The Effect of Math Ability and English Ability on Graduate Academic Performance Using Database of the International Private University
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Abstract
The purposes of this study are to examine the relationship between student demographics and Math ability and English ability; to examine the relationship between student academic background and Math ability and English ability; to examine the relationship between Math ability and English ability and graduate academic performance using database of the international private university. This study collected data of graduates from the database of the international private university to test hypotheses with three sets of data; the first set was combined from four graduate batches (batches 44-47), the second set was one latest batch (batch 47), and the third set was sample taking 10% from total four batches. Data were analyzed with multiple regression analysis, independent sample t-test, and one-way ANOVA. The results found that student demographics (gender, age, and nationality), and their academic background (types of school, math skills in high school, and majors) determined their Math ability and English ability, except types of high school on Math ability. In addition, both Math and English abilities also influenced graduate performance.
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References
Abadel, F. T., & Hattab, A. S. (2013). How Does the Medical Graduates' Self-Assessment of Their Clinical Competency Differ from Experts' Assessment? BMC Medical Education. 13(1): 24-32.
Academic Major. (2020). In Wikipedia. [Online]. Available: https://en.wikipedia.org/wiki/Academic_major.
Academic Performance. (2020). In Wikipedia. [Online]. Available: https://en.wikipedia.org/wiki/Academic_achievement
Adeboyel, A. O. (1999). Interesting Relationships Between Mathematics and Science. Journal of Mathematics and Science. 1(2): 22-29.
Alcock, J., Cockcroft, S., & Finn, F. (2008). Quantifying the Advantage of Secondary Mathematics Study for Accounting and Finance Undergraduates. Accounting & Finance. 48(5): 697-718.
Al-Rofo, M. (2010). The Dimensions That Affect the Students’ Low Accumulative Average in Tafila Technical
University. Journal of Social Sciences. 22(1): 53-59.
Andrews, R., Boyne, G. A., & Walker, R. M. (2006). Subjective and Objective Measures of Organizational Performance. Public Service Performance: Perspectives on Measurement and Management. 14-34.
Badru, A. K. (2004). Student Performance in Mathematics as Correlate of Their Performance in Chemistry. In 45th Annual Conference Proceedings Science Teachers Association of Nigeria (pp 35-40). Asaba, Nigeria, Science Teachers Association of Nigeria by Heinemann Educational Books.
Balart, P., & Oosterveen, M. (2019). Females Show More Sustained Performance During Test-Taking Than Males. Nature Communications. 10(1): 1-11.
Baloglu, M. (2003). Individual Differences in Statistics Anxiety Among College Students. Personality and Individual Differences. 34(5): 855–865.
Bernard, H., Drake, D. D., Paces, J. J., & Raynor, H. (1996). Student-Centered Educational Reform: The Impact of Parental and Educator Support of Student Diligence. The School Community Journal. 6(2): 9-25.
Blair, E., & Blair, J. (2015). Applied Survey Sampling. California: Sage Publications.
Brookshire, R. G., & Palocsay, S. W. (2005). Factors Contributing to The Success of Undergraduate Business Students in Management Science Courses. Decision Sciences Journal of Innovative Education. 3(1): 99-108.
Chen, P., & Zimmerman, B. (2007). A Cross-National Comparison Study on The Accuracy of Self-Efficacy Beliefs of Middle-School Mathematics Students. The Journal of Experimental Education. 75(3): 221-244.
Clarkson, P. C. (2007). Australian Vietnamese Students Learning Mathematics: High Ability Bilinguals and Their Use of Their Languages. Educational Studies in Mathematics. 64(2): 191-215.
Coll, R. K. (1996). The BSc (Technology) Degree: Responding to the Challenges of The Education Marketplace. Journal of Cooperative Education. 32: 29-35.
Cortina, J. M. (1993). What is Coefficient Alpha? An Examination of Theory and Applications. Journal of Applied Psychology. 78(1): 98-104.
