IDEAS home Printed from https://ideas.repec.org/a/bla/acctfi/v46y2006i5p697-713.html
   My bibliography  Save this article

Australian evidence on student expectations and perceptions of introductory business finance

Author

Listed:
  • Balasingham Balachandran
  • Michael Skully
  • Kevin Tant
  • John Watson

Abstract

This study examines the differences in perceptions and expectations between students at the Caulfield and Peninsula campuses of Monash University with different entrance criteria and degree availability to determine whether two different introductory finance subjects should be offered rather than one. Results reported in this study suggest that students at the Caulfield campus are interested in studying a challenging introductory finance subject, whereas students at the Peninsula campus perceived that introductory finance is ‘difficult’. Capital structure and cost of capital topics are statistically significantly ranked higher by Caulfield students than Peninsula students. The results reported in this study revealed that two different introductory finance subjects would be more effective. The core subject at the finance major campus (Caulfield) follows a traditional structure with more emphasis on finance theory, whereas the new subject at the non‐finance campus (Peninsula) places greater emphasis on applications.

Suggested Citation

  • Balasingham Balachandran & Michael Skully & Kevin Tant & John Watson, 2006. "Australian evidence on student expectations and perceptions of introductory business finance," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 46(5), pages 697-713, December.
  • Handle: RePEc:bla:acctfi:v:46:y:2006:i:5:p:697-713
    DOI: 10.1111/j.1467-629X.2006.00193.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1467-629X.2006.00193.x
    Download Restriction: no

    File URL: https://libkey.io/10.1111/j.1467-629X.2006.00193.x?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. Rosina Mladenovic, 2000. "An investigation into ways of challenging introductory accounting students' negative perceptions of accounting," Accounting Education, Taylor & Francis Journals, vol. 9(2), pages 135-155.
    2. John Marangos, 2002. "How University Students Were Planning To Study Introductory Microeconomics? Were Their Study Plans Realised?," Economic Papers, The Economic Society of Australia, vol. 21(2), pages 45-60, June.
    3. Paul Azzalini & Sandra Hopkins, 2002. "What Business Students Think Of Economics: Results From A Survey Of Second Year Students," Economic Papers, The Economic Society of Australia, vol. 21(1), pages 11-17, March.
    4. Andrew Worthington & Helen Higgs, 2003. "Factors explaining the choice of a finance major: the role of students' characteristics, personality and perceptions of the profession," Accounting Education, Taylor & Francis Journals, vol. 12(3), pages 261-281.
    5. Eisenbeis, Robert A, 1977. "Pitfalls in the Application of Discriminant Analysis in Business, Finance, and Economics," Journal of Finance, American Finance Association, vol. 32(3), pages 875-900, June.
    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. Tiffany Hutcheson & Harry Tse, 2004. "Learning by Students at University," Working Paper Series 136, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
    2. Premachandra, I.M. & Bhabra, Gurmeet Singh & Sueyoshi, Toshiyuki, 2009. "DEA as a tool for bankruptcy assessment: A comparative study with logistic regression technique," European Journal of Operational Research, Elsevier, vol. 193(2), pages 412-424, March.
    3. Montgomery, D. & Swinnen, G. & Vanhoof, K., 1997. "Comparison of some AI and statistical classification methods for a marketing case," European Journal of Operational Research, Elsevier, vol. 103(2), pages 312-325, December.
    4. Dimitras, A. I. & Slowinski, R. & Susmaga, R. & Zopounidis, C., 1999. "Business failure prediction using rough sets," European Journal of Operational Research, Elsevier, vol. 114(2), pages 263-280, April.
    5. Lin, Hsiou-Wei William & Lo, Huai-Chun & Wu, Ruei-Shian, 2016. "Modeling default prediction with earnings management," Pacific-Basin Finance Journal, Elsevier, vol. 40(PB), pages 306-322.
    6. Veres Ferrer, Ernesto Jesús & Labatut Serer, Gregorio & Pozuelo Campillo, Jose, 2009. "Hacia una ordenación de las pequeñas empresas atendiendo a su posible situación de fracaso/Towards a Ranking of Smaller Companies According to Their Failure Risk," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 27, pages 775(18á)-77, Diciembre.
    7. Patrick Boisselier & Dominique Dufour, 2003. "Scoring Et Anticipation De Defaillance Des Entreprises : Une Approche Par La Regression Logistique," Post-Print halshs-00582740, HAL.
    8. Adriana Csikosova & Maria Janoskova & Katarina Culkova, 2020. "Application of Discriminant Analysis for Avoiding the Risk of Quarry Operation Failure," Journal of Risk and Financial Management, MDPI, Open Access Journal, vol. 13(10), pages 1-14, September.
    9. Dorene Isenberg, 1989. "Financial Instability: A Recession Simulation on the U.S. Corporate Structure," Economics Working Paper Archive wp_24, Levy Economics Institute.
    10. Stephen Coetzee & Ruanda Oberholzer, 2010. "South African Career Guidance Counsellors' and Mathematics Teachers' Perception of the Accounting Profession," Accounting Education, Taylor & Francis Journals, vol. 19(5), pages 457-472.
    11. Lucas, Ursula & Meyer, Jan H.F., 2005. "‘Towards a mapping of the student world’: the identification of variation in students' conceptions of, and motivations to learn, introductory accounting," The British Accounting Review, Elsevier, vol. 37(2), pages 177-204.
    12. Krom, Cynthia L. & Williams, Satina V., 2011. "Tell me a story: Using creative writing in introductory accounting courses to enhance and assess student learning," Journal of Accounting Education, Elsevier, vol. 29(4), pages 234-249.
    13. Marek Vochozka, 2010. "Vývoj metod komplexního hodnocení výkonnosti podniku [Development of Methods for Comprehensive Evaluation of Business Performance]," Politická ekonomie, Prague University of Economics and Business, vol. 2010(5), pages 675-688.
    14. Dean Fantazzini & Silvia Figini, 2009. "Random Survival Forests Models for SME Credit Risk Measurement," Methodology and Computing in Applied Probability, Springer, vol. 11(1), pages 29-45, March.
    15. Youssef Zizi & Mohamed Oudgou & Abdeslam El Moudden, 2020. "Determinants and Predictors of SMEs’ Financial Failure: A Logistic Regression Approach," Risks, MDPI, Open Access Journal, vol. 8(4), pages 1-21, October.
    16. Kurt M. Fanning & Kenneth O. Cogger, 1994. "A Comparative Analysis of Artificial Neural Networks Using Financial Distress Prediction," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 3(4), pages 241-252, December.
    17. Duff, Angus & Mladenovic, Rosina, 2015. "Antecedents and consequences of accounting students' approaches to learning: A cluster analytic approach," The British Accounting Review, Elsevier, vol. 47(3), pages 321-338.
    18. Manjusha Senapathi & Saptarshi Ghosal, 2016. "Modelling Corporate Sector Distress in India," Working Papers id:11540, eSocialSciences.
    19. Dorene Isenberg, 1991. "Financial Instability: A Recession Simulation on the U.S. Corporate Structure," Eastern Economic Journal, Eastern Economic Association, vol. 17(2), pages 165-175, Apr-Jun.
    20. Larry G. Perry & Glenn V. Henderson Jr. & Timothy P. Cronan, 1984. "Multivariate Analysis Of Corporate Bond Ratings And Industry Classifications," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 7(1), pages 27-36, March.

    More about this item

    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:bla:acctfi:v:46:y:2006:i:5:p:697-713. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/aaanzea.html .

    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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/aaanzea.html .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.