Evaluating a learning analytics dashboard to detect dishonest behaviours: A case study in small private online courses with academic recognition

Abstract

AbstractBackgroundSmall private online courses (SPOCs) are one of the strategies to introduce the massive open online courses (MOOCs) within the university environment and to have these courses validates for academic credit. However, numerous researchers have highlighted that academic dishonesty is greatly facilitated by the online context in which SPOCs are offered. And while numerous algorithms have already been proposed, no research has been performed on how to transfer this information to instructors, so that they can intervene and decrease the prevalence of this issue.ObjectivesIn this article, we present a qualitative evaluation of a tool for detecting and monitoring students suspected of academic dishonesty in SPOCs in Selene, a Colombian instance of Open edX.MethodsThe evaluation was carried out through semi‐structured interviews with four instructors who taught SPOCs with academic recognition at the University of Cauca.ResultsThe evaluation results indicated that participants found the dashboard reliable and appropriate to detect academic dishonesty behaviours in order to intervene in these cases.ImplicationsBut interventions are difficult to systematise, need an institutional policy, and there is uncertainty about whether these interventions can actually contribute to decreasing academic dishonesty.