Live Sessions & Guest Speakers
Live Sessions & Guest Speakers
Each week, we will be hosting several guest presenters on topics relevant to learning analytics. We've tried to arrange speakers by relevance to weekly themes, but in some cases, schedules did not allow this match. As a result, some topics bleed into other weeks. We think that's a good thing - knowledge development isn't linear. The speaker schedule for LAK13 will be posted on Feb 15.
All live sessions will be held here in Collaborate Links to an external site.
Marie Bienkowski April 4, 1 pm EST (what time for me?)
The Learning Registry: Applying Social Metadata for Learning Resource Recommendations
The proliferation of online teaching, learning, and assessment resources is hampering efforts to make finding relevant resources easy. Metadata, while valuable for curating digital collections, is difficult to keep current or, in some cases, to obtain in the first place. Social metadata, paradata, usage data, and contextualized attention metadata all refer to data about doing with digital resources that can be harnessed for recommendations. To centralize this data for aggregation and amplification, the Learning Registry, a store and forward, distributed, de-centralized network of nodes was created. The Learning Registry makes it possible for disparate sources to publish learning resource social/attention metadata—data about users of and activity around resources. We describe our experimentation with social metadata, including that which describes alignment of learning resources to U.S. teaching standards, as a means to generate relationships among resources and people, and how it can be used for recommendations.
Biography
Marie Bienkowski is the Deputy Director of the Center for Technology in Learning, at the nonprofit research organization, SRI International. She works with educational researchers to develop and evaluate technology in K-12 education, and to contribute research data to education policy discussions. Many of her projects involve efforts to interest underrepresented groups in science, technology, engineering, and mathematics careers with a focus on computer science. She leads software projects in the areas of learning resource analytics and intelligent information management. Dr. Bienkowski co-authored the report “Enhancing Teaching and Learning through Educational Data Mining and Learning Analytics” for the U.S. Department of Education (released in October 2012). She is the co-PI of an NSF-funded grant on assessing computational thinking for high school students and is leading SRI’s contributions to the core infrastructure of the open-source learning-resource analytics project called the Learning Registry. She received her Ph.D. in computer science from the University of Connecticut.
Previous Sessions
Two orientation sessions are planned for week 1:
Tues, Feb 12, 11:00 am Mountain (See Time Zone Conversions
Links to an external site.)
Tues, Feb 12, 7 pm Mountain (See Time Zone Conversions)
Links to an external site.
Presentation: An overview of learning analytics: making sense of, and finding your way through, an emerging discipline
Presenter: George Siemens
Date: Thurs, Feb 14, 2 pm Mountain (See Time Zone Conversions
Links to an external site.)
John Whitmer: Feb 19, 2pm EST (what time for me?)
Using Learner Analytics to Understand Student Achievement in a Large Enrollment Hybrid Course
Using Learner Analytics to Understand Student Achievement in a Large Enrollment Hybrid Course This case study will discuss a learning analytics research study (n=377) on a redesigned hybrid large enrollment undergraduate course. The study explored the relationship between Learning Management System (LMS) use, student background characteristics and course achievement. Data analysis tools including Tableau, Stata, and Excel were used to conduct the analysis. Separate LMS use variables were found to explain over four times the variation in final grade compared to student characteristic variables. For at-risk students, LMS use had a 25% smaller effect on final grade. These results suggest that the LMS is a potentially valuable resource to carry out instructional reforms. Further, data from the LMS can be used as a meaningful indicator of student educational effort.
Biography
John has managed and evaluated large-scale academic technology projects for the past decade. He currently serves as an Associate Director in the Academic Technology Services division of the California State University Office of the Chancellor. In this capacity, John works on several projects related to Learning Analytics and the use of data to help understand the impact of technology on teaching and learning. In addition, he develops other innovative technology services, negotiates pricing agreements, and helps communicate findings across campuses. John previously directed academic technology initiatives for an NSF-funded 15 campus Earthquake Engineering consortium and for a system-wide project in the California Community College system. John holds a Doctorate in Educational Leadership from UC Davis and a Master’s Degree in Sociocultural Anthropology from UC Davis.
