تحلیل و بررسی تاثیر تعامل صنعت و دانشگاه در کیفیت آموزش فنی
Highlights
Abstract
1- Introduction
2- Framework of the study
3- Literature review
4- The system dynamics model
5- Stock and flow diagram
6- Results and analysis
7- Limitations and future scope
8- Conclusion
References
Vitae
Abstract
Indian technical education since the year 1995 experienced an exponential growth which adversely affected the quality of engineering graduates. Many research studies have strongly emphasized on improving the quality of technical education in India. The industry is proactively involved in improving the quality of its raw material suppliers, but it has overlooked academia despite it being an important supplier of human capital to the industry. This is perhaps because the industry adopted myopic approach towards academia considering it as a fruitless option. As a result, there is a visible disconnect between industry and academia in India which is a major cause for the poor quality of technical education. This research paper presents a novel approach to analyze the impact of industry interaction on the quality of technical education through system dynamics (SD) modeling. A computer based model was developed to explain the impact of Industry-Academia (IA) interaction in enhancing the quality of technical education as seen through the employability of graduates. The paper attempts to prove that the proactive involvement of industry in academia is a profitable proposition for both the stakeholders. The study also analyzes the impact of key policy variables on unemployment level, shortage of employees and total cost of involvement of industry in academia. The model was developed using SD simulation software STELLA (version 10.0) and four scenarios were generated to analyze the system behavior. The SD model was simulated for fifty years. The findings of the study reveal that proactive involvement of industry is essential for improving the quality of technical education and is profitable in the long run. The insights from the study would be helpful to policy makers and researchers from the industry and academia in analyzing the long-term implications of decisions using SD modeling.