Exploring Student-Controlled Social Comparison

Abstract

Previous research on technology-enhanced learning indicated that exposing students to information related to their peers' performance might positively or negatively affect their behavior and performance. For example, recent research has demonstrated that augmenting traditional open learner models (OLMs) with views of the learner model of peers could boost student engagement and affect navigational patterns. On the other hand, the negative impact of social comparison has been also reported in the literature, which demonstrates that a comparison with much better-performing peers presents a threat to self-integrity. These conflicting findings have not yet been reconciled in the context of technology-enhanced learning. This work attempts to extend research in social comparison in an educational context and on OLMs by examining how the potential negative and positive sides of social comparison could be balanced by enabling students to select their peer comparison group, rather than by being forced to compare themselves with an aggregated class average.