Digital transformation has become a strategic priority in higher education, particularly in engineering education, where technological innovation, Industry 4.0, and digital competencies are essential for preparing future professionals. However, the successful implementation of digital transformation initiatives depends largely on an institution’s readiness to adapt organizationally, technologically, and strategically. This systematic literature review (SLR) aimed to examine institutional readiness for digital transformation in engineering education by identifying the factors that influence readiness, the challenges and barriers encountered, and the strategies, frameworks, and best practices proposed to enhance readiness. Guided by the PRISMA 2020 framework and Kitchenham Guidelines, the review employed a systematic search using Lens.org, with studies screened and managed through Zotero and Rayyan.ai. From an initial pool of 5,636 records, a rigorous screening, eligibility assessment, and quality evaluation process resulted in 19 studies being included in the final qualitative synthesis. Data were analyzed using thematic analysis, narrative synthesis, and bibliometric analysis. The findings revealed that institutional readiness is primarily influenced by leadership and governance, technological infrastructure, faculty competencies and digital literacy, organizational culture, and institutional support. The review also identified key barriers, including infrastructure limitations, digital competency gaps, resistance to change, resource constraints, and organizational challenges. Furthermore, effective strategies for enhancing readiness include digital leadership and strategic planning, faculty development and capacity building, readiness assessment frameworks, technology integration, and stakeholder collaboration. Overall, the findings suggest that institutional readiness for digital transformation is a multidimensional construct that requires the alignment of technological, organizational, human, and strategic dimensions. This review contributes to the growing body of knowledge on digital transformation in engineering education and provides evidence-based insights for policymakers, institutional leaders, educators, and researchers seeking to strengthen institutional preparedness and support sustainable digital transformation initiatives.
Cristina G. Ang, Neil Mark S. Gasataya, Russel M. Dela Torre· International journal of res...· 0 citations
The integration of Artificial Intelligence (AI) within Technical-Vocational Education and Training (TVET) is increasingly shaping the educational landscape, presenting both novel pedagogical opportunities and complex challenges. This systematic literature review investigates how instructors and students perceive and experience the implementation of AI-supported teaching and learning approaches in TVET settings. This review addresses the growing need to understand the human dimensions of AI adoption in vocational education, particularly from the perspectives of those directly involved in teaching and learning. As AI technologies become increasingly embedded in educational practices, examining the experiences, perceptions, and concerns of instructors and students is essential for informing effective and responsible implementation strategies. By synthesizing evidence across diverse TVET contexts, this review provides insights into emerging opportunities, challenges, and implications for policy and practice. Following the PRISMA 2020 framework, an initial database search on Lens.org yielded 580 records. After applying rigorous inclusion and exclusion criteria, including filters for publication date, document type, and subject matter, 19 empirical studies were selected for final qualitative synthesis. The findings reveal three overarching themes. First, while instructors exhibit optimism regarding efficiency gains, they express significant concerns about dehumanization, cognitive decline, and threats to academic integrity. Second, students experience enhanced psychological safety through instant feedback, yet face a paradox of being "Engaged but Amotivated" alongside risks of severe technological dependency. Third, AI implementation in TVET is uniquely constrained by the necessity for tactile skill mastery, industry precision, and alignment with local cultural practices. Ultimately, maximizing AI's potential in vocational education requires addressing systemic infrastructure barriers and preserving the hands-on, human-centric core of TVET.
Iron G. Morales, John Hillard Mansueto, Russel M. Dela Torre· International journal of res...· 0 citations