Active Learning Strategies: A Computing Course for Undergraduates

The programming language Python is simple and easy to learn and is used for students with no prior background in programming. Several colleges and universities teach Python to students who are learning a programming language for the first time. In this paper, we present a curricular model for introducing, through active learning strategies, data analytics concepts and applications into an introductory computer science course for non-majors. We have designed the course to use a variety of hands-on laboratory projects that use the Python programming language and associated tools. While introducing students to an important research area, we believe the use of these projects improves students’ learning experiences, enables them to apply and relate fundamental computational thinking concepts of algorithmic reasoning, data representation, and computational efficiency to data analytics problems. Assessment results show that introducing data analytics concepts and applications through active learning strategies enhanced students’ computing capability to solve problems.