Teaching Pervasive Computing to CS Freshmen: A Multidisciplinary Approach

Pervasive Computing is a growing area in research and commercial reality. Despite this extensive growth, there is no clear consensus on how and when to teach it to students. We report on an innovative attempt to teach this subject to first year Computer Science students. Our course combines computer science, engineering and social disciplines, such as: data acquisition, signal processing, control theory, machine learning, quality control and ethics. This unusual mix of disciplines is induced by a project-based learning approach. The project challenges the students to develop an assistive pervasive computing system that infers its context by using pattern recognition. This course is yearly taught to approximately 200 freshmen, and receives positive evaluations. Its main strength is that it motivates both non CS major strugglers, as well as top students. This paper describes the course design and its teaching artifacts, and shares our teaching experiences. We are confident that this teaching formula can be applied to other target groups, such as computer engineering, or even liberal arts.