Cybersecurity Awareness and Digital Privacy Behaviour Among Engineering Students: An Empirical Study Using an Extended Protection Motivation Theory–Technology Acceptance Model Framework

Abstract

Engineering undergraduates now rely heavily on internet-enabled devices, cloud-based academic platforms and social media, which makes cyber security awareness and digital privacy behaviour essential skills for the twenty-first century. This study investigates the level of cyber security awareness, perceived threat, self-efficacy and security behaviour among Bachelor of Technology (B. Tech) students in India, and examines the psychological predictors of their protective behaviour and behavioural intention. An integrated model was used in which Protection Motivation Theory (PMT) constructs are combined with constructs borrowed from the Technology Acceptance Model (TAM). Data from 186 engineering undergraduates in their second, third and fourth years were gathered through a structured questionnaire covering ten constructs: Knowledge/Awareness, Perceived Severity, Susceptibility, Benefits, Self-Efficacy, Usefulness, Ease of Use, Privacy Concern, Protective Behaviour and Behavioural Intention. Every construct showed good to excellent reliability (Cronbach’s α = 0.82–0.93; overall α = 0.98). Mean scores were moderately positive (3.61–3.89 on a 5-point scale), lowest for Perceived Ease of Use and highest for Perceived Benefits. One-way ANOVA revealed that scores for Knowledge, Perceived Susceptibility, Ease of Use, and Privacy Concern increased significantly over study years (p <.05), while independent-samples t-tests revealed that female respondents scored significantly higher than male respondents on Perceived Benefits, Usefulness, Ease of Use, and Behavioural Intention (p <.05). Previous participation in a cyber security workshop or course was the most influential demographic factor: attendees scored significantly higher on all ten constructs (all p ≤ .011). Protective behaviour was significantly predicted by Self-Efficacy, Perceived Ease of Use, Perceived Usefulness, and Privacy Concern in multiple linear regression (R² =.78), while behavioural intention was significantly predicted by Perceived Usefulness, Perceived Susceptibility, Perceived Severity, and Perceived Ease of Use (R² =.63). The results provide India-specific evidence to guide the design of cyber security education in institutions and future PMT-based research on behaviour change in higher education.