Integrated Education of Data Analytics and Information Security through Cross-Curricular Activities

Abstract

The National Research Council's report states that cross-sectional studies of multiple courses within a discipline, or all courses in a major, would enhance the understanding of how people learn the concepts, practices, and ways of thinking of science and engineering and the nature and development of expertise in a discipline. In science and engineering, ever-evolving technology and information make integrative abilities necessary and especially valuable. In this study, we investigated cross-curricular pedagogy, by engaging undergraduate students of two disciplines in collaboration on a common, context-connected project, so that students are better prepared for solving interdisciplinary problems in career settings. We implemented cross-curricular pedagogy in a network security course and a big data analytics course. The era of big data enables data-driven malicious detection, and big data analytics techniques have been applied to analyzing network logs to reinforce information security and predict abnormal behaviors, so these domains overlap. We investigated two forms of cross-curricular activities: one was integrated instructional units, and the other was cross-curricular knowledge integration projects. The results show significant improvements in students confidence in solving cross-disciplinary problems and a much better understanding of data analytics and information security, as well as the connections between them. This project is the first to study the loose integration of two context-connected courses that are taught in parallel.