Inquiry-based environments for bio-signal processing training in engineering education

Abstract

Active student engagement, teaching via experience in real-life settings and learning by doing, are pedagogical strategies appropriate to improve student-reasoning skills. By building models, performing investigations, examining and explaining experimental results, using theoretical and computational thinking, constructing representations, undergraduates can acquire a deeper understanding of fundamental disciplinary concepts while reinforcing transversal abilities. In this framework, Engineering courses should be designed with the final objective to develop practical skills, focusing on hands-on activities. This contribution presents two different inquiry-based learning environments recently experienced at the University of Palermo in the context of bioelectronic and biomedical Engineering. The first study describes a laboratory activity about digital ophthalmologic signal classification; the second laboratory focuses on the analysis of the prefrontal cortex activation during a memory task using functional Near InfraRed Spectroscopy (fNIRS). We introduce and discuss the learning workshops, with the research objective of improving current instruction and training in Engineering courses. Indeed, this contribution aims to suggest a conceptual framework in the form of a structured elective suite of modules tailored to meet the needs of Engineering graduates. The outcomes of both studies seem to highlight that self-directed learning activities could enhance students’ enthusiasm to learn and engagement in engineering investigations, contributing to improve the achievements of students and acquire a more effective learning approach.