John Fritz: Feb 20, 3pm EST (what time for me?)
Using Learning Analytics to Scale Peer Feedback as AN Intervention Strategy
UMBC has been exploring how to help students take more responsibility for their learning. To help, we created a "Check My Activity" (CMA) dashboard they all see when logging into our Blackboard LMS. Why might they want to do this? Since 2007, students earning a D or F have been using our LMS about 40 percent less than students earning a C or higher. Does the pattern hold true throughout the semester? If so, what would happen if all students could see this sooner? And how might prior student LMS activity inform instructors' future course design? We are not suggesting the LMS makes good students, but we are interested in how good students use the LMS and what difference this makes when anonymously shared with all users of the system. Note: For a brief (5 min) screencast "demo" of the CMA, and a sneak peek at where we're going, visit http://youtu.be/iLifdZ5sRMc
Biography
John Fritz is Assistant Vice President for Instructional Technology & New Media in UMBC's Division of Information Technology. He is responsible for UMBC's focused efforts in teaching, learning and technology and was the primary information architect and content developer of UMBC's web site. Before joining DoIT in 1999, John served as UMBC's director of News & Online Information for four years, and has more than 10 years experience as a public information officer, writer and editor in three University of Maryland campuses. For seven years, he taught a class in "web content development" for UMBC's English and Information Systems Departments, but is now back in school working on a Ph.D in Language, Literacy and Culture at UMBC. John holds an M.A. in English (with an emphasis in rhetoric and composition) from the University of Maryland, College Park (1989), a B.A. in English and religion from Columbia Union College in Takoma Park, Maryland (1985), and certificates in New Media Publishing from the University of Baltimore (2002) and Instructional Systems Design from UMBC (2009).
Chuck Severance: Feb 25, 11 am EST (what time for me?)
IMS: Learning Tools Interoperability
Ryan S.J.d. Baker: Feb 26, 1 pm EST (what time for me?)
Educational Data Mining: A Methodological Review
Abstract: In this session, I will discuss the methods of educational data mining, a community closely related to learning analytics. I will discuss some of the commonalities and differences between the two research areas, and some of the key uses of educational data mining methods.
Bio: Ryan Shaun Joazeiro de Baker is the Julius and Rosa Sachs Distinguished Lecturer at Columbia University Teachers College, in 2012-2013. He earned his Ph.D. in Human-Computer Interaction from Carnegie Mellon University, and was a post-doctoral fellow in the Learning Sciences at the University of Nottingham. He earned his Bachelor’s Degree (Sc.B.) in Computer Science from Brown University. Dr. Baker has been Assistant Professor of Psychology and the Learning Sciences at Worcester Polytechnic Institute. He previously served as the first Technical Director of the Pittsburgh Science of Learning Center DataShop, the largest public repository for data on the interaction between learners and educational software. He is currently serving as the founding President of the International Educational Data Mining Society, and as Associate Editor of the Journal of Educational Data Mining.
Live session on epistemology (with guests): March 19, 8.30pm GMT (what time for me? Links to an external site.)
