Main Article Content


Although the mathematics foundation program was introduced in Sultan Qaboos University (SQU) half a decade ago, there has been no evaluation or assessment of the program. The aim of this study was to evaluate the students’ performance in the Mathematics foundation course in SQU and to examine the predictive value of  a student’s high school performance for success in the math foundation course. The study considered a sample of 551 students who took the math course (MATH2107) during 2014 Spring semester. More than 95% of the students were admitted to SQU with a high school score of 80 and above.  The analysis revealed that, in general, female students were admitted to SQU with a significantly higher average high school score than the male students. The findings indicate a very unsatisfactory performance of the students in the mathematics foundation course as the mean GPA was 1.66 and more than half (59%) of the students obtained a GPA less than 2 (i.e. below grade C), of which 14% failed and 35% obtained grade D. Female students outperformed male students in the mathematics course. High school mathematics performance, gender and cohort of students were identified as significant predictors of success in the mathematics foundation course.  To increase the success rate of the mathematics course, the high school curriculum needs to be aligned with the University standards and the admission authority should continue to give more attention to high school mathematics scores along with overall high school performance while making admission decisions for the College of Science in SQU.


Predict Foundation High school score Sultan Qaboos University Oman.

Article Details


  1. Schofer, E. and Meyer. Journal of the worldwide expansion of higher education in the twentieth century. American Sociological Review, 2005, 70, 898-920.
  2. Clancy, P. Measuring access and equity from a comparative perspective. In: Eggins, H. (Ed.). Access and Equity: Comparative Perspectives. Rotterdam: Sense Publishers, 2010, 69-102.
  3. Altbach, P.G. and Knight. Journal of the internationalization of higher education: Motivation and realities. Journal of Studies in International Education, 2007, 11(3), 290-305.
  4. Hourigan, M. and O‘Donoghue. Journal Mathematical under-preparedness: The influence of the pre-tertiary mathematics experience on students’ ability to make a successful transition to tertiary level mathematics courses in Ireland. International Journal of Mathematics Education in Science and Technology, 2007, 38(4), 461-476.
  5. Rylands, L. and Coady, C. Performance of students with weak mathematics in first-year mathematics and science. International Journal of Mathematical Education in Science and Technology, 2009, 40(6), 741-753.
  6. Al-Ghanboosi, S.S. and Ayedh, A.A.A. Student dropout trends at Sultan Qaboos University and Kuwait University: 2000-2011. College Student Journal, 2013, 47, 499-506.
  7. Oman Accreditation Council. Quality Audit Manual-Institutional Accreditation: Stage 1. Sultanate of Oman: Oman Accreditation Council. Ministry of Information #2008/87, 2008. Also available online
  8. at
  9. Carroll, M.I., Razvi. S. and Goodliffe, T. Using foundation program academic standards as a quality enhancement tool, a paper for INQAAHE, 2009.
  10. Al-Mamari, A.S. General Foundation Program in Higher Education Institutions in Oman National Standards: Implementation and Challenges. Paper presented in the Oman Quality Network Regional Conference 20-21 February, 2012, Ministry of Higher Education, Muscat.
  11. Travers, R.M.W. Significant research on the prediction of academic success. In W.T. Donahue, C.H. Coomb, and R.M.W. Travers (eds.), The Measurement of Student Adjustment and Achievement, 1949, pp. 147–190. Ann Arbor: University of Michigan Press.
  12. Fishman, J.A. Supplement to College Board Scores, No. 2. New York: College Entrance Examination Board, 1957.
  13. Cabrera, A.F., Nora, A. and Castan˜eda, M.B. College persistence: structural modeling of an integrated model of student retention. Journal of Higher Education, 1993, 64, 123–139.
  14. Wolfe, R.N. and Johnson S.D. Personality as a predictor of college performance. Educational and Psychological Measurement, 1995, 55(2), 177-185.
  15. Eimers, M.T. and Pike, G.R. Minority and nonminority adjustment to college: differences or similarities? Research in Higher Education, 1997, 38, 77–97.
  16. Noble, J. and Sawyer, R. Alternative methods for validating admission and course placement criteria. AIR Professional File, No., 1997, 63, 1–9.
  17. Adelman, C. Answers in the tool box: Academic intensity, attendance patterns, and bachelor’s degree attainment. Washington, DC: U.S. Department of Education, Office of Educational Research and Improvement, 1999.
  18. Bridgeman, B., McCamley-Jenkins, L., and Ervin, N. Predictions of freshman grade point average from the revised and recentered SAT I: Reasoning Test (College Board Rep. No. 2000-1). New York: College Entrance Examination Board, 2000.
  19. Snyder, V., Hackett, R.K., Stewart, M. and Smith, D. Predicting academic performance and retention of private university freshmen in need of developmental education. Research and Teaching in Developmental Education, 2003, 19(2), 17-28.
