Diversifying Cybersecurity: Evaluation of an Internet of Things (IoT)-Based Cybersecurity Training Course Designed to Bridge the Diversity Gap

This study aimed to evaluate the effectiveness of an eight-module Cybersecurity course at increasing the learning outcomes of middle and high school students with little to no experience, including underrepresented minorities (URMs) in Cybersecurity. Twice we administered and evaluated the Cybersecurity course, which included hands-on IoT-based activities, utilizing collaborative learning, scaffolding, and representation-based learning strategies. Using a quasi-experimental, within-subjects, repeated measures design, each participant experienced a pretest, the course, and a post-test to evaluate the impact on learners’ self-efficacy, interest, and knowledge. The results revealed that (1) at pre-test, female (p = .001) and in one course administration minority males (p = .006), knowledge was significantly less than that of non-minority males; (2) from pre-posttest, all groups experienced a significant increase in knowledge F(1, 16) = 15.76, p = .001, ηp2. = .496., and in one course administration, self-efficacy, F(1, 16) = 8.59, p = .01, ηp2. = .349, and interest, F(1, 16) = 8.19, p = .01, ηp2. = .339 as well; and (3) at post-test, there were no longer significant knowledge differences between the student groups (females vs. URM males vs. non-URM males), F(3,15) = .25, p = .25, ηp2 = .25. The results also reveal that one-size-fits-all training approaches may not be ideal to improve learning outcomes for all groups of students, as in collaborative learning activities, the composition of the groups influenced the engagement levels differently for males and females.