Simon Knight & Simon Buckingham Shum
Introduction to epistemology, pedagogy, assessment and learning analytics
This week we want to highlight some of the implications of analytics for learning, assessment, and how we understand ‘knowledge’ – what does the content we assess, and the way we assess imply about how we understand learning and knowledge? We’ll introduce these issues and discuss the activities for the week, described https://learn.canvas.net/courses/33/wiki/week-6-epistemology-and-pedagogy
Biographies
Simon Knight is a PhD student at The Open University’s Knowledge Media Institute
Links to an external site., researching learning analytics for analysing epistemic moves and collaborative dialogue in collaborative information retrieval tasks. Prior to starting his PhD he gained an MPhil in Educational Research Methods from Cambridge, and a Ma in Philosophy of Education from the Institute of Education. He is also a qualified teacher, and taught a-level philosophy and psychology. The topics this week are focussed on "Epistemology, Pedagogy, Assessment and Learning Analytics" which he will be presenting at LAK13 in Leuven as well as a DCLA paper "Discourse, Computation and Context – Sociocultural DCLA Revisited"
Simon Buckingham Shum is Professor of Learning Informatics at The Open University’s Knowledge Media Institute
Links to an external site., an 80-strong lab at the convergence of learning sciences, web media, collaboration tools and the social/semantic web. He researches, teaches and consults on learning analytics, social learning media, collective intelligence and dialogue/argument visualization. In KMi he leads the Hypermedia Discourse
Links to an external site. group, and serves as Associate Director (Technology) interfacing KMi’s R&D with the OU’s strategic development. He is also a Visiting Fellow at University of Bristol Graduate School of Education
Links to an external site.. Simon was Programme Co-Chair for the 2012 Learning Analytics conference
Links to an external site., a co-founder of the new Society for Learning Analytics Research
Links to an external site., and is a regular invited speaker on the topic. He serves on the Advisory Groups for a variety of analytics initiatives in education and enterprise. His particular interests are in what learning analytics may be blind to, analytics for informal/social learning, and whether analytics can help build the learning dispositions and capacities needed to cope with complexity and uncertainty — the only things we can be sure the future holds.
George Siemens
Connective Knowledge and Analytics
Biography
George Siemens, Founder and President of Complexive Systems Inc., a research lab assisting organizations to develop integrated learning structures for global strategy execution. In 2006 he authored a book - Knowing Knowledge
Links to an external site. (.pdf version available here
Links to an external site.)- an exploration of how the context and characteristics of knowledge have changed, and what it means to organizations today. In 2009, he published the Handbook of Emerging Technologies for Learning
Links to an external site. (.pdf version available here
Links to an external site.) with Peter Tittenberger.
George is currently affiliated with the Technology Enhanced Knowledge Research Institute Links to an external site. (TEKRI) at Athabasca University Links to an external site.. His role as a social media strategist involves planning, researching, and implementing social networked technologies, with focus on systemic impact and institutional change.
Prior to TEKRI, he was the Associate Director, Research and Development with the Learning Technologies Centre Links to an external site. at University of Manitoba Links to an external site..
David Williamson Shaffer
Epistemic Games for 21st Century Assessment
In this talk, Dr. Shaffer presents an overview of Epistemic Frame Theory, which he describes as the structure of connections among values, knowledge, skills, epistemology, and identity that people have as part of a particular community of practice. An epistemic frame is thus the organizational rules and premises, partly existing in the minds of participants and partly in the structure of the activity itself, that shape the perceptions of those involved: a set of norms and practices through which experiences are interpreted that is simultaneously individual, social, and measurable. This talk will look at how epistemic frame theory can thus operationalize learning through enculturation.
Biography
David Williamson Shaffer is a professor at the University of Wisconsin-Madison in the departments of Educational Psychology and Curriculum and Instruction, 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 studies how new technologies change the way people think and learn. His particular area of interest is in the development of epistemic games: computer and video games in which players become professionals to develop innovative and creative ways of thinking.
Stephanie Teasley (March 25, 1:30 pm EST) (What time for me?) Links to an external site.
Using Learning Analytics to Support Academic Advising for At-Risk Undergraduates
Recent efforts utilizing learning analytics have been limited in scope (e.g., well defined problem spaces) and in scale (targeting individual courses, using proprietary software). We describe an Early Warning System in use in the “STEM Academies", academic support programs aimed at increasing success and retention by undergraduate students identified as at-risk. This system, the Student Explorer, leverages data from an Open Source Learning Management System to provide academic advisors with real-time feedback about student performance and engagement. Specifically, we use LMS data to track student performance across courses and provide a timely way to intervene with those students struggling academically.
