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Student Feedback as a Guideline for Higher Education Quality Enhancement

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  • Puska, Adis
  • Ejubovic, Adisa
  • Beganovic, Admir I

Abstract

Increasing competition present in the higher education in B&H has conditioned the trend that institutions need to “fight” for each student via quality development at higher education institutions. This paper deals with means of enhancing quality at eMPIRICA College through continual investigation of students’ satisfaction. For the purpose of this research, we used a quality questionnaire related to quality, satisfaction and loyalty of students. The research was carried out at the start and end of the academic year. This approach ascertained a gap with respect to quality, satisfaction and loyalty of students of eMPIRICA College. Using factor analysis the statements were grouped in 3 quality dimensions. The results of multivariate analysis of variance (MANOVA) showed that there is a significant statistical difference between expected and perceived quality, satisfaction and loyalty on the part of the students. Based on that, a gap between expectations and perceptions was ascertained. The use of t-test revealed that some statements have significant statistical difference in the area of expected and perceived quality, satisfaction and loyalty of students.

Suggested Citation

  • Puska, Adis & Ejubovic, Adisa & Beganovic, Admir I, 2016. "Student Feedback as a Guideline for Higher Education Quality Enhancement," Ekonomika, Journal for Economic Theory and Practice and Social Issues, Society of Economists Ekonomika, Nis, Serbia, vol. 62(4), December.
    • Handle: RePEc:ags:sereko:290324
    DOI: 10.22004/ag.econ.290324
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    Cited by:

    1. Qing Wang & Muhammad Saqib Khan & Muhammad Kamran Khan, 2021. "Predicting user perceived satisfaction and reuse intentions toward Massive Open Online Courses (MOOCs) in the Covid-19 pandemic," International Journal of Research in Business and Social Science (2147-4478), Center for the Strategic Studies in Business and Finance, vol. 10(2), pages 1-11, March.

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    Keywords

    Productivity Analysis;

    Statistics

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