Darling, N., Caldwell, L. L., & Smith, R. (2005). Participation in School-Based Extracurricular Activities and Adolescent Adjustment. Journal of Leisure Research. 37(1): 51-76.
Ebenuwa-Okoh, E. E. (2010). Influence of Age, Financial Status, And Gender on Academic Performance Among Undergraduates. Journal of Psychology. 1(2): 99-103.
Eddey, P., & Baumann, C. (2009). Graduate Business Education: Profiling Successful Students and Its Relevance for Marketing and Recruitment Policy. Journal of Education for Business. 84(3): 160-168.
Erdem, C., Şentürk, I., & Arslan, C. (2007). Factors Affecting Grade Point Average of University Students. The
Empirical Economics Letters. 6(5): 360-368.
Ervina, A., & Othman, M. N. (2005). Undergraduate Students’ Performance: The Case of University Malaya. Quality Assurance in Education. 13(4): 329-343.
Evans, W. N., & Schwab, R. M. (1995). Finishing High School and Starting College: Do Catholic Schools Make a Difference? The Quarterly Journal of Economics. 110(4): 941-974.
Feast, V. (2002). The Impact of IELTS Scores on Performance at University. International Education Journal. 3(4): 70-85.
Fornell, C. & Larcker, D.F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research. 18(1): 39-50.
Galli, S., Chiesi, F., & Primi, C. (2011). Measuring Mathematical Ability Needed For “Non-Mathematical” Majors: The Construction of a Scale Applying IRT And Differential Item Functioning Across Educational Contexts. Learning and Individual Differences. 21(4): 392-402.
Gu, L. (2015). Language Ability of Young English Language Learners: Definition, Configuration, and Implications. Language Testing. 32(1): 21-38.
Hagedorn, L. S., & Ren, J. (2012). International Graduate Students’ Academic Performance: What are the Influencing Factors? Journal of International Students. 2(23): 135-143.
Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2010). Multivariate Data Analysis. (7th ed). Upper Saddle River, New Jersey: Prentice Hall.
Harb, N., & El-Shaarawi, A. (2007). Factors Affecting Business Students' Performance: The Case of Students in United Arab Emirates. Journal of Education for Business. 82(5): 282-290.
Hartnett, N., Römcke, J., & Yap, C. (2004). Student Performance in Tertiary‐Level Accounting: An International Student Focus. Accounting & Finance. 44(2): 163-185.
Helm, F., Mueller-Kalthoff, H., Nagy, N., & Möller, J. (2016). Dimensional Comparison Theory: Perceived Subject Similarity Impacts on Students’ Self-Concepts. AERA Open. 2(2): 2332858416650624.
Hodges, D., & Burchell, N. (2003). Business Graduate Competencies: Employers' Views on Importance and Performance. International Journal of Work-Integrated Learning. 4(2): 16-22.
Hodgman, M. R. (2018). Employers Perspectives on The Performance of Higher Education Institutions in Preparing Graduates for The Workplace: A Review of The Literature. Business and Economic Research. 8(3): 92-103.
Jenkins, D. (2003). Wisconsin School Readiness Indicator Initiative: The Status of School Readiness Indicators in Wisconsin. [Online]. Available: ERIC database. (ED480807) https://dpi.wi.gov/sites/default/files/imce/early-childhood/pdf/Wisconsin%20School%20Readiness%20Indicator%20Initiative.pdf.
Junco, R., & Cotten, S. R. (2011). Perceived Academic Effects of Instant Messaging Use. Computers & Education. 56(2): 370–378.
Koh, M. Y., & Koh, H. C. (1999). The Determinants of Performance in An Accountancy Degree Program. Accounting Education: An International Journal. 8(1): 13–29.
Kovas, Y., Haworth, C. M., Petrill, S. A., & Plomin, R. (2007). Mathematical Ability of 10-Year-Old Boys and Girls: Genetic and Environmental Etiology of Typical and Low Performance. Journal of Learning Disabilities. 40(6): 554-567.
