Social Cognitive Theory and the Engineering Gap: A Communication Perspective on Industry-Student Alignment
by Nicholas Low Chun Pin, Tan Kwang Shean
Published: April 30, 2026 • DOI: 10.47772/IJRISS.2026.100400165
Abstract
As artificial intelligence (AI) continues to redefine global industry demands, engineering education faces a critical need for structural realignment to ensure graduate readiness. This study identifies the primary determinants of engineering student competence at INTI International College Penang (IICP), framing the investigation within the multifaceted lens of Social Cognitive Theory (SCT). By examining the triadic reciprocity between cognitive, behavioural, and environmental factors, the research evaluates the impact of curriculum gaps, AI awareness, and the efficacy of industry-academia collaboration on professional development. Employing a quantitative methodology, a survey was administered to 50 diploma and degree engineering students, utilizing a five-point Likert scale to measure perceptions of these specific determinants. Descriptive analysis revealed a compelling shift in student perspectives: while respondents perceived outdated curricula and a lack of AI awareness as less influential than initially anticipated, the adoption of AI tools, practical on-the-job training, industry collaboration, and organizational cultural dynamics emerged as the most significant drivers of competence. These findings advocate for strategic educational reforms that prioritize the integration of AI-driven technologies and the expansion of experiential learning opportunities to bridge the industry-student divide. Furthermore, the study highlights the importance of communicative proficiency alongside technical mastery in modern media ecologies. This research provides policymakers and higher education providers with actionable insights to enhance curricular relevance, ensuring the development of a workforce that is both technically adept and communicatively prepared to navigate the complexities of an increasingly AI-driven industrial landscape. Through this alignment, institutions can better foster innovation and long-term employability for future engineers.