The Significant Contextual Predictors of Industrial Academic Collaboration in Engineering

Abstract

In a Modern Economy, transforming academics into competitive advantages is pivotal. The present work discusses the impact and challenges of academia-industry collaboration on academic output and campus placement preparation. This study explores the contextual predictors related to core placement and industrial-academic collaboration requirements among undergraduate students in Engineering. Industrial -academic training and placement intent are defined as the core competence and the students undergo these trainings to develop the skills in order to get placement in the core domains of RTL Verification using System Verilog, SOC-ASIC physical design, Embedded system design, IoT and Artificial intelligence for Cyber security. Overall, 509 students have been included as participants and they are students of second year, third year, and final year engineering from the Department of Electronics and Communication Engineering of Kalasalingam Academy of Research and Education. This work examines the Collaborative Success in Learning New Application, Teaching Research Level Collaboration, and Preparation for First Campus Placement. The statistical Analysis of Regression has been utilized to address the relationships. Skill training from industry and participation in domain-specific activities are more strongly intended for engineering undergraduate students during their course. The analysis pertains that both are significant parameters. However, the level of significance is more in Collaborative Success in Learning New Application (CSLNA) compared to Teaching Research Level Collaboration (TRLC) for the confidence level in Preparation for First Campus Placement (PFCP).