Learning analytics – Understanding past and present and guiding future performance

ID: 54813 Type: Roundtable
  1. Ying-Hsiu Liu, University of Missouri - Columbia, United States
  2. Hui-Wen Tu, Berkeley College, United States

Wednesday, June 26 12:00 PM-1:00 PM Location: De Dam 2 View on map

No presider for this session.

Abstract: Recently, learning analytics have become a popular term among researchers, educators and practitioners. Researchers and educators who have implemented learning analytics do so to understand student-generated data leading to evidence-based predictions of future course outcomes. The analytics can also guide researchers or educators in future decision-making. Educators have found that learning analytics can to apply to various educational contexts serving different purposes and institutional requirements. Thus, in order to use learning analytics to its full potential, while improving teaching and learning in the education setting, it is necessary to document learning analytics usage cases, its challenges and the tool’s limitations. Cases from two institutions will be shared throughout this paper. We will explore topics such as the pedagogical implication, identified critical challenges and tips for success when working with learning analytics.


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