Purpose: The research objective is to address the problem of students’ critical achievement in remote lab courses aiming at identifying the risk factors of students’ failure by exploiting e-learning learning analytics. A robust risk model is developed to serve this purpose. The research is orented into NI-Elvis remote lab courses given that they offer a stable environment in the context of which automation lab courses could be effectively delivered.
Design/methodology/approach: A robust risk model was developed by analyzing students’ behavioral engagement data. The e-learning part of the remote lab course was used to provide the requisite dataset. In detail, a proper binary logistics regression scheme was employed to come up with the aforementioned risk model. The e-learning part was implemented by a specific e-learning platform that is suitable for NI-Elvis remote lab courses. The data was collected after the course completion.
Findings: Factors that are related to students’ engagement (number of theory exercises completed and number of messages sent) appeared to be decisive.
Originality/value: The originality of our research lies in the fact that the issue of students’ critical achievement in remote lab courses is not addressed in a fragmentary way by just carrying out a specific analysis and coming up with results, like many similar studies in the literature. Thereby, a concrete methodology was developed on the basis of an established generic risk management framework. The added value of our research is centered on the fact that our risk model could potentially be applied to any remote lab course to come up with the respective risk factors.