  20. Cohn, E., Cohn, S., Balch, D. and Bradley, J. Determinants of undergraduate GPAs: SAT scores, high-school GPA and high-school rank. Economics of Education Review, 23, 577-586.
  21., 2004
  22. Pentages, T.J. and Creedon, C.F. Studies of college attrition: 1950-1975. Review of Educational Research, 1978, 48, 49-101.
  23. Kappe, R. and Flier, H.V.D. Predicting academic success in higher education: what’s more important than being smart? European Journal of Psychology of Education, 2012, 27(4), 605-619.
  24. Clercq, M.D., Galand, B., Dupont, S. and Frenay, M. Achievement among first-year university students: an integrated and contextualized approach. European Journal of Psychology of Education, 2013, 28(3), 641-662.
  25. Islam, M.M. and Al-Ghasani, A. Predicting college math success: do high school performance and gender matter? evidence from Sultan Qaboos University in Oman. International Journal of Higher Education, 2015, 4(2), 67-80.
  26. Kowarsky, J., Clatfelter, D. and Widaman, K. Predicting university grade-point average in a class of University of California freshmen: an assessment of the validity of GPA and test scores as indicators of future academic performance. Institutional research paper. Oakland, CA: University of California Office of the President, 1998.
  27. Betts, J.R. and Morrell, D. The determinants of undergraduate grade point average. Journal of Human Resources, 1999, 34(2), 268-293.
  28. Camara, W.J. and Echternacht, G. The SAT[R] I and High School Grades: Utility in Predicting Success in College. (Report No. CB-RN-10). New York, NY: College Entrance Examination Board, 2000.
  29. Fleming, J. Who will succeed in college? When the SAT predicts black students’ performance. Review of Higher Education, 2002, 25(3), 281-296.
  30. Zheng, J.L., Saunders, K.P., Shelley II, M.C. and Whalen, D.F. Predictors of academic success for freshmen residence hall students. Journal of College Student Development, 2002, 43(2), 267-283.
  31. Geiser, S. and Santelices, M.V. Validity of high-school grades in predicting student success beyond the freshman year: high-school record vs. standardized tests as indicators of four-year college outcomes. University of California, Berkeley, 2007.
  32. Pascarella, E.T. and Terenzini, P.T. How College Affects Students: Findings and Insights from Twenty Years of Research. San Francisco: Jossey-Bass, 1991.
  33. Lee, V.E., Bryk, A.S. and Smith, J.B. The organization of effective secondary schools. In L. Darling-Hammond (ed.), Review of Research in Education, 1993, 19, 171-267.
  34. Wilhite, P., Windham, B. and Munday, R. Predictive effects of high school calculus and other variables on achievement in fist-semester college calculus course. College Student Journal, 1998, 32(4), 610-618.
  35. Williford, L.E. The freshman year: How do personal factors influence academic success and persistence? 1996 SAIR Annual Report: Charting the Course in a Changing Environment. Mobile, AL: Southern Association for Institutional Research and Southern Region of the Society for College and University Planning, 1996.
  36. Schneider, B.L., Kirst, M. and Hess, F.M. Strategies for success: high school and beyond. Brookings Papers on Education Policy, 2003, 6, 55-93.
  37. Adelman, C., Daniel, B. and Berkovits, I. Postsecondary attainment, attendance, curriculum, and performance: Selected results from the NELS:88/2000 postsecondary education transcript study (PETS), 2003.
  38. Adelman, C. The toolbox revisited: paths to degree completion from high school through college. Washington, DC: U.S. Department of Education, 2006. Retrieved from
  39. toolbox.pdf
  40. Russell, Bertrand. A History of Western Philosophy, George Allen and Unwin Ltd., London 1945, ISBN 0-415-32505-6, 1945.
  41. Bressoud, D.M. Why do we teach calculus? American Mathematical Monthly, 1992, 99, 615-617.
  42. Pearson, K. On a new method for determining the correlation between a measured character A, and a character B, Biometrika, 1909, 7, 96-105.
  43. Islam, M.M. Factors influencing the academic performance of undergraduate students in Sultan Qaboos University in Oman. Journal of Emerging Trends in Educational Research and Policy Studies, 2014, 5(4), 396-404.
  44. Azen, R., Bronner, S. and Gafni, N. Examination of gender bias in university admissions. Applied Measurement in Education, 2002, 15, 75-94.
  45. Chambers, E.A. and Schreiber, J.B. Girl’s academic achievement: varying associations of extracurricular activities. Gender and Education, 2004, 16(3), 327-346.
  46. Van Houtte, M. Why boys achieve less at school than girls: The difference between boys' and girls' academic culture. Educational Studies, 2004, 30, 159-173.
  47. Bourquin, S.D. The relationship among math anxiety, math self-efficacy, gender, and math achievement among college students at an open admissions commuter institution. Dissertation Abstracts International, Section A. Humanities and Social Sciences, 1999, 60(3-A), 0679.
  48. Kuncel, N.R., Credé, M. and Thomas, L.L. A comprehensive meta-analysis of the predictive validity of the Graduate Management Admission Test (GMAT) and undergraduate grade point average (UGPA). Academy of Management Learning and Education , 2007, 6, 51-68.
  49. Ma, X. A longitudinal assessment of antecedent course work in mathematics and subsequent mathematical attainment, The Journal of Educational Research. 2000, 94(1), 16-28.