Biography
Stephanie Teasley is a Research Professor in the School of Information and Director of the USE Lab at the University of Michigan. She received her PhD in cognitive psychology from the University of Pittsburgh in 1992. Throughout her career, her work has focused on issues of collaboration and learning, looking specifically at how sociotechnical systems can be used to support effective collaborative processes and successful outcomes. She is the co-editor of the volume, Perspectives on Socially Shared Cognition, and co-author of several highly cited book chapters on collaborative learning. Her work has also appeared in numerous scholarly journals including Science, Developmental Psychology, the International Journal of Computer Supported Collaborative Learning, and Computers and Education. Dr. Teasley’s research has been funded by the US National Science Foundation and the National Institutes of Health. She is on the Executive Committee of the Society for Learning Analytics Research (SoLAR).
Abelardo Pardo: March 28, 9 pm GMT (what time for me?) Links to an external site.
Practical privacy issues around Learning Analytics
The controversy around privacy and security in ICT seems to be a never-ending source of newspaper headlines. Cases of security and privacy breaches are interspersed with an equal number of announcements of new legislative measures or amendments. Learning analytics is certainly not the first technological area to deal with these issues, but more often than not, the debate on privacy tends to prevent the design of practical solutions. Far from trying to settle the main controversy around privacy, in this talk we will try to identify the major areas in which privacy concerns can be divided and provide some examples of practical solutions.
Biography
Abelardo Pardo is a Lecturer at the School of Electrical and Information Engineering, University of Sydney. He has a PhD in Computer Science by the University of Colorado at Boulder applied to formal verification of digital circuits. His research interest is in the application of software engineering techniques to improve all aspects of the well-being of humans and communities. He has experience in the use of mobile devices in areas such as behavioral analytics, social networks, computer supported collaboration, personalization, and technology enhanced learning, which he deploys in his teaching activities. He has participated in national and international projects funded by NSF (USA) and the European Union. Abelardo is author of more than 100 research publications in prestigious conferences and journals, member of the steering committee of the Society for Learning Analytics Research (www.solaresearch.org), and member of the editorial board of the Journal of Social Media and Interactive Learning Environments and the Journal for Learning Analytics.
Stefan Dietze. April 2, 2013: 4:30 GMT (see here for time zone conversions Links to an external site.)
Linked Data as a new environment for Learning Analytics and education
The Semantic Web has been for a long time considered a pure research area, concerned with the way to formally express and share knowledge in reusable forms. With the emergence of Linked Data, it is now considered from a more practical perspective, with many concrete applications in many different domains, as well as new technical issues related to the scale, distribution and heterogeneity of the data now available online. This new approach to the dissemination and reuse of information online has naturally been picked up in a variety of learning scenarios, with educational institutions, open educational repositories and many others starting publishing Linked Data about relevant entities. In this presentation, we will discuss the basic principles on which Linked Data rely, how these principles are applied to education and what are the benefits. We will especially concentrate on the way the availability of such large scale, distributed data sources can be exploited in learning analytics scenario, both through a use of Linked Data technologies for integrating data as input of the process, and as a way to share and enrich the results of data analytics based on information available online. We will also show, at a broader level, how this idea of sharing and collecting collective information about a large variety of education-related information sources opens the way to new scenarios in learning analytics, and more generally, supports the current evolution of the education domain towards a global, open environment online.
Biography
Stefan Dietze currently is research group leader at the L3S Research Center of the Leibniz University Hannover (Germany). His main research interests are in Semantic Web and Linked Data technologies and their application to Web data integration problems in domains such as education or Web archiving. He holds a Ph.D. (Dr. rer. nat.) in Applied Computer Science from Potsdam University and previously held research positions at the Knowledge Media Institute (KMI) of The Open University (UK) and the Fraunhofer Institute for Software and Systems Engineering (Berlin, Germany). Stefan currently is coordinator of the EU-funded project LinkedUp (http://linkedup-project.eu) and he has been involved in leading roles in numerous EU R&D projects, such as LUISA, NoTube, ARCOMEM or mEducator. Furthermore, he is co-founder of the Linked Learning workshop series and of the community platform http://linkededucation.org. Stefan’s work has been published throughout major conferences and journals in areas such as Semantic Web, Linked Data, Services-oriented Systems and Technology-enhanced Learning and he is reviewer, organiser and committee member for numerous scientific events and publications.