Towards Automated Evaluation of the Quality of Educational Services in HEIs

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Abstract

The provision of educational services with high quality is a matter of concern to all stakeholders in higher education (academic staff, administration, students, etc.). According to many researchers, student satisfaction is an indicator of service quality in higher education institutions (HEIs), and evaluating the quality of educational and administrative services from students is an effective tool for improving the quality of HEIs. To ensure a competitive benefit over other educational institutions, HEIs leadership should take measures leading to improved student feedback on the quality of the provided administrative and education services, seek ways to exceed student expectations and provide high-quality services. Due to the great importance of the opinion of students on the quality of the services offered, many HEIs develop and use tools to assess student satisfaction with the quality of the services in the HEI. Little researched in the literature is the issue regarding the need to develop tools for HEIs leadership allowing survey results analysis, tracking trends over the years and comparing HEIs results. Based on a detailed analysis of developed questionnaires for evaluating the quality of services, this paper explores the possibilities of automation of the overall process for conducting questionnaire surveys of student’s satisfaction with the quality of services. As a result, a software prototype of a tool to automate the entire process for assessing student satisfaction is proposed - from questionnaire modelling, survey organizing and conducting to the analysis of the collected data. The developed tool allows governing bodies in HEIs to make informed decisions to improve the quality of services and to compare the results with those of competing universities.

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APA

Gaftandzhieva, S., Doneva, R., Zhekova, M., & Pashev, G. (2023). Towards Automated Evaluation of the Quality of Educational Services in HEIs. International Journal of Advanced Computer Science and Applications, 14(8), 150–165. https://doi.org/10.14569/IJACSA.2023.0140818

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