Automated Statistical Analysis for Improving HEIs Training Performance

Abstract

Among the most vital key performance indicators for the quality of educational services offered by higher education institutions (HEIs) are students' retention and success rate. The number of trained students is also decisive for financing HEIs. Therefore, HEIs leaders need continuous access to data on current students in aggregated form to help them to formulate concrete and consistent, data-driven decisions to improve the quality of educational services, to attract and retain more students, and monitor the number of students. This paper offers a software tool developed for decision-making bodies in Bulgarian HEIs (deans' and rectors' management). The tool retrieves and analyses data from university information systems on students and generates aggregated reports that allow governing bodies to track the number of students at different levels (study programme, faculty, professional field) and to monitor indicators related to the accomplishment of the institutional training capacity determined by the state for admission (maximum number of students). These reports can help HEIs leaders to make timely, data-driven decisions for increasing student retention rate, determining how many admission places it can announce, and the need to change the capacity within the following accreditation procedure. Results of tool experimentation are discussed.