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Evaluating higher education teaching performance using combined analytic hierarchy process and data envelopment analysis

Author

Listed:
  • Emmanuel Thanassoulis

    (Aston University)

  • Prasanta Kumar Dey

    (Aston University)

  • Konstantinos Petridis

    (Aston University)

  • Ioannis Goniadis

    (University of Macedonia)

  • Andreas C. Georgiou

    (University of Macedonia)

Abstract

Evaluating higher education teaching performance is complex as it involves consideration of both objective and subjective criteria. The student evaluation of teaching (SET) is used to improve higher education quality. However, the traditional approaches to considering students’ responses to SET questionnaires for improving teaching quality have several shortcomings. This study proposes an integrated approach to higher education teaching evaluation that combines the analytical hierarchy process (AHP) and data envelopment analysis (DEA). The AHP allows consideration of the varying importance of each criterion of teaching performance, while DEA enables the comparison of tutors on teaching as perceived by students with a view to identifying the scope for improvement by each tutor. The proposed teaching evaluation method is illustrated using data from a higher education institution in Greece.

Suggested Citation

  • Emmanuel Thanassoulis & Prasanta Kumar Dey & Konstantinos Petridis & Ioannis Goniadis & Andreas C. Georgiou, 2017. "Evaluating higher education teaching performance using combined analytic hierarchy process and data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(4), pages 431-445, April.
    • Handle: RePEc:pal:jorsoc:v:68:y:2017:i:4:d:10.1057_s41274-016-0165-4
    DOI: 10.1057/s41274-016-0165-4
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    1. De Witte, Kristof & Rogge, Nicky, 2011. "Accounting for exogenous influences in performance evaluations of teachers," Economics of Education Review, Elsevier, vol. 30(4), pages 641-653, August.
    2. Yang, Taho & Kuo, Chunwei, 2003. "A hierarchical AHP/DEA methodology for the facilities layout design problem," European Journal of Operational Research, Elsevier, vol. 147(1), pages 128-136, May.
    3. Sueyoshi, Toshiyuki & Shang, Jennifer & Chiang, Wen-Chyuan, 2009. "A decision support framework for internal audit prioritization in a rental car company: A combined use between DEA and AHP," European Journal of Operational Research, Elsevier, vol. 199(1), pages 219-231, November.
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    13. Badiee, Aghdas & Moshtari, Mohammad & Berenguer, Gemma, 2024. "A systematic review of operations research and management science modeling techniques in the study of higher education institutions," Socio-Economic Planning Sciences, Elsevier, vol. 93(C).
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    15. Qi-Zhen Zhang & Shan Jiang & Ran Liu & Hu-Chen Liu, 2020. "An Integrated Decision-Making Model for Analyzing Key Performance Indicators in University Performance Management," Mathematics, MDPI, vol. 8(10), pages 1-16, October.
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    19. Lihui Xiong & Ximiao Dong & Jiaqi Fang, 2023. "Interdisciplinary Teaching Reform of Financial Engineering Majors Based on the Analytic Hierarchy Process in the Post-Pandemic Era," Sustainability, MDPI, vol. 15(11), pages 1-17, May.
    20. Ao Yu & Zhuoqiang Jia & Weike Zhang & Ke Deng & Francisco Herrera, 2020. "A Dynamic Credit Index System for TSMEs in China Using the Delphi and Analytic Hierarchy Process (AHP) Methods," Sustainability, MDPI, vol. 12(5), pages 1-21, February.
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