IDEAS home Printed from https://ideas.repec.org/a/sae/sagope/v13y2023i2p21582440231181569.html
   My bibliography  Save this article

What Do Academic Faculty Members Think of Performance Measures of Academic Teaching? A Case Study From a 10-Year Perspective

Author

Listed:
  • Eyal Eckhaus
  • Nitza Davidovitch

Abstract

Much has been written about myths and facts concerning teaching surveys completed by students at academic institutions. The myths usually emerge among faculty members based on their subjective point of view, personal experience, or intuitive interpretation of events. The following case study is the first of its kind, and it follows how academic faculty members evaluate performance measurement of academic teaching and teaching surveys in particular, while examining the change that has occurred over the last decade. The case analysis, examining instructors’ evaluation of teaching surveys completed by students, is based on a group of senior faculty members in Israeli academic institutions. The current study is unique in examining how academic faculty members perceive alternative options for measuring their overall performance in academic teaching as manifested in teaching surveys. One hundred eighty-two questionnaires were collected from senior faculty members at academic institutions, comprised of open-ended questions concerning suggestions for alternative teaching evaluation surveys and their structure. The research findings show that the instructors mention “professional†alternatives and perceive teaching surveys as an unprofessional and populist tool. Assuming that students’ voices and their opinion of teaching are important, professional alternatives for evaluating and improving teaching should find expression—and instructors relate significantly to professional elements at academic institutions as potentially helpful factors.

Suggested Citation

  • Eyal Eckhaus & Nitza Davidovitch, 2023. "What Do Academic Faculty Members Think of Performance Measures of Academic Teaching? A Case Study From a 10-Year Perspective," SAGE Open, , vol. 13(2), pages 21582440231, June.
  • Handle: RePEc:sae:sagope:v:13:y:2023:i:2:p:21582440231181569
    DOI: 10.1177/21582440231181569
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/21582440231181569
    Download Restriction: no

