A Holistic approach to assessing students´ laboratory performance using Bayesian networks

Laboratory activities have a central role in engineering teaching and learning. They are used to involve students in practical experimentations with concepts. This central role makes the ongoing challenge of performance assessment of students´ laboratory work one of utmost importance. Laboratory work is traditionally assessed by the teacher marking students´ written report of the laboratory activity. Assessment based on written evidence often overlooks the fact that laboratory work involves specific abilities/skills. The latter are highlighted by both QAA and ABET as part of engineering teaching and learning outcomes. There is a need to develop a model for laboratory performance assessment, which not only assesses what a student knows and understands about the concept addressed by a laboratory activity, but also the student´s laboratory abilities/skills through analysis of the laboratory work process. This paper presents the work so far on the implementation of such a model. The model harnesses the strengths of Bayesian networks and integrates with a virtual electronic laboratory, the RealLab, which was designed and implemented in the course of this work.