IDEAS home Printed from https://ideas.repec.org/p/wpa/wuwpgt/0503011.html
   My bibliography  Save this paper

Heterogeneous Students, Impartial Teaching and Optimal Allocation of Teaching Methods

Author

Listed:
  • Carmen Lamagna

    (American International University Bangladesh)

  • Sheikh Selim

    (University of Southampton)

Abstract

This paper addresses the issue of identifying optimal mix of teaching methods for an instructor when students are of heterogeneous types. The exact student type cannot be identified ex ante which forces the instructor to act impartially and allocate teaching methods according to some pre-designed plan. In a simple model of instructor-student interaction, we show that if the instructor acts benevolent and impartially towards preparing the initial teaching method plan, there exists a unique optimal mix of teaching methods. We calibrate the impartial teaching model with data on the teaching of Business and Economics related undergraduate and postgraduate units, and find that the characterized optimal teaching method mix differs significantly across different units.

Suggested Citation

  • Carmen Lamagna & Sheikh Selim, 2005. "Heterogeneous Students, Impartial Teaching and Optimal Allocation of Teaching Methods," General Economics and Teaching 0503011, University Library of Munich, Germany.
    • Handle: RePEc:wpa:wuwpgt:0503011
    Note: Type of Document - pdf; pages: 22. AIUB-ORP Working paper version December 2004. Final version accepted for publication in the AIUB Journal of Business & Economics (AJBE).
    as

