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Prabandhan: Indian Journal of Management

ISSN: 0975-2854 Frequency: Monthly Peer Review: Double-blind Published since: 2008 Language: English
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Investigating Report Cards to Predict the Academic Performance of New MBA Students

Open Access Original Article

Investigating Report Cards to Predict the Academic Performance of New MBA Students

Amitabh Mishra1,  Ankur Agrawal2

1 Associate Professor, University School of Business, Chandigarh University, Gharuan, Mohali - 140 413, Punjab

2 Assistant Professor, Sharda School of Business Studies (SSBS), Sharda University, Gr. Noida - 201 310, Uttar Pradesh

Volume 15
Issue 3
Pages 8–23
Year 2022
Received: June 15, 2021 Accepted: Feb. 20, 2022 Published: March 16, 2022
Abstract

Report cards not only attest to students’ academic performance in a program, but they also contain several valuable insights. The study was based on the analysis of information readily available on the report cards of MBA Ist semester students. Report cards of 1,301 students enrolled in Dr. APJ Abdul Kalam Technical University, India (Asia’s largest affiliating University) affiliated institutions were examined. The study identified two types of courses: quantitative courses and non-quantitative courses. Furthermore, students’ performance varied significantly between categories, and quantitative courses were more difficult to score than non-quantitative courses. Decision models capable of predicting ‘overall academic performance’ were developed using multiple linear regression analysis. Report cards were used to collect data on the dependent variable (overall academic performance) and five predictor variables (gender, ethnicity, and students’ performance in three quantitative courses, namely managerial economics, business statistics, and business accounting). Finally, the study discovered that the predictor variable ‘AGP in Managerial Economics’ had the most significant impact on overall academic performance. Then came ‘AGP in Business Statistics,’ ‘AGP in Business Accounting,’ and the gender of the students.

Keywords Academic Performance Quantitative Courses Gender Ethnicity AGP (average Grade Points) SGPA (Semester Grade Point Average)
How to Cite

Amitabh Mishra, Ankur Agrawal (2022). Investigating Report Cards to Predict the Academic Performance of New MBA Students. Prabandhan: Indian Journal of Management, 15(3), 8–23. https://doi.org/10.17010/pijom/2022/v15i3/168846

