Leveraging Log Data From Simulations in Technology-Enhanced Learning Environments to Understand Students' Learning Patterns

• In Event: Paper Session: New Directions in Learning Analytics and Assessment

Abstract

As technology becomes more prevalent in classrooms learning environments, it is possible to collect an infinite amount of information both about student learning and about their learning processes (DiCerbo & Behrens, 2014). Interactive science simulations offer the potential to collect fine-grained, log data that may be used to provide insight into student learning patterns. In order to inform the design of simulations and make meaningful inferences about actions, this study investigates the relationship between log data variables from two middle-school chemistry simulations and reflection scores to determine actions that are significantly related to improved learning. Differences in significant actions between the two simulations suggest aspects of the simulations that may have aided or impaired student learning.

Authors

• Emily Toutkoushian, University of North Carolina - Chapel Hill

• Amanda Swearingen, University of North Carolina - Chapel Hill

• Kihyun "Kelly" Ryoo, University of North Carolina - Chapel Hill

• Robert Plumley, University of North Carolina, Chapel Hill