    Download full text from publisher

    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/get/papers/0503/0503011.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Correa, Hector & Gruver, Gene W., 1987. "Teacher-student interaction: A game theoretic extension of the economic theory of education," Mathematical Social Sciences, Elsevier, vol. 13(1), pages 19-47, February.
    2. Allgood, Sam, 2001. "Grade targets and teaching innovations," Economics of Education Review, Elsevier, vol. 20(5), pages 485-493, October.
    3. Huang, Cliff J., 1981. "Optimal allocation of faculty time under uncertainty in production," Economics of Education Review, Elsevier, vol. 1(1), pages 99-112, February.
    4. Oosterbeek, Hessel, 1995. "Choosing the optimum mix of duration and effort in education," Economics of Education Review, Elsevier, vol. 14(3), pages 253-263, September.
    5. Becker, William E, Jr, 1982. "The Educational Process and Student Achievement Given Uncertainty in Measurement," American Economic Review, American Economic Association, vol. 72(1), pages 229-236, March.
    6. McDonough, Carol C & Kannenberg, Lloyd C, 1977. "The Microeconomic Impact of a Reduction in Faculty Teaching Loads," Australian Economic Papers, Wiley Blackwell, vol. 16(28), pages 112-120, June.
    7. Ross Guest, 2001. "The Instructor's Optimal Mix of Teaching Methods," Education Economics, Taylor & Francis Journals, vol. 9(3), pages 313-326.
    8. Bacdayan, Andrew W., 1997. "A mathematical analysis of the learning production process and a model for determining what matters in education," Economics of Education Review, Elsevier, vol. 16(1), pages 25-37, 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. Ross Guest, 2001. "The Instructor's Optimal Mix of Teaching Methods," Education Economics, Taylor & Francis Journals, vol. 9(3), pages 313-326.
    2. Gomis-Porqueras, Pedro & Rodrigues-Neto, José A., 2018. "Teaching technologies, attendance, learning and the optimal level of access to online materials," Economic Modelling, Elsevier, vol. 73(C), pages 329-342.
    3. Pedro Gomis-Porqueras & Juergen Meinecke & Jose A. Rodrigues-Neto, 2011. "New Technologies in Higher Education: Lower Attendance and Worse Learning Outcomes?," Agenda - A Journal of Policy Analysis and Reform, Australian National University, College of Business and Economics, School of Economics, vol. 18(1), pages 69-84.
    4. Piopiunik, Marc & Schwerdt, Guido & Woessmann, Ludger, 2013. "Central school exit exams and labor-market outcomes," European Journal of Political Economy, Elsevier, vol. 31(C), pages 93-108.
    5. Hui Chen & Guanghui Fu & Huiqin Wu & Yao Xiao & Xuan Nie & Wenjin Zhao, 2024. "Sustainable Collaboration and Incentive Policies for the Integration of Professional Education and Innovation and Entrepreneurship Education (IPEIEE)," Sustainability, MDPI, vol. 16(17), pages 1-24, August.
    6. Allgood, Sam, 2001. "Grade targets and teaching innovations," Economics of Education Review, Elsevier, vol. 20(5), pages 485-493, October.
    7. Miguel Ricardo Rueda, 2006. "Efecto De Exigencia En Calificaci√Ìn Sobre El Desempeno Acad√Âmico. Estudio De Los Cursos De Matem√Åticas B√Åsicos En La Universidad De Los Andes," Documentos CEDE 2414, Universidad de los Andes, Facultad de Economía, CEDE.
    8. Michael Ostrovsky & Michael Schwarz, 2010. "Information Disclosure and Unraveling in Matching Markets," American Economic Journal: Microeconomics, American Economic Association, vol. 2(2), pages 34-63, May.
    9. Becker, William E. & Powers, John R., 2001. "Student performance, attrition, and class size given missing student data," Economics of Education Review, Elsevier, vol. 20(4), pages 377-388, August.
    10. Schwerdt, Guido & Woessmann, Ludger, 2017. "The information value of central school exams," Economics of Education Review, Elsevier, vol. 56(C), pages 65-79.
    11. Correa, Hector, 2003. "A game theoretical analysis of the educational impact of differences in the abilities and work ethics of teachers and students," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 32(3), pages 249-263, July.
    12. Robert Baumann & David Chu & Charles Anderton, 2009. "Religious penalty in the U.S. News & World Report college rankings," Education Economics, Taylor & Francis Journals, vol. 17(4), pages 491-504.
    13. Sumit Ghosh & N. Sivakumar, 2015. "Beta Clustering of Impact of Crude-Oil Prices on the Indian Economy," Journal of Applied Management and Investments, Department of Business Administration and Corporate Security, International Humanitarian University, vol. 4(1), pages 24-34.
    14. Chadi, Adrian & de Pinto, Marco & Schultze, Gabriel, 2019. "Young, gifted and lazy? The role of ability and labor market prospects in student effort decisions," Economics of Education Review, Elsevier, vol. 72(C), pages 66-79.
    15. Hans Bonesrønning, 2003. "Class Size Effects on Student Achievement in Norway: Patterns and Explanations," Southern Economic Journal, John Wiley & Sons, vol. 69(4), pages 952-965, April.
    16. Tisha L. N. Emerson & Beck A. Taylor, 2004. "Comparing Student Achievement across Experimental and Lecture‐Oriented Sections of a Principles of Microeconomics Course," Southern Economic Journal, John Wiley & Sons, vol. 70(3), pages 672-693, January.
    17. Hans Bonesrønning, 2004. "Do the teachers' grading practices affect student achievement?," Education Economics, Taylor & Francis Journals, vol. 12(2), pages 151-167.
    18. De Fraja, Gianni & Landeras, Pedro, 2006. "Could do better: The effectiveness of incentives and competition in schools," Journal of Public Economics, Elsevier, vol. 90(1-2), pages 189-213, January.
    19. Ninos P. Malek & Joshua C. Hall & Collin Hodges, 2014. "A Review and Analysis of the Effectiveness of Alternative Teaching Methods on Student Learning in Economics," Working Papers 14-27, Department of Economics, West Virginia University.
    20. Kiridaran Kanagaretnam & Robert Mathieu & Alex Thevaranjan, 2003. "An economic analysis of the use of student evaluations: implications for universities," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 24(1), pages 1-13.

    More about this item

    Keywords

    ;
    ;
    ;

    JEL classification:

    • A - General Economics and Teaching

    Statistics

    Access and download statistics

    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:wpa:wuwpgt:0503011. 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: EconWPA The email address of this maintainer does not seem to be valid anymore. Please ask EconWPA to update the entry or send us the correct address (email available below). General contact details of provider: https://econwpa.ub.uni-muenchen.de .

    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.