Share Paper: A Learning Analytic Approach to Identify Attributes of Learners and Multimedia Instruction that Influence Learning

  1. Gwen Nugent, University of Nebraska, United States
  2. Kevin Kupzyk, University of Nebraska-Lincoln, United States
  3. Lee Miller, University of Nebraska-Lincoln, United States
  4. Leyla Masmaliyeva, University of Nebraska-Lincoln, United States
  5. Leen-Kiat Soh, University of Nebraska, United States
  6. Ashok Samal, University of Nebraska-Lincoln, United States
Tuesday, June 28 10:00-10:30 AM Amphitheater 4 - Faculty of Letters Building

Abstract: This paper describes how statistical evaluation of data obtained from an online tracking system can identify key learner and media variables related to student learning from multimedia learning objects. This learning analytic approach allows the construction of predictive models for student success and provides valuable information about media characteristics that contribute to student learning. The research also identifies moderating effects of instructional strategies that may differentially benefit students with particular characteristics.