Revealing Interaction Patterns Among Youth in an Online Social Learning Network Using Markov Chain Principles

Abstract

The problem of the digital divide has shifted attention from access to inequities of participation and opportunities to develop 21st century skills in online learning platforms. In this paper, we explore Markov chain principles in a time-based probabilistic graphical approach to analyze a multi-year data set of log data generated by students from one urban middle school and coded using a framework aligned with 21st century learning activities. Results showed the efficacy of applying Markov chain principles in helping reveal similar and distinct usage patterns of the learners in this community across different time spans. This work has implications for the design and analysis of online learning platforms and for creating opportunities to help youth build 21st century skills using online learning platforms.