Our first brown-bag seminar of the semester will take place next Wednesday (28 January 2015) from 12:00 PM – 1:00 PM in Woodruff Library Rm 208E. Please RSVP by email to Timothy Harfield (tharfie [at] emory [dot] edu by Friday, 23 September 2015 so that we can ensure that our space can comfortably accommodate all who plan to attend.
Our meeting will be facilitated by Dr. Ben Sayeski (Managing Partner, Education Strategy Consulting), who will lead a discussion about the ways in which he has leveraged big data in K-12, and opportunities for similar work in Higher Education. The full abstract for this seminar is as follows:
K-12 Lessons and Higher Education Opportunity
This presentation and discussion will focus on the evolution of big data analyses in K-12 education and the opportunities for higher education. The discussion will be grounded in research from the Los Angeles Unified School District, publicly available K-12 data from the state of Georgia, and publicly available data from the Integrated Postsecondary Education Data System. All data will be presented within a visualization tool in order to address specific questions from attendees and create questions for future consumption. Particular attention will be paid to the visualizations from a variety of stakeholder perspectives including policy, professional, students, and parents.
This semester, the general goal of our brown bag series is to stimulate our data-imaginations in order to gain a richer idea of how various types of educational data can be put to use. In addition to Ben Sayeski, our series will also include seminars led by Nancy Bliwise (Emory University), Kimberly Arnold (University of Wisconsin-Madison), and Mike Sharkey (Blue Canary). Our season will conclude with a session led by Timothy Harfield, which will provide an overview of the learning analytics work being done at Emory, a description of how far we’ve come, and an opportunity to reflect upon the future of learning analytics at Emory University. For complete details, our full seminar schedule is available to view HERE.
All this amounts to what is certain to be an engaging and fruitful set of events.
Analytics for Learning at Emory invites applications to participate in an intensive, day-long symposium on the use of data to inform decisions about learning environments and instructional design.
The Southeast Educational Data Symposium (SEEDS) will bring together administrators, researchers, and instructors to share how they are making use of educational data to foster student success, and to generate opportunities for ongoing collaboration in the Southeast region. The day’s schedule will include a morning keynote, delivered by Carolyn Rosé (Carnegie Mellon University), followed by four panel discussions. The all-day event will be held on Friday, February 20, 2015 from 9:00 AM to 4:30 PM EST at the Emory Conference Center in Atlanta, GA.
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October 15, 2014 | 12:00pm – 1:30pm
Speaker: Charles Dziuban (University of Central Florida)
Chuck will present outcomes from twenty years of research on the concept of learning analytics through an effective teaching and learning perspective. He will compare student success rates in varying course modalities in addition to preference for instructional formats. He will show the characteristics of excellent instructors from the student point of view using concepts such as the Anna Karenina Phenomenon. Finally he will present examples of how individual faculty members at the University of Central Florida are undertaking an analytic approach to improving their courses with the scholarship of teaching and learning.
Charles Dziuban is Director of the Research Initiative for Teaching Effectiveness at the University of Central Florida (UCF) where has been a faculty member since 1970 teaching research design and statistics. He received his Ph.D. from the University of Wisconsin. Since 1996, he has directed the impact evaluation of UCF’s distributed learning initiative examining student and faculty outcomes as well as gauging the impact of online, blended and lecture capture courses on the university. Chuck has published in numerous journals including Multivariate Behavioral Research, The Psychological Bulletin, Educational and Psychological Measurement, the American Education Research Journal, the Phi Delta Kappan, the Internet in Higher Education, the Journal of Asynchronous Learning Networks, and the Sloan-C View. His methods for determining psychometric adequacy have been featured in both the SPSS and the SAS packages. He has received funding from several government and industrial agencies including the Ford Foundation, Centers for Disease Control, National Science Foundation and the Alfred P. Sloan Foundation. In 2000, Chuck was named UCF’s first ever Pegasus Professor for extraordinary research, teaching, and service and in 2005 received the honor of Professor Emeritus. In 2005, he received the Sloan Consortium award for Most Outstanding Achievement in Online Learning by an Individual. In 2007 he was appointed to the National Information and Communication Technology (ICT) Literacy Policy Council. In 2010, Chuck was named an inaugural Sloan-C Fellow. In 2012 the University of Central Florida initiated the Chuck D. Dziuban Award for Excellence in Online Teaching for UCF faculty members in honor of Chuck’s impact on the field of online teaching.
Chuck has co-authored, co-edited, or contributed to numerous books and chapters on blended and online learning including Handbook of Blended Learning Environments, Educating the Net Generation, and Blended Learning: Research Perspectives. He has given invited presentations on how modern technologies impact learning at more than 80 colleges and universities worldwide. His new book Blended Learning Research Perspectives II, co-edited with Anthony Picciano and Charles Graham was released in the fall of 2013.
November 17, 2014 | 12:00pm – 1:30pm
Speaker: Alyssa Wise (Simon Fraser University)
Learning analytics are data traces of student activity that can be used to better understand and support learning processes and outcomes. Over the last few years there have been remarkable advances in our ability to calculate and display useful information about what students are doing. Now, we face the important challenge of how to mobilize this intelligence to have a meaningful impact on university teaching and learning. To do so, we need to consider and design for the ways in which learning analytics can become a part of (and change) the activity patterns of instructors and students. Working within the scope of the university course, I describe ways to integrate learning analytics into teaching and learning processes by using data-informed reflection to probe the connections (and disconnects) between instructors’ and designers’ pedagogical intents and students’ actual activity patterns. Particular attention will be paid to roles for students in the process, and the use of different reference frames for data interpretation. To ground the discussion, work from the E-Listening Project at Simon Fraser University will be presented as an initial example of a learning analytics application developed and implemented in a university course using such an integrated approach.
Alyssa Friend Wise is an Associate Professor with the Educational Technology & Learning Design Program at Simon Fraser University in Canada. Her research examines how people interact with each other through technologies and how such interactions can contribute to learning. Recent work includes the E-Listening Project (research into how participants attends to others’ comments in online discussions), the development of Youtopia (a collaborative table-top game about sustainability issues), and the creation of a model for Learning Analytics Interventions (a pedagogical approach to help students work with data collected on their learning as part of the educational process).
February 9, 2014 | 12:00pm – 1:30pm
Speaker: Ryan Baker
Towards Long-Term and Actionable Prediction of Student Outcomes using Automated Detectors of Engagement and Affect
In recent years, researchers have been able to model an increasing range of aspects of student interaction with online learning environments, including affect, meta-cognition, robust learning, and engagement.
In this talk, I discuss how automated detectors of engagement and learning can be used in prediction of long-term student outcomes, illustrating this with examples of how affect, engagement, and learning during middle school use of educational software can support prediction of student long-term success, including end-of-year learning, decisions about whether to attend college, and even what major a student chooses. These predictive models can in turn support inference about what factors make a specific student at-risk for poorer learning or lower long-term engagement in learning.
Ryan Baker is Associate Professor of Cognitive Studies at Teachers College, Columbia University. He earned his Ph.D. in Human-Computer Interaction from Carnegie Mellon University. Dr. Baker was previously Assistant Professor of Psychology and the Learning Sciences at Worcester Polytechnic Institute, and 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. His research combines educational data mining and quantitative field observation methods to better understand how students respond to educational software, and how these responses impact their learning. He studies these issues within intelligent tutors, simulations, multi-user virtual environments, and educational games.