A Hybrid Approach To Evaluating The Performance Of Engineering Schools

Science and engineering (S&E) are two disciplines that are highly receptive to the changes in demand for products and services. These disciplines can either be leading in nature, viz., they create the demand in the market (push) for new products and/or services, or can adopt the changes caused by the varying market conditions (pull). Regardless of the reason, both science and engineering have the responsibility to be compatible with the emerging needs of the market. This fact is also true for the institutions awarding science and engineering degrees. Such higher education institutions also require continuous monitoring and evaluation to be able to remain competitive in the educational arena. Generally, educational institutions are evaluated for their (i) academic affairs, and (2) administrative and financial operations. Academic affairs are monitored by outside authorities such as professional accrediting agencies, State Departments of Higher Education, and the regional accrediting bodies (i.e., NEASC), whereas outcome assessment for administrative and financial operations are handled by the Board of Trustees and the regional accrediting body. In addition, educational institutions also have internal assessment processes conducted to (1) ensure the ability to meet and/or exceed the national educational standards, (2) to be compatible with the mission and vision statements of the organization, and (3) to guarantee the continuous improvement of students, academic and administrative personnel. This internal assessment process embodies a broad spectrum of performance criteria such as curriculum development and revision, contributions to the literature, ethnicity/gender profiles, budget allocation, and student and personnel development. Therefore, several factors that are tangible and intangible in nature have to be considered during internal reviews, thus creating a complex problem environment for the evaluators/decision makers. This being the motivation, this paper proposes a Data Envelopment Analysis (DEA) model to compare each department in the School of Engineering at the University of Bridgeport with each other and with the School. Data and case studies are provided to demonstrate the functionality of the proposed model.