Designing Ethical AI-Integrated Cybersecurity Education: A Qur’anic Values Informed Framework for Responsible Digital Learning

The rapid integration of artificial intelligence into cybersecurity education presents unprecedented ethical challenges that existing Western-centric frameworks inadequately address for diverse global contexts. As AI systems become increasingly pervasive in cybersecurity operations, the need for ethically grounded professionals has intensified, yet the cultural homogeneity of current ethical frameworks limits their relevance and effectiveness across Muslim-majority societies representing 1.8 billion people. This study develops and validates a novel pedagogical framework grounding AI-integrated cybersecurity education in Qur'anic ethical principles, offering an alternative paradigm for responsible digital learning in Muslim-majority contexts while contributing to genuinely pluralistic global AI ethics discourse. Employing a rigorous mixed-methods approach, we conducted (1) a systematic literature review of 80 foundational references spanning AI ethics, cybersecurity education, and Islamic ethics; (2) integrative theoretical synthesis mapping Qur'anic principles to contemporary AI ethics challenges; (3) expert validation through a three-round modified Delphi technique with 42 international experts across AI ethics, cybersecurity education, and Islamic studies; and (4) quasi-experimental pilot implementation with 237 undergraduate students across three universities, comparing QVIF-based curriculum against traditional approaches. The Qur'anic Values-Informed Framework (QVIF) successfully integrates five core principles Amanah (trust/responsibility), Adl (justice), Ihsan (excellence), Ilm (knowledge), and Maslaha (public interest) demonstrating 95% alignment with established international AI ethics frameworks while maintaining distinctive cultural resonance. Validation results demonstrated exceptional expert consensus (Fleiss' κ = 0.82, p < 0.001; Content Validity Index = 0.91). Pilot implementation revealed significantly greater ethical awareness gains in the experimental group (M = + 22.4, SD = 8.3) compared to control (M = + 10.3, SD = 10.2), with large effect size (Cohen's d = 1.35, p < 0.001). Cultural relevance ratings significantly favored QVIF (6.5/7.0 vs. 4.2/7.0, p < 0.001). This framework represents the first systematic integration of Islamic ethical principles with AI cybersecurity education, demonstrating that non-Western value systems can enhance, not merely accommodate, global AI ethics discourse while addressing unique cultural-educational needs. The findings carry significant implications for educational institutions across 57 OIC member states, international AI governance frameworks, and the broader project of culturally-diverse responsible innovation.