Beyond Traditional Metrics: Using Automated Log Coding to Understand 21st Century Learning Online

Abstract

While log analysis in massively open online courses and other online learning environments has mainly focused on traditional measures, such as completion rates and views of course content, research is responding to calls for analytic frameworks that are more reflective of social learning models. We introduce a generalizable approach to automatically code log data that highlights educator support roles and student actions that are consistent with recent conceptualizations of 21st century learning, such as creative production, self-directed learning, and social learning. Here, we describe details of a log-coding framework that builds from prior mixed method studies of the use of iRemix, an online social learning network, by middle school youth and adult educators in blended learning contexts.