Learning Analytics, Quantified Self, & Personalized/Personal Learning: Keeping up with big data

• In Event: ICEM-Annual Graduate Student Panel Discussion

Short Description

ICEM-USA’s 9th annual graduate student panel discussion is a collaborative session to provide graduate students from all over the world a platform to share their research and practices in emerging technologies. Learning Analytics, Quantified Self, & Personalized/Personal Learning has been selected as the key discussion topic for AECT 2016. Graduate students in educational technology are frequently the earliest adopters of learning technologies. Their ideas, perceptions, applications, practices, and research are valuable to share with academic communities to shed light on Quantified Self and Learning Analytics. Four to six student panelists will be selected from all over the world. A facilitator and four commentators, who are ICEM-USA professional members, will comprise this panel discussion.

Authors

• Chih-Hsiung Tu, Northern Arizona University

• Robert Doyle, Harvard University

• Marina S. McIsaac, Arizona State University

• Richard Albert Cornell, University of Central Florida

• Cheng-Chang (Sam) Pan, Nova Southeastern University

• Hsin-Te Yeh, Metropolitan State University of Denver

• Ben Sencindiver, Colorado State University

• Najia Sabir, Indiana University

• Nicole Wang, Penn State University

• Aaron Thomas, University of Florida

• Carole Beal, University of Florida

• Jennifer Drew, University of Florida