Learning Analytics: Big Data, the Bigger the Better?

• In Event: ICEM - Learning Analytics: Big Data, the Bigger the Better?

Short Description

Learning Analytics (LA) provide statistical evaluation of rich data sources to discern learning patterns that enhance teaching and learning. At the individual learner level, students could apply a visual dashboard to track personal progress; analytics can be valuable tool for self-assessment and a powerful component of a personal learning environment. LA might facilitate better communication between students and educators while empowering students to monitor their coursework and take greater responsibility for their learning. What are the implications for teaching and learning? What are the issues, challenges, and risks that students exposed to LA may encounter? How about legal and ethical considerations, including privacy, security, and ownership in LA? Are measurements of LA neutral and reflect what we consider as good education, pedagogy, and assessment practices? This panel discussion intends to obtain better understanding of LA their capacities, applications, challenges, issues, and risks etc.

Authors

• Chih-Hsiung Tu, Northern Arizona University

• Marina S. McIsaac, Arizona State University

• Rick Shearer, Penn State University

• Robert Doyle, Harvard University

• Cengiz Hakan AYDIN, Anadolu University

• Cheng-Chang (Sam) Pan, University of Texas at Brownsville

• Hsin-Te Yeh, Metropolitan State University of Denver