Impact of AI-Enhanced Capture the Flag (CTF) competitions on student learning outcomes in cybersecurity training: a qualitative study

Ojugo, Okhae Joel and Afaha, Nse-obot Peter (2025) Impact of AI-Enhanced Capture the Flag (CTF) competitions on student learning outcomes in cybersecurity training: a qualitative study. Open Access Research Journal of Engineering and Technology, 8 (2). 073-080. ISSN 2783-0128

Abstract

Capture The Flag (CTF) competitions have been widely used as an educational tool in cybersecurity training. To enhance learning outcomes among students, AI has been integrated into CTF competitions, which have affected students in the use of AI-enhance CTF competitions. Thus, this study assessed the impact of AI-enhanced capture the flag (CTF) competitions on student learning outcomes in cybersecurity training. This study employed a qualitative research design of a phenomenological type. The population for this study comprised individuals (students) enrolled in cybersecurity-related programs who have participated in AI-enhanced CTF competitions. A purposive sampling technique was employed to select eight (8) participants who have direct experience with AI-enhanced CTF competitions. The research data was collected using semi-structured interviews, which was conducted online (zoom). Thematic analysis was used to analyze the data and answer the research questions. The study revealed that students’ experiences with AI-enhanced Capture the Flag (CTF) competitions were largely positive and multifaceted. AI-enhanced CTFs significantly shaped students’ problem-solving behaviors and critical thinking approaches. It was recommended in the study that educational institutions and training centers should integrate AI-enhanced Capture the Flag (CTF) competitions into their cybersecurity curricula.

Item Type: Article
Official URL: https://doi.org/10.53022/oarjet.2025.8.2.0044
Uncontrolled Keywords: Capture The Flag (CTF); Artificial Intelligence; Cybersecurity; Student Learning Outcomes; Jeopardy-Style CTF; Attack-Defense-Style CTF
Date Deposited: 01 Sep 2025 14:11
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URI: https://eprint.scholarsrepository.com/id/eprint/5520