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Learning Analytics in Higher Education: Exploring Big Data on Campus
Mon, April 11, 11:45am to 1:15pm, Convention Center, Floor: Level One, Room 149 BSession Type: Symposium
Abstract
Learning analytics (educational big data) is revolutionizing higher education, by providing insight into institutional context, strategic decision-making, and pedagogical and advising effectiveness. The promise learning analytics offers makes understanding its impact not just useful, but imperative. The purpose of this interactive symposium is to provide an overview of central issues related to learning analytics; create a forum for participants to share current work; and allow for the establishment of new scholarly partnerships and practices at the intersection of big data and higher education.
Sub Unit
Chair
Papers
Big Data, Small Data, and Data Shepherds - Jennifer Deboer, Purdue University
Data Analytics for Linking Institutional Context and Individual Outcomes in Higher Education: A Nested Structuration Perspective - Aditya Johri, George Mason University
Improving Academic Pathways by Mining University Data - George Karypis, University of Minnesota
A Human-Centered Design Approach to Learning Analytics - David Knight, Virginia Polytechnic Institute and State University
Learning Analytics in Higher Education: Making the Connections Among Data, Learning, and Outcomes - Huzefa Rangwala, George Mason University