References
  1. Arnold, I. J., & Straten, J.T. (2012). Motivation and math skills as determinants of first-year performance in economics. The Journal of Economic Education, 43(1), 33–47. https://doi.org/10.1080/00220485.2012.636709
  2. Baird, K., & Munir, R. (2015). The effectiveness of workshop (cooperative learning) based seminars. Asian Review of Accounting, 23(3), 293–312. https://doi.org/10.1108/ARA-03-2014-0038
  3. Broker, T., Milkman, M., & Raj, V. (2014). How do instructor's attendance policies influence student achievement in principles of microeconomics? Journal of Economic and Economic Education Research, 15(3), 13–23.
  4. Chan, S. W., & Ismail, Z. (2014). A technology-based statistical reasoning assessment tool in descriptive statistics for secondary school
  5. students. Turkish Online Journal of Educational Technology - TOJET, 13(1), 29–46.
  6. Christensen, D. G., Nancy, W. R., & White, D. E. (2012). Academic performance in MBA programs: Do prerequisites really matter? Journal of Education for Business, 87(1), 42–47. https://doi.org/10.1080/08832323.2011.555790
  7. Cordis, A. S., & Pierce, B. G. (2017). The impact of class scheduling on academic performance in quantitative and qualitative business disciplines. Global Perspectives on Accounting Education, 14(1), 44–66.
  8. De Jager, E., & Bitzer, E. (2013). First-year students' participation and performance in a financial accounting support group. International Business & Economics Research Journal, 12(4), 399–414. https://doi.org/10.19030/iber.v12i4.7739
  9. D'Souza, K. A., & Maheshwari, S. K. (2011). Predicting and monitoring student performance in the introductory management science course. Academy of Educational Leadership Journal, 15(2), 69–80.
  10. Duggal, M., & Mehta, P. (2015). Antecedents to academic performance of college students: An empirical investigation. Paradigm, 19(2), 197–211. https://doi.org/10.1177%2F0971890715609992
  11. Epstein, R. H., Clinton, M. S., Gabrovska, K., & Petrenko, O. (2013). Changes in motivation during an MBA program: Gender makes a difference from first-year to graduation. Academy of Educational Leadership Journal, 17(2), 103–120.
  12. Estelami, H. (2014). Determining the drivers of student performance in online business courses. American Journal of Business Education (Online), 7(1), 79–92. https://doi.org/10.19030/ajbe.v7i1.8321
  13. Fallan, L., & Opstad, L. (2014). Beyond gender performance in accounting: Does personality distinction matter? Accounting Education, 23(4), 343–361. https://doi.org/10.1080/09639284.2014.930693
  14. Fogarty, T. J., & Goldwater, P. M. (2010). Beyond just desserts: The gendered nature of the connection between effort and achievement for accounting students. Journal of Accounting Education, 28(1), 1–12.
  15. Gougeon, D. J. (2016). Analysis of student perceptions in an introductory business statistics course. Journal of the Northeastern Association of Business, Economics and Technology, 19(1), 1– 8.
  16. Guidry, K. (2013). Predictors of student success in online courses : Quantitative versus qualitative subject matter. Journal of Instructional Pedagogies, 10(4), 1–11.
  17. Guney, Y. (2009). Exogenous and endogenous factors influencing students' performance in undergraduate accounting modules. Accounting Education: An International Journal, 18(1), 51–73. https://doi.org/10.1080/09639280701740142
  18. Gupta, K., & Maksy, M. M. (2014). Factors associated with student performance in an investments course: An empirical study. Journal of Finance and Accountancy, 16, 1– 26.
  19. Harsolekar, D. D., & Munshi, J. (2018). An empirical analysis of the perception of management students about their employment. Prabandhan: Indian Journal of Management, 11(9), 21–37. https://doi.org/10.17010/pijom/2018/v11i9/131613
  20. Hettler, P. L. (2015). Student demographics and the impact of team-based learning. International Advances in Economic Research, 21(4), 413–422.
  21. Irfan, S. M., Awan, M., Saman, S., & Hakeem, R. (2012). An empirical investigation of student's poor performance in quantitative subjects: A case study of management students from Pakistan. Sci. Int. (Lahore), 24(4), 487– 494.
  22. Kass, D., Christian, G., & Bommer, W. (2012). The GMAT as a predictor of MBA performance : Less success than meets the eye. Journal of Education for Business, 87(5), 290–295. https://doi.org/10.1080/08832323.2011.623196
  23. Katsikas, E., & Panagiotidis, T. (2010). Student status and academic performance: An approach of the quality determinants of university studies in Greece. Hellenic Observatory papers on Greece and Southeast Europe (GreeSE paper no. 40). London School of Economics and Political Science, London, UK.
  24. Kohli, A. S., Peng, C., Mittal, M. S. (2011). Predictors of student success in undergraduate business statistics course. Journal of the Academy of Business and Economics, 11, 32–42.
  25. Kumar, D. P., Subbarayudu, Y., & Nagaraju, E. (2019). Employability skills of management graduates: The comparative status of SC/ST students in Andhra Pradesh. Prabandhan: Indian Journal of Management, 12(3), 50–61. https://doi.org/10.17010/pijom/2019/v12i3/142340
  26. Mishra, A. (2018). Investigating few presumptions regarding the academic performance of students: A study on MBA scholars in Knowledge Park, Greater Noida. Prabandhan: Indian Journal of Management 11(11), 37–50. https://doi.org/10.17010/pijom/2018/v11i11/138208
  27. Nalukenge, B., Wamala, R., & Ocaya, B. (2016). Do prior studies matter? Predicting proficiencies required to excel academically in Law School at Makerere University, Uganda. Quality Assurance in Education, 24(1), 139–154. https://doi.org/10.1108/QAE-09-2013-0038
  28. Nema, G., & Kasliwal, K. (2018). The impact of integrated marketing communication (IMC) tools on learning in B-schools: A study. Prabandhan: Indian Journal of Management, 11(5), 42–54. https://doi.org/10.17010/pijom/2018/v11i5/123813
  29. Opstad, L. (2018). Success in business studies and mathematical background: The case of Norway. Journal of Applied Research in Higher Education, 10(3), 399–408. https://doi.org/10.1108/JARHE-11-2017-0136
  30. Phang, M. M., Johl, S. K., & Cooper, B. J. (2014). Goal-efficacy framework: An examination of domestic and international accounting students' academic performance. Accounting and Finance, 54(4), 1295–1318.
  31. Prathiba, S. (2020). A study on professors' adeptness and students' expectations on perceived student learning outcomes. Prabandhan: Indian Journal of Management, 13(1), 19–32. https://doi.org/10.17010/pijom/2020/v13i1/149945
  32. Preet, K., & Ahluwalia, A. K. (2019). Factors of stress amongst students of professional institutes. Prabandhan: Indian Journal of Management, 12(6), 31–40. https://doi.org/10.17010/pijom/2019/v12i6/144934
  33. Rahal, A., & Zainuba, M. (2016). Improving students' performance in quantitative courses: The case of academic motivation and predictive analytics. The International Journal of Management Education, 14(1), 8–17. https://doi.org/10.1016/j.ijme.2015.11.003
  34. Rath, N., & Kar, N. (2012). Attendance in classes and examination outcome in management students: Exploring the association. Journal of Organization and Human Behaviour, 1(4), 58–62.
  35. Rienties, B., Beausaert, S., Grohnert, T., Niemantsverdriet, S., & Kommers, P. (2012). Understanding academic performance of international students: The role of ethnicity, academic and social integration. Higher Education, 63(6), 685–700. https://doi.org/10.1007/s10734-011-9468-1
  36. Rudranath, P. G. (2013). Impact of self-concept achievement motivation on academic achievements of MBA students: An empirical analysis. Prabandhan: Indian Journal of Management, 6(10), 36–48. https://doi.org/10.17010/pijom/2013/v6i10/60038
  37. Russo, C. J., & Kaynama, S. (2012). The impact of personality type and gender on students' performance in a business capstone course. Academy of Educational Leadership Journal, 16(1), 49–67.
  38. Schlee, R. P., & Harich, K. R. (2014). Teaching creativity to business students: How well are we doing? Journal of Education for Business, 89(3), 133–141. https://doi.org/10.1080/08832323.2013.781987
  39. Simmons, G. R. (2014). Business statistics: A comparison of student performance in three learning modes. Journal of Education for Business, 89(4), 186–195. https://doi.org/10.1080/08832323.2013.836470
  40. Singh, S., Misra, R., & Srivastava, S. (2017). An empirical investigation of student's motivation towards learning quantitative courses. The International Journal of Management Education, 15(2), 47–59. https://doi.org/10.1016/j.ijme.2017.05.001
  41. Ujar, A., & Gϋngörmus, A. H. (2011). Factors associated with student performance in financial accounting courses. European Journal Economics and Political Studies, 2, 141–156.
  42. Yousef, D. A. (2012). Factors affecting academic performance of non-English speaking business students in quantitative courses: A study at a private university in the UAE. Journal of International Business Education, 7, 103–120.
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