LAUSR

This paper aims to develop a Student Workload Estimator tool for University students. Traditionally, modular credit has been used as a student workload indicator at a purely time-based stage. This needs rethinking keeping in view the changing educational settings. The paper presents a basic student workload model built to assess student workload in a more realistic and detailed manner taking into consideration objective factors as well as subjective factors for personalized model. It presents a mechanism for data collection of course workload as well as of the students’ subjective perceptions for the workload estimator. The outcomes are expected to provide more insights than only estimated weekly working hours indicated by modular credit, thus allowing students to make more informed decisions for a suitable academic path and to help reduce the course dropping rate. Deliverables of the work include a data collection tool and a workload estimator tool.