Leveraging Learning Analytics to Guide Online Learning Design

Tuesday, March 27 | 12:45PM–1:30PM | Zurich B
Session Type: Professional Development
The increasing use of learning technologies has offered access to tremendous amounts of student data that can be utilized to improve teaching and learning practices. This research tracked the interactions of students enrolled in an online course, gathered data on their learning characteristics, and searched for better learning design solutions. A dynamic learning analysis (DLA) model was proposed to marry student data from different sources. It can be used to tailor online learning design to individual learners more effectively, develop personalized online instruction, and guide the design and selection of cloud-based learning tools.


  • Haijun Kang

    Associate Professor, Kansas State University

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