Industry–Academia Collaboration and Technical Skill Development among Students in Higher Education Institutions: Evidence from the Visakhapatnam Region of Andhra Pradesh

Abstract

The demand and supply mismatch between the academia and industry is now one of the most pressing issues of the higher education institutions (HEIs) in India. In this paper, the author tried to investigate empirically the impact of industry-academy collaboration (IAC) on the technical skills of the students in HEIs in the city of Visakhapatnam of Andhra Pradesh. The internship programs, interaction with industry experts, curriculum alignment, live projects, training and workshops and placement relationships are explored in detail under the 6 IAC dimensions.
A quantitative cross-sectional research design was used and the primary data were collected from 320 undergraduate and postgraduate students from autonomous colleges, affiliated colleges and deemed universities. It was in the form of a structured questionnaire with 45 items being answered on a 5-point Likert scale. The study is equipped with an unusually extensive statistical toolbox, including descriptive statistics, Pearson correlation, multiple linear regression, one-way ANOVA, independent samples t-tests, chi-square association tests, exploratory factor analysis (EFA), confirmatory factor analysis (CFA), mediation analysis (Baron & Kenny approach with Sobel test), hierarchical regression, cluster analysis (K-means), and Structural Equation Modelling (SEM) path interpretation.
Key findings: Firstly, the findings indicated that all six IAC dimensions were significant in predicting the development of technical skills (R² = 0.61, F(6,313) = 81.74, p < 0.001); secondly, internship programs (β = 0.294) and live projects (β = 0.277) were the strongest predictors; thirdly, there were significant mean differences across institution type (F = 14.82, p < 0.001) and across programme level (t = 6.44, p < 0.001); fourthly, mediation analysis indicates that the internship–skill development relationship was partially mediated by self-efficacy (Sobel z = 4.21, p < 0.001); and fifthly, cluster analysis identified three distinct student segments characterized by differential pathways to skill development. The results from these studies inform academic administrators, policymakers, and industry partners at the micro level