The Role of Multiple Representations and Representational Fluency in Cryptography Education

Both the public sector and private sector have strong demand for qualified cybersecurity professionals. It is therefore imperative that higher education institutions can fill the gap by producing more skilled graduates that have deep understanding of cybersecurity. Cryptography is one of those fundamental subjects that is difficult to learn and error-prone in practice. This work aims to understand if multiple representations and representational fluency can help students better learn new cryptography concepts. Experiments were designed to present the same new cryptography concepts using three different representations to the participants: language, graph, and math notations. Assessments with different representations were then conducted after the learning phase to associate the learning gains with the learning behaviors. An eye tracker was adopted in this study to keep track of the learning behaviors of the participants'. This IRB approved study recruited 43 undergraduate students who are majored in IT. Results showed that most participants are language dominant learners. Graphic and math representations are able to help students to improve their comprehensions on new cryptography concepts.