Computing Malmquist Index Using Data Envelopment Analysis as an Improvement Measure for Educational Purposes

With the introduction of “Malmquist indices”, MI, (Caves et al, 1982), it has rapidly grown into a standard approach for evaluating productivity over recent years. Meanwhile, Based on the concept of cost efficiency that was first mentioned by Farrell, (1957), the DEA has become a brawny quantitative and analytical tool for measuring and evaluating performance of public and private sectors. With the growth of civilization and vast increase in higher educational institutes around the world, the performance and efficiency of students became very important as far as their evaluation is concerned. Defining educational technology as all necessary resources needed by an institution for accurate student’s performance, we will compute MI using DEA considering some ABET’s accreditation criteria for student outcomes as an improvement measure for educational purposes. As the DEA measure the efficiencies of the student’s performance using a defined set of inputs and outputs, “Malmquist index” conflate the efficiencies with other factors such as surveys to compute an index (productivity) for a course or program which can be compared to unity. Based on this, an educational Malmquist index is defined called Malmquist Educational Index, MEI to evaluate Student Outcomes, performance and monitor continuous improvement of Educational programs. We used a case study example, with real data provided by the chair of the industrial engineering department to compute MEI for each course. Regarding the value MEI, it could be concluded that MEI indicates regress and need improvement, MEI indicates progress and MEI indicates no change for DMU under evaluation. Keywords: Malmquist Index, DEA, Student Outcomes, and Student performance