IDEAS home Printed from https://ideas.repec.org/a/taf/jeduce/v40y2009i2p115-137.html
   My bibliography  Save this article

The Effects of Remedial Mathematics on the Learning of Economics: Evidence from a Natural Experiment

Author

Listed:
  • Johan N. M. Lagerlöf
  • Andrew J. Seltzer

Abstract

The authors examined the effects of remedial mathematics on performance in university-level economics courses using a natural experiment. They studied exam results prior and subsequent to the implementation of a remedial mathematics course that was compulsory for a subset of students and unavailable for the others, controlling for background variables. They found that, consistent with previous studies, the level of and performance in secondary school mathematics have strong predictive power on students' performances at university-level economics. However, they found relatively little evidence for a positive effect of remedial mathematics on student performance.

Suggested Citation

  • Johan N. M. Lagerlöf & Andrew J. Seltzer, 2009. "The Effects of Remedial Mathematics on the Learning of Economics: Evidence from a Natural Experiment," The Journal of Economic Education, Taylor & Francis Journals, vol. 40(2), pages 115-137, April.
    • Handle: RePEc:taf:jeduce:v:40:y:2009:i:2:p:115-137
    DOI: 10.3200/JECE.40.2.115-137
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.3200/JECE.40.2.115-137
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.3200/JECE.40.2.115-137?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
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Eric P. Bettinger & Bridget Terry Long, 2009. "Addressing the Needs of Underprepared Students in Higher Education: Does College Remediation Work?," Journal of Human Resources, University of Wisconsin Press, vol. 44(3).
    2. Dolton, Peter J & Makepeace, G H, 1990. "The Earnings of Economics Graduates," Economic Journal, Royal Economic Society, vol. 100(399), pages 237-250, March.
    3. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521608275.
    4. Massimiliano BRATTI & Luca MANCINI, 2003. "Differences in Early Occupational Earnings of UK Male Graduates by Degree Subject: Evidence from the 1980-1993 USR," Working Papers 189, Universita' Politecnica delle Marche (I), Dipartimento di Scienze Economiche e Sociali.
    5. Dolado, Juan J & Morales, Eduardo, 2007. "Which Factors Determine Academic Performance of Undergraduate Students in Economics? Some Spanish Evidence," CEPR Discussion Papers 6237, C.E.P.R. Discussion Papers.
    6. Roger Koenker & Kevin F. Hallock, 2001. "Quantile Regression," Journal of Economic Perspectives, American Economic Association, vol. 15(4), pages 143-156, Fall.
    7. Durden, Garey C & Ellis, Larry V, 1995. "The Effects of Attendance on Student Learning in Principles of Economics," American Economic Review, American Economic Association, vol. 85(2), pages 343-346, May.
    8. Koenker,Roger, 2005. "Quantile Regression," Cambridge Books, Cambridge University Press, number 9780521845731.
    9. J. S. Butler & T. Aldrich Finegan & John J. Siegfried, 1998. "Does more calculus improve student learning in intermediate micro- and macroeconomic theory?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(2), pages 185-202.
    10. Eide, Eric & Showalter, Mark H., 1998. "The effect of school quality on student performance: A quantile regression approach," Economics Letters, Elsevier, vol. 58(3), pages 345-350, March.
    11. Charles L. Ballard & Marianne F. Johnson, 2004. "Basic Math Skills and Performance in an Introductory Economics Class," The Journal of Economic Education, Taylor & Francis Journals, vol. 35(1), pages 3-23, January.
    12. Jane S. Lopus, 1997. "Effects of the High School Economics Curriculum on Learning in the College Principles Class," The Journal of Economic Education, Taylor & Francis Journals, vol. 28(2), pages 143-153, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Melanie A. Fennell & Irene R. Foster, 2021. "Test Format and Calculator Use in the Testing of Basic Math Skills for Principles of Economics: Experimental Evidence," The American Economist, Sage Publications, vol. 66(1), pages 29-45, March.
