Motivational active learning: engaging university students in computer science education

Abstract

Attracting and engaging computer science students to enhance their mathematical and algorithmic thinking skills are challenging tasks. In winter 2013 we introduced a new teaching format for a course, which combines theory in computer science with hands-on algorithmic challenges, mathematical thinking activities, and collaborative problem-solving. Therefore, we introduced the pedagogical model Motivational Active Learning (MAL), which is grounded in MIT's successful format for teaching physics, Technology-Enabled Active Learning (TEAL), and combines it with motivational strategies usually used by game designers. Results from the initial setup in class reveals that students indeed assessed the course structure as more interactive and motivating compared to other similar courses. In this paper we discuss the course design, issues, and the impact, and analyze the first results in detail.