    File URL: https://libkey.io/10.1177/21582440231181569?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Margaret E. Roberts & Brandon M. Stewart & Dustin Tingley & Christopher Lucas & Jetson Leder‐Luis & Shana Kushner Gadarian & Bethany Albertson & David G. Rand, 2014. "Structural Topic Models for Open‐Ended Survey Responses," American Journal of Political Science, John Wiley & Sons, vol. 58(4), pages 1064-1082, October.
    2. Eyal Eckhaus & Zachary Sheaffer, 2018. "Managerial hubris detection: the case of Enron," Risk Management, Palgrave Macmillan, vol. 20(4), pages 304-325, November.
    3. Eyal Eckhaus & Nitza Davidovitch, 2019. "How do Academic Faculty Members Perceive the Effect of Teaching Surveys Completed by Students on Appointment and Promotion Processes at Academic Institutions? A Case Study," International Journal of Higher Education, Sciedu Press, vol. 8(1), pages 171-171, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Everett, Jeff & Shiraz Rahaman, Abu & Neu, Dean & Saxton, Gregory, 2024. "Letters to the editor, institutional experimentation, and the public accounting professional," CRITICAL PERSPECTIVES ON ACCOUNTING, Elsevier, vol. 99(C).
    2. Minchul Lee & Min Song, 2020. "Incorporating citation impact into analysis of research trends," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1191-1224, August.
    3. Marcel Fratzscher & Tobias Heidland & Lukas Menkhoff & Lucio Sarno & Maik Schmeling, 2023. "Foreign Exchange Intervention: A New Database," IMF Economic Review, Palgrave Macmillan;International Monetary Fund, vol. 71(4), pages 852-884, December.
    4. Li Tang & Jennifer Kuzma & Xi Zhang & Xinyu Song & Yin Li & Hongxu Liu & Guangyuan Hu, 2023. "Synthetic biology and governance research in China: a 40-year evolution," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(9), pages 5293-5310, September.
    5. Savin, Ivan & Drews, Stefan & van den Bergh, Jeroen, 2021. "Free associations of citizens and scientists with economic and green growth: A computational-linguistics analysis," Ecological Economics, Elsevier, vol. 180(C).
    6. Vishnu Baburajan & Jo~ao de Abreu e Silva & Francisco Camara Pereira, 2022. "Open vs Closed-ended questions in attitudinal surveys -- comparing, combining, and interpreting using natural language processing," Papers 2205.01317, arXiv.org.
    7. Valérie Mignon & Celso Brunetti & Marc Joëts, 2023. "Reasons Behind Words: OPEC Narratives and the Oil Market," EconomiX Working Papers 2023-24, University of Paris Nanterre, EconomiX.
    8. Ferrara, Federico M. & Masciandaro, Donato & Moschella, Manuela & Romelli, Davide, 2022. "Political voice on monetary policy: Evidence from the parliamentary hearings of the European Central Bank," European Journal of Political Economy, Elsevier, vol. 74(C).
    9. Camilla Salvatore & Silvia Biffignandi & Annamaria Bianchi, 2022. "Corporate Social Responsibility Activities Through Twitter: From Topic Model Analysis to Indexes Measuring Communication Characteristics," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 164(3), pages 1217-1248, December.
    10. Alex Luscombe & Kevin Dick & Kevin Walby, 2022. "Algorithmic thinking in the public interest: navigating technical, legal, and ethical hurdles to web scraping in the social sciences," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(3), pages 1023-1044, June.
    11. Andreas Rehs, 2020. "A structural topic model approach to scientific reorientation of economics and chemistry after German reunification," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1229-1251, November.
    12. Dehler-Holland, Joris & Okoh, Marvin & Keles, Dogan, 2022. "Assessing technology legitimacy with topic models and sentiment analysis – The case of wind power in Germany," Technological Forecasting and Social Change, Elsevier, vol. 175(C).
    13. Laura Battaglia & Timothy Christensen & Stephen Hansen & Szymon Sacher, 2024. "Inference for Regression with Variables Generated from Unstructured Data," Papers 2402.15585, arXiv.org, revised May 2024.
    14. Ulrich Fritsche & Johannes Puckelwald, 2018. "Deciphering Professional Forecasters’ Stories - Analyzing a Corpus of Textual Predictions for the German Economy," Macroeconomics and Finance Series 201804, University of Hamburg, Department of Socioeconomics.
    15. Vita Akstinaite & Graham Robinson & Eugene Sadler-Smith, 2020. "Linguistic Markers of CEO Hubris," Journal of Business Ethics, Springer, vol. 167(4), pages 687-705, December.
    16. Beatrice Ferrario & Stefanie Stantcheva, 2022. "Eliciting People's First-Order Concerns: Text Analysis of Open-Ended Survey Questions," AEA Papers and Proceedings, American Economic Association, vol. 112, pages 163-169, May.
    17. J. Ignacio Conde-Ruiz & Juan José Ganuza & Manu Garcia & Luis A. Puch, 2021. "Gender distribution across topics in Top 5 economics journals: A machine learning approach," Economics Working Papers 1771, Department of Economics and Business, Universitat Pompeu Fabra.
    18. Seraphine F. Maerz & Carsten Q. Schneider, 2020. "Comparing public communication in democracies and autocracies: automated text analyses of speeches by heads of government," Quality & Quantity: International Journal of Methodology, Springer, vol. 54(2), pages 517-545, April.
    19. Temesgen Gelata, Fikiru & Han, Jiqin & Kipkogei Limo, Shadrack, 2024. "Impact of dairy contract farming adoption on household resilience to food insecurity evidence from Ethiopia," World Development Perspectives, Elsevier, vol. 33(C).
    20. Szymon Sacher & Laura Battaglia & Stephen Hansen, 2021. "Hamiltonian Monte Carlo for Regression with High-Dimensional Categorical Data," Papers 2107.08112, arXiv.org, revised Feb 2024.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:sagope:v:13:y:2023:i:2:p:21582440231181569. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.