    2. Büchele, Stefan, 2020. "Should we trust math preparatory courses? An empirical analysis on the impact of students’ participation and attendance on short- and medium-term effects," Economic Analysis and Policy, Elsevier, vol. 66(C), pages 154-167.
    3. Carlos Arias & Javier Valbuena & Jose Manuel Garcia, 2021. "The Impact of Secondary Education Choices on Mathematical Performance in University: The Role of Non-Cognitive Skills," Mathematics, MDPI, vol. 9(21), pages 1-16, October.
    4. Carlos J. Asarta & Roger B. Butters & Andrew Perumal, 2013. "Success in Economics Major: Is it Path Dependent?," Working Papers 13-11, University of Delaware, Department of Economics.
    5. Ann L. Owen, 2011. "Student Characteristics, Behavior, and Performance in Economics Classes," Chapters, in: Gail M. Hoyt & KimMarie McGoldrick (ed.), International Handbook on Teaching and Learning Economics, chapter 32, Edward Elgar Publishing.
    6. Girijasankar Mallik & John Lodewijks, 2010. "Student Performance in a Large First Year Economics Subject: Which Variables are Significant?," Economic Papers, The Economic Society of Australia, vol. 29(1), pages 80-86, March.
    7. Maria Paola & Vincenzo Scoppa, 2014. "The effectiveness of remedial courses in Italy: a fuzzy regression discontinuity design," Journal of Population Economics, Springer;European Society for Population Economics, vol. 27(2), pages 365-386, April.
    8. Stefan Buechele, 2018. "Bridging the Gap - how Effective are Remedial Math Courses in Germany?," MAGKS Papers on Economics 201825, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    9. Juan J. Dolado & Eduardo Morales, 2009. "Which factors determine academic performance of Economics freshers? Some Spanish evidence," Investigaciones Economicas, Fundación SEPI, vol. 33(2), pages 179-210, May.
    10. Ivo J. M. Arnold & Jerry T. Straten, 2012. "Motivation and Math Skills as Determinants of First-Year Performance in Economics," The Journal of Economic Education, Taylor & Francis Journals, vol. 43(1), pages 33-47, January.
    11. Leiv Opstad, 2023. "The Relationship Between Norwegian Business Students’ Attitudes Towards Mathematics And Success In Business Education," International Journal of Teaching and Education, European Research Center, vol. 11(1), pages 47-60, December.
    12. Dino Alves & Ana Balcao Reis & Carmo Seabra & Luis Catela-Nunes, 2015. "Determinants of Academic Success in Economics and Management," Investigaciones de Economía de la Educación volume 10, in: Marta Rahona López & Jennifer Graves (ed.), Investigaciones de Economía de la Educación 10, edition 1, volume 10, chapter 17, pages 335-356, Asociación de Economía de la Educación.
    13. Stefan Buechele, 2019. "Should We Trust Math Preparatory Courses? An Empirical Analysis on the Impact of Students' Participation and Attendance on Short- and Medium-Term Effects," MAGKS Papers on Economics 201927, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    14. Elena Moreno-García & Arturo García-Santillán & Némesis Larracilla Salazar & Milka Elena Escalera-Chávez, 2019. "Anxiety about Mathematics among Economics Students in Mexico," Mathematics, MDPI, vol. 7(5), pages 1-12, May.
    15. Ivo J. M. Arnold & Wietske Rowaan, 2014. "First-Year Study Success in Economics and Econometrics: The Role of Gender, Motivation, and Math Skills," The Journal of Economic Education, Taylor & Francis Journals, vol. 45(1), pages 25-35, March.
    16. Tasnádi, Attila & Kánnai, Zoltán & Pintér, Miklós, 2010. "Matematikaoktatás a bolognai típusú gazdasági képzésekben [Maths instruction in Bologna-type economics tuition]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(3), pages 261-277.

