metadata quality assessment of humans are clear reminders that even bright theoretical discussions do not compensate the lack of experimentation and measurement. Both theoretical and empirical studies should go hand in hand in order to advance the status of the field. This talk is an invitation to other researchers in the field to apply Informetric techniques to measure, understand and apply in their tools the vast amount of information generated by the usage of Technology Enhanced Learning systems. This new field of research, that we can call Learnometrics, Educational Data Mining or Learning Analytics, promises to provide deep insight into how instructors and learners are making use of the technology and how we can improve that technology. Only this kind of understanding could help us to be sure that we are moving forward in our quest to provide great learning experiences for anyone, anytime, anyplace.
Bio:
Xavier Ochoa is a Principal Professor at the Faculty of Electrical and Computer Engineering at Escuela Superior Politécnica del Litoral (ESPOL) in Guayaquil Ecuador. Currently, he coordinates the research group on Teaching and Learning Technologies at the Information Technology Center (CTI) at ESPOL. He is also involved in the coordination of the Latin American Community on Learning Objects (LACLO), the ARIADNE Foundation, the Ibero-American Society for the Advancement of Learning Technologies (SIATE) and several regional projects. His main research interests revolve around Informetrics, specially related to the field of Learning (Learnometrics) and Science (Scientometrics). More information at
http://ariadne.cti.espol.edu.ec/xavier.

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Erik Duval

Attention please!
Attention metadata capture how people interact with resources and with one another. We can make use of the patterns in attention metadata to help learners and teachers cope with the abundance of learning resources through recommendation techniques. By visualizing the patterns, we can make teachers and learners more aware of what they do. An important concern is openness, so that we can detect patterns across the boundaries of technical and organizational systems and ensure data portability that prevents system lock-in.

bio:
Erik Duval is a professor of computer science at the Katholieke Universiteit Leuven, Belgium. His research focuses on management of and access to data and content. Typical applications come from the fields of technology- enhanced learning, music information retrieval, and “Science2.0.”
More specifically, his interests include metadata, reusable content, global infrastructures based on open standards, and mass personalization (“The Snowflake Effect”).  Prof. Duval serves on the ARIADNE Foundation, chairs the IEEE LTSC working group on Learning Object Metadata, is a fellow of the AACE, and a member of the ACM and the IEEE Computer Society. He cofounded two spin-offs that apply research results for access to music and scientific output.
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Caroline Haythornthwaite

Learning networks, crowds and communities
Who we learn from, where and when is dramatically affected by the reach of the Internet. From learning for formal education to learning for pleasure, we now look to the web early and often for our data and knowledge needs, but also for places and spaces where we can collaborate, contribute to, and create learning and knowledge communities. This talk explores the emerging landscape of online learning with attention to the structure and dynamics of online learning networks, crowds and communities. With reference to social network informed studies of learning, the talk explores the different ways learning emerges from social interaction, how structures and motivators differ across ‘lightweight’ (crowd-based) and ‘heavyweight’ (community-based) peer productions, and where an analytics perspective can be used to follow, support or enhance learning outcomes.

Bio:
Caroline Haythornthwaite is Director, School of Library, Archival and Information Studies, University of British Columbia. She joined UBC in 2010 after 14 years at the University of Illinois at Urbana-Champaign, where she was Professor in the Graduate School of Library and Information Science. In 2009-10, she was Leverhulme Trust Visiting Professor at the Institute of Education, University of London presenting and writing on learning networks; and in summer 2009 she was a visiting researcher lecturing on distributed knowledge, social networks, and e-learning at the Brazilian Institute for Information in Science and Technology (IBICT), Rio de Janeiro, Brazil. She has an international reputation in research on information and knowledge sharing through social networks, and the impact of computer media and the Internet on work, learning and social interaction. Her research includes empirical and theoretical work on social networks of work and media use, the development and nature of community online, distributed knowledge processes, the nature and constraints of interdisciplinary collaboration, motivations for participation in crowds and communities, and the development of automated processes for analysis of online learning activity. Current work aims to expand the understanding of the term ‘e-learning’ to include theory and practice of e-learning as: a socio-technical implementation for education; an emerging practice of informal learning on and via the Internet; and as a research and development initiative akin to e-research. Major publications include The Internet in Everyday Life (2002, with Barry Wellman); Learning, Culture and Community in Online Education (2004, with Michelle M. Kazmer), the Handbook of E-learning Research (2007, with Richard Andrews), and E-learning Research and Practice (2011, with Richard Andrews).

Accepted Papers
Dataset-driven Research for Improving Recommender Systems for Learning (Katrien Verbert and Erik Duval)
Learning Analytics as Interpretive Practice: Applying Westerman to Educational Intervention (Michael Atkisson and David Wiley)
Variable Construction for Predictive and Causal Modeling of Online Education Data (Stephen Fancsali)
A Unified Framework for Multi-Level Analysis of Distributed Learning (Daniel Suthers and Devan Rosen)
Using learning analytics to assess students’ behavior in open‐ended programming tasks (Paulo Blikstein)
Evolving a learning analytics platform (Ari Bader-Natal and Thomas Lotze)
Usage Contexts for Object Similarity: Exploratory Investigations (Katja Niemann, Hans-Christian Schmitz, Maren Scheffel and Martin Wolpers)
iSpot Analysed: Participatory Learning and Reputation (Doug Clow and Elpida Makriyanni)
Discourse-Centric Learning Analytics (Anna De Liddo, Simon Buckingham Shum, Ivana Quinto, Michelle Bachler and Lorella Cannavacciuolo)
SNAPP: A Bird’s-Eye View of Temporal Participant Interactions (Aneesha Bakharia and Shane Dawson)
Towards Visual Analytics for Teachers' Dynamic Diagnostic Pedagogical Decision-Making (Ravi Vatrapu, Chris Teplovs and Nobuko Fujita)
Learning Analytics To Identify Exploratory Dialogue within Synchronous Text Chat (Rebecca Ferguson and Simon Buckingham Shum)
AAT – A Tool for Accessing and Analysing Students’ Behaviour Data in Learning Systems (Sabine Graf, Cindy Ives, Nazim Rahman and Arnold Ferri)
Redefining dropping out in online higher education: a case study from the UOC (Josep Grau and Julià Minguillón)
Learning at a Glance: a Blog Visualization System in a Japanese Context (Terumi Miyazoe)
The Value of Learning Analytics to Networked Learning on a Personal Learning Environment (Rita Kop, Helene Fournier and Hanan Sitlia)
The Who, What, When, Where, and Why of Lecture Capture (Christopher Brooks, Carrie Demmans Epp, Greg Logan and Jim Greer)