Kruck, S. K. S., & Lending, D. L. D. (2003). Predicting Academic Performance in an Introductory College Introductory College-Level IS Course Level IS Course. Information Technology, Learning, and Performance Journal. 21(2): 9-15.
Kerstjens, M., & Nery, C. (2000). Predictive Validity in The IELTS Test: A Study of The Relationship Between IELTS Scores and Students' Subsequent Academic Performance (Research report). International English Language Testing System (IELTS). 3: 85-108.
Lincove, J. & Painter, G. (2006). Does the Age That Children Start Kindergarten Matter? Evidence Of Long-Term Educational and Social Outcomes. Educational Evaluation and Policy Analysis. 28(2): 153-179.
Lipnevich, A. A., MacCann, C., Krumm, S., Burrus, J., & Roberts, R. D. (2011). Mathematics Attitudes and Mathematics Outcomes of US And Belarusian Middle School Students. Journal of Educational Psychology. 103(1): 105-118.
Martirosyan, N. M., Hwang, E., & Wanjohi, R. (2015). Impact of English Proficiency on Academic Performance of International Students. Journal of International Students. 5(1): 60-71.
Malgwi, C. A., Howe, M. A., & Burnaby, P. A. (2005). Influences on Students' Choice of College Major. Journal of Education for Business. 80(5): 275-282.
Nisbet, D. L., Tindall, E. R., & Arroyo, A. A. (2005). Language Learning Strategies and English Proficiency of Chinese University Students. Foreign Language Annals. 38(1): 100-107.
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.
Palmer, J. C., & Wright, R. E. (1996). Predicting Academic Performance in Graduate Business Programs; When Does Age Make a Difference? Delta Pi Epsilon Journal. 38(2): 72-80.
Pritchard, R. E., Potter, G. C., & Saccucci, M. S. (2004). The Selection of a Business Major: Elements Influencing Student Choice and Implications for Outcomes Assessment. Journal of Education for Business. 79(3): 152-156.
Rohr, S. L. (2012). How Well Does the SAT And GPA Predict the Retention of Science, Technology, Engineering, Mathematics, And Business Students. Journal of College Student Retention: Research, Theory & Practice. 14(2): 195-208.
Sheard, M. (2009). Hardiness Commitment, Gender, And Age Differentiate University Academic Performance. British Journal of Educational Psychology. 79(1): 189-204.
Steffens, M. C., & Jelenec, P. (2011). Separating Implicit Gender Stereotypes Regarding Math and Language: Implicit Ability Stereotypes Are Self-Serving for Boys and Men, But Not for Girls and Women. Sex Roles. 64(5-6): 324-335.
Tempelaar, D., Rienties, B., & Nguyen, Q. (2020). Subjective Data, Objective Data and The Role of Bias in Predictive Modelling: Lessons from A Dispositional Learning Analytics Application. PloS ONE. 15(6): 1-29 [Online]. Available: https://doi.org/10.1371/journal.pone.0233977
Udousoro, U. J. (2011). The Effects of Gender and Mathematics Ability on Academic Performance of Students in Chemistry. African Research Review. 5(4): 201-213.
Umarji, O., McPartlan, P., & Eccles, J. (2018). Patterns of Math and English Self-Concepts as Motivation for College Major Selection. Contemporary Educational Psychology. 53(April): 146-158.
Umoh, C. G. (2003). A Theoretical Analysis of The Effects of Gender and Family Education on Human Resource Development. Journal of Curriculum Organization of Nigeria. 10(1): 1-4.
Wally-Dima, L. & Mbekomiza, C. L. (2013). Causes of Gender Differences in Accounting Performance: Students’ Perspective. International Education Studies. 6(10): 13–26.
Yousef, D. A. (2011). Academic Performance of Business Students in Quantitative Courses: A Study in The Faculty of Business and Economics at the UAE University. Decision Sciences Journal of Innovative Education. 9(2): 255-267.