    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. Chowdhury, Biplob & Jeyasreedharan, Nagaratnam & Dungey, Mardi, 2018. "Quantile relationships between standard, diffusion and jump betas across Japanese banks," Journal of Asian Economics, Elsevier, vol. 59(C), pages 29-47.
    2. Bekkerman, Anton & Brester, Gary W. & McDonald, Tyrel J., 2013. "A Semiparametric Approach to Analyzing Differentiated Agricultural Products," Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 45(1), pages 79-94, February.
    3. Sheng-Tung Chen & Hsiao-I. Kuo & Chi-Chung Chen, 2012. "Estimating the extreme behaviors of students performance using quantile regression -- evidences from Taiwan," Education Economics, Taylor & Francis Journals, vol. 20(1), pages 93-113, December.
    4. Crambes, Christophe & Gannoun, Ali & Henchiri, Yousri, 2013. "Support vector machine quantile regression approach for functional data: Simulation and application studies," Journal of Multivariate Analysis, Elsevier, vol. 121(C), pages 50-68.
    5. Cristina Davino & Vincenzo Esposito Vinzi, 2016. "Quantile composite-based path modeling," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 10(4), pages 491-520, December.
    6. Ann L. Owen, 2011. "Student Characteristics, Behavior, and Performance in Economics Classes," Chapters, in: Gail M. Hoyt & KimMarie McGoldrick (ed.), International Handbook on Teaching and Learning Economics, chapter 32, Edward Elgar Publishing.
    7. Bouhlila, Donia Smaali, 2015. "The Heyneman–Loxley effect revisited in the Middle East and North Africa: Analysis using TIMSS 2007 database," International Journal of Educational Development, Elsevier, vol. 42(C), pages 85-95.
    8. Mallik, Girijasankar & Shankar, Sriram, 2016. "Does prior knowledge of economics and higher level mathematics improve student learning in principles of economics?," Economic Analysis and Policy, Elsevier, vol. 49(C), pages 66-73.
    9. Muller, Christophe, 2018. "Heterogeneity and nonconstant effect in two-stage quantile regression," Econometrics and Statistics, Elsevier, vol. 8(C), pages 3-12.
    10. Jean-Marc Fournier & Isabell Koske, 2012. "The determinants of earnings inequality: evidence from quantile regressions," OECD Journal: Economic Studies, OECD Publishing, vol. 2012(1), pages 7-36.
    11. Jamal Bouoiyour & Refk Selmi, 2017. "The Bitcoin price formation: Beyond the fundamental sources," Working Papers hal-01548710, HAL.
    12. Wiji Arulampalam & Alison Booth & Mark Bryan, 2010. "Are there asymmetries in the effects of training on the conditional male wage distribution?," Journal of Population Economics, Springer;European Society for Population Economics, vol. 23(1), pages 251-272, January.
    13. Arribas Ivan & Perez Francisco & Tortosa-Ausina Emili, 2010. "The Determinants of International Financial Integration Revisited: The Role of Networks and Geographic Neutrality," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 15(1), pages 1-55, December.
    14. Marrocu, Emanuela & Paci, Raffaele & Zara, Andrea, 2015. "Micro-economic determinants of tourist expenditure: A quantile regression approach," Tourism Management, Elsevier, vol. 50(C), pages 13-30.
    15. Jiang, Rong & Qian, Weimin & Zhou, Zhangong, 2012. "Variable selection and coefficient estimation via composite quantile regression with randomly censored data," Statistics & Probability Letters, Elsevier, vol. 82(2), pages 308-317.
    16. Gabrieli, T. & Galvao Jr, A. F. & Montes-Rojas, G., 2010. "Who benefits from reducing the cost of formality? Quantile regression discontinuity analysis," Working Papers 10/07, Department of Economics, City University London.
    17. Chen, Zhao & Cheng, Vivian Xinyi & Liu, Xu, 2024. "Reprint: Hypothesis testing on high dimensional quantile regression," Journal of Econometrics, Elsevier, vol. 239(2).
    18. Micheline Goedhuys & Leo Sleuwaegen, 2010. "High-growth entrepreneurial firms in Africa: a quantile regression approach," Small Business Economics, Springer, vol. 34(1), pages 31-51, January.
    19. Luke B. Smith & Brian J. Reich & Amy H. Herring & Peter H. Langlois & Montserrat Fuentes, 2015. "Multilevel quantile function modeling with application to birth outcomes," Biometrics, The International Biometric Society, vol. 71(2), pages 508-519, June.
    20. Arulampalam, Wiji & Naylor, Robin A. & Smith, Jeremy, 2012. "Am I missing something? The effects of absence from class on student performance," Economics of Education Review, Elsevier, vol. 31(4), pages 363-375.

    More about this item

    JEL classification:

    • A22 - General Economics and Teaching - - Economic Education and Teaching of Economics - - - Undergraduate
    • I20 - Health, Education, and Welfare - - Education - - - General

    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:taf:jeduce:v:40:y:2009:i:2:p:115-137. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/VECE20 .

    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.