Winter 2014 Issue Available
Special Issue on Big Data & Learning Analytics |
The pieces in this Special Issue on Big Data & Learning Analytics have been arranged to provide a natural progression on the topic for the reader. The volume opens with an article by Candace Thille et al. that provides a definition of big data and examines how assessment processes with large-scale data will be different from those without it. Emphasizing a “wicked” problem in a complex system, Leah Macfadyen, Shane Dawson, Abelardo Pardo & Dragan Gašević offer a policy framework for navigating the tension between assessment-for-accountability and assessment-for-learning. Matters pertaining to various analytics are then given attention beginning with Una-May O’Reilly & Kalyan Veeramachaneni who describe an agenda for developing technology that enables MOOC analytics. Ryan Baker & Albert Corbett then consider how an emphasis on robust learning might advance the focus of assessments from single to multiple domains. Following this, Maarten de Laat & Fleur Prinsen introduce social learning analytics as an instrument in formative assessment practices. The final two articles offer innovative systems presently being used in organizations to strengthen student success through persistence and retention. In the first, Tristan Denley highlights how closing the information gap impacts the educational achievement gap for low income and minority students. Mark Milliron, Laura Malcolm & David Kil use insight and action analytics to produce predictive flow models of student progression and completion across three diverse organizations.
Book reviews for this volume were strategically chosen to provide readers with a sample of present works on big data. Aiden & Michel’s accessible work based on the Google Ngram Viewer, Uncharted: Big data as a lens on human culture is reviewed by Carolyn Penstein Rose. Fabio Rojas then engages Lane’s Building a Smarter University: Big data, innovation, and analytics, suggesting this may be an important volume for university administrators. Finally, drawing parallels from the K-12 sector, Karly Sarita Ford reviews Piety’s book Assessing the Educational Data Movement. The end of the issue asks readers to give consideration to the myriad subjects of big data. Here, Mitchell Stevens poignantly ask us to consider the legal, political and ethical questions of big data collection. He highlights the heroic efforts of the scholars and scientists at the Asilomar Convention, which yielded six principles to inform the navigation of this uncertain terrain.
Individual articles may be accessed via the links below or through the RPA archives:
The Future of Data-Enriched Assessment
By Candace Thille, Emily Schneider, René F. Kizilcec, Christopher Piech, Sherif A. Halawa, & Daniel K. Greene (Stanford University)
Big Data in Complex Educational Systems: The Learning Analytics Imperative and the Policy Challenge
By Leah P. Macfadyen (University of British Columbia), Shane Dawson (University of South Australia), Abelardo Pardo (The University of Sydney), & Dragan Gašević (Athabasca University)
Technology for Mining the Big Data of MOOCs
By Una-May O’Reilly & Kalyan Veeramachaneni (Massachusetts Institute of Technology)
Assessment of Robust Learning with Educational Data Mining
By Ryan S. Baker (Columbia University) & Albert T. Corbett (Carnegie Mellon University)
Social Learning Analytics: Navigating the Changing Settings of Higher Education
By Maarten de Laat & Fleur Prinsen (Open University of the Netherlands)
How Predictive Analytics and Choice Architecture can Improve Student Success
By Tristan Denley (Tennessee Board of Regents)
Insight and Action Analytics: Three Case Studies to Consider
By Mark David Milliron, Laura Malcolm & David Kil (Civitas Learning)
Book Review of: Uncharted: Big Data as a Lens on Human Culture
By Carolyn Penstein Rose (Carnegie Mellon University)
Book Review of: Building a Smarter University: Big Data, Innovation and Analytics
By Fabio Rojas (Indiana University)
Book Review of: Assessing the Educational Data Movement
By Karly Sarita Ford (Pennsylvania State University)
An Ethically Ambitious Higher Education Data Science
By Mitchell L. Stevens (Stanford University)
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