Factors Affecting or Predicting Student Performance - Research Paper Example

Factors that may affect or predict a performance in his degree program were investigated using a sample of 236 taking upManagement degree programs in various areas of specialization. Statistical tests and mathematical tools such as frequency count, descriptive statistics, correlation, chi square analysis, t test, and regression analysis were used to identify existing relationships and possible predictors of overall performance. Results indicate that demographics and prior maths education do not significantly affect overall performance. Rather, scores in each unit course significantly predict the overall performance of a student. Introduction For this study, the dependent variable was “First Year Performance” which was measured by taking the average of the grades received by the student from the courses he was taking. Independent variables were region, age, and gender. Region referred to the student’s place of study, and took the values of EU, OS, and UK. Age was divided into two values: regular (below 21 years old as of 1st September at the year of intake) and mature (below 21 years old as of 1st September at the year of intake). Gender took the values of Male and Female. Frequency count was used to find the number of respondents per category. In finding the relationship between continuous variables (e. g. scores), Pearson’s correlation techniques were used. In finding the relationship between categorical variables, cross tabulation and chi square tests were performed on the data. To investigate the effects of prior maths education on unit scores and overall performance, t test were conducted. Finally, to find out which variables predicted overall performance, regression analysis was performed. Presentation and Discussion of Results Demographic profile of respondents There were a total of 236 respondents surveyed for this study. Table 1 shows the country of origin of the respondents. Figures indicate that majority if the respondents are from the UK (36.4%), China (25.4%), and India (8.5%). In terms of the Program that the respondents are taking up, 36.4% are majoring in MSc (Hons) Management (n = 88), 26.3% in Marketing (n = 62), 16.1% in Accounting (n = 38), 12.3% in IBE (n = 29), 3.8% in Human Resources (n = 9), and 3.4% in IS (n = 8). There are 2 respondents each majoring in Decision Making and in Operations. Of the respondents surveyed, 53.8% are from the OS region (n = 127), 36.4% are from the UK region (n = 86), and 9.7% are from the EU region (n = 23). There were 87.3% of respondents who were considered regular students (n = 206), while 12.7% are mature students (n = 30). There were more female respondents in this study at 53.4% (n = 126) compared with male respondents at 46.6% (n = 110). Descriptive Statistics The primary interest of this study is the overall performance of students and the underlying factors that may predict overall performance. As such, it would be helpful to look into the descriptive characteristics of overall performance scores and the individual unit course scores (Anderson, Sweeney, & Williams, 2009). Figure 1 shows that the overall performance scores are skewed to the left, with higher concentration on the 50 to 70 range (Mean = 56.88, SD = 11.7). Table 2 reflects the mean scores of respondents in the different units. The figures indicate that students have the highest mean score in BMAN10001 (10) – Economic Principles: Microeconomics (Mean = 70.02, SD = 14.77) and the lowest mean scores in BMAN10621 (10) – Fundamentals of Financial Reporting. Table 1. Histogram of overall performance scores. Relationship between unit courses and overall performance Overall performance was measured by taking the average of a student’s unit courses. It is helpful to find out in this investigation which unit course affects overall performance most. Table 3 shows the correlation coefficients, Pearson’s r, between the unit courses and overall performance. The figures show that overall performance is most highly and positively correlated with BMAN10632(M) (10) - Fundamentals of Management Accounting, r = .862, p < .01. This means that 86.2% of the variances in overall performance may be significantly explained by a student’s BMAN10632 scores. The other units that are highly correlated with overall performance are BMAN10522(M) (10) - Financial Decision Making (M), BMAN10732 (10) - Quantitative Methods for Bus & Mgmt 2, and BMAN10002 (10) - Economic Principles : Macroeconomics, with coefficients of r = .833, p < .01, r = .818, p< .01, and r = .807, p < .01, respectively. On the other hand, the units that have the lowest correlation with overall performance are BMAN10780 (10) - Business & Management Skills and BMAN10791 (10) - People and Organisations, with coefficients of r = .473, p < .01, and r = .511, p < .01, respectively. Units that have low correlation with overall performance are those that do not particularly dictate a student’s overall performance scores (Tabak, 2004). It would seem that the unit courses that are highly correlated with overall performance are quantitative in nature. Thus, we will investigate later whether a previous math education, which may indicate an inclination towards higher quantitative familiarity, has any effect on a student’s overall performance. It is also helpful to look into the relationships of unit courses with each other. That is, which unit courses seem to be highly correlated with each other? Another importance of this portion of the investigation is that it allows us to identify and eventually eliminate courses that are highly correlated with each other when the data are subjected to a regression analysis. This is because one requirement of an effective regression analysis is that homoscedasticity must be avoided (Anderson, Sweeney, & Williams, 2009). That is, the independent variables that are highly correlated with each other must be removed from the analysis. It should first be noted that all the unit courses are positively and significantly correlated with each other at significant level of .05. Thus, higher scores in each of the units included in this study correspond to other high unit scores as well (Bluman, 2004). Moreover, the unit courses that are highly correlated with each other are BMAN10812 (10) - The Modern Corporation and BMAN10852 (10) - Management in Society, r = .815, p < .01. This means that these two unit courses may be eliminated from the regression analysis that will be performed on the data later on. It may be noted that these two unit courses are quite qualitative in nature and largely deals with the qualitative social science aspects of management and may thus explain the high correlation that they have with each other. On the other hand, unit courses that have the lowest correlation with each other are BMAN10621(M) (10) - Fundamentals of Financial Reporting and BMAN10780 (10) - Business & Management Skills, r = .197, p < .01, and BMAN10791 (10) - People and Organisations and BMAN10821 (10) - Quantitative Methods for B&M 1, r = .185, p < .04. It may be observed that the two pairs of unit courses that are least correlated with each other are such that one unit is highly quantitative in nature (e. g., BMAN10621 and BMAN10821) while the other is highly qualitative in nature (e. g. BMAN10780 and BMAN10791). This may point to an indication that students who perform well in quantitative unit courses do not perform as well in the qualitative unit courses of their degree programs (Bluman, 2004). Relationship between demographic characteristics and unit courses and overall performance Another significant consideration in this study is the relationship of the different demographic characteristics included in this investigation. A comparison of Figure 2 and Figure 3 indicates that male and female students are quite evenly distributed in terms of age. However, more female regular students come from OS than from the two other regions. Moreover, results from the chi-square tests found in Table 4 indicate that there are no significant relationships among the demographic characteristics of the respondents. Fig. 2. Distribution of males respondents (n = 110) Fig. 3 Distribution of female respondents (n = 126) Relationship between prior maths education and unit courses and overall performance It was earlier pointed out that students who performed well in quantitative elements of their degree programs, performed significantly better when overall performance was considered. Thus, it may bode well to investigate the relationship of prior maths education with unit courses and overall performance. Although there were a number of different maths education courses indicated in the data, they were all merged into two categories of No Prior Maths Education and With Prior Maths education since some categories had very few cases. T test was conducted on the data and results are found in Table 5. Findings indicate that a student’s prior maths education significantly affected test scores in BMAN10001 (10) - Economic Principles : Microeconomics, t(234) = 2.44, p = .02, BMAN10621(M) (10) - Fundamentals of Financial Reporting, t(229) = p = .02, and BMAN10852 (10) - Management in Society, t(107) = - 2.27, p = .03. Interestingly enough, those with no prior maths education (Mean = 72.47, SD = 13.62) scored higher in BMAN10001 than those with prior maths education (Mean = 67.85, SD = 15.45). Similarly, those with no prior maths education also scored higher (Mean = 49.27, SD = 20.05) in BMAN10621 than those with prior maths education (Mean = 43.21, SD = 19.37). On the contrary, those with prior maths education scored higher (Mean = 56.14, SD = 13.03) in BMAN10852 than those without prior maths education (Mean = 48.73, SD = 21.20). More importantly, prior maths education did not have a significant effect on overall performance of students. These findings seem to point to the indication that prior maths education is not an important determinant of a student’s overall success in his first year of education in the degree programs indicated (Anderson, Sweeney, & Williams, 2009). Predictors of overall performance After looking at the identified relationships between different variables and overall performance, we now find out through regression analysis which of the factors earlier identified predicted the level of success in the overall performance of a student. In particular, we will consider the unit courses (except BMAN10812 (10) - The Modern Corporation and BMAN10852 (10) - Management in Society) as possible predictors of Overall Performance. Results of regression analysis indicate that the predictors entered into the analysis have a very high correlation with overall performance as indicated by a Pearson’s coefficient of r = .997. Moreover, the regression equation is likewise highly significant, F(11, 155) = 2708.47, p < .01, with each of the unit courses being a significant predictor of overall performance at p < .01. (Complete figures found in Table 6.) Figure 4 shows a highly linear relationship between overall performance and the standardized predicted value. Figure 4. Scatterplot of overall performance scores vs standardized predicted value Finally, the regression equation may be given by: (Eqn 1) Y = .11X1 + .17X2 + .12X3 + .17X4 + .10X5 + .10X6 + .10X7 + .14X8 + .13X9 + .09X10 + .18X11 where Y = Predicted overall performance score X1 = Score in BMAN10001 (10) - Economic Principles : Microeconomics X2 = Score in BMAN10621(M) (10) - Fundamentals of Financial Reporting X3 = Score in BMAN10632(M) (10) - Fundamentals of Management Acctg X4 = Score in BMAN10732 (10) - Quantitative Methods for Bus & Mgmt 2 X5 = Score in BMAN10780 (10) - Business & Management Skills X6 = Score in BMAN10791 (10) - People and Organisations X7 = Score in BMAN10801 (10) - Introduction to Work Psychology X8 = Score in BMAN10821 (10) - Quantitative Methods for B&M 1 X9 = Score in BMAN10842 (10) - Law in a Management Context X10 = Score in BMAN10002 (10) - Economic Principles : Macroeconomics X11 = Score in BMAN10522(M) (10) - Financial Decision Making (M) Conclusion This investigation provides us with sufficient evidence to conclude that overall performance is highly dependent on a student’s performance in each of the unit courses. There seems to be no sufficient evidence that would suggest that demographics or prior maths eduation has any significant bearing on the overall performance of a student. Therefore, it may seem that upon entry in the first year, a student starts off with a clean slate in such that previous education, specifically previous maths education nor demographics could significantly affect his overall performance. References Anderson, D. R., Sweeney, D., & Williams, T. (2009). Statistics for Business and Economics. Mason, OH: Thomas Higher Education. Bluman, A. (2004). Elementary statistics: a step by step approach, 5th ed. McGraw-Hill. Tabak, J. (2004). Probability and statistics: The science of uncertainty. Infobase Publishing. Appendix Table 1. Demographic characteristics of respondents (N = 236). Demographic Characteristics Frequency Percent Cumulative % Country Russian Federation 2 .8 .8 China 60 25.4 26.3 United Kingdom 86 36.4 62.7 India 20 8.5 71.2 Lithuania 2 .8 72.0 Bulgaria 4 1.7 73.7 Pakistan 3 1.3 75.0 Romania 7 3.0 78.0 Canada 1 .4 78.4 Korea, Republic of 12 5.1 83.5 Hong Kong 5 2.1 85.6 Nigeria 1 .4 86.0 Norway 2 .8 86.9 Sri Lanka 1 .4 87.3 Thailand 1 .4 87.7 Sweden 3 1.3 89.0 Ireland 1 .4 89.4 Poland 2 .8 90.3 Vietnam 1 .4 90.7 Czech Republic 1 .4 91.1 Syria Arab Republic 2 .8 91.9 Slovakia 1 .4 92.4 Germany 1 .4 92.8 Singapore 5 2.1 94.9 Bangladesh 1 .4 95.3 Netherlands 1 .4 95.8 Brazil 1 .4 96.2 Brunei Darussalam 2 .8 97.0 Italy 1 .4 97.5 Taiwan, Republic of 1 .4 97.9 Saudi Arabia 1 .4 98.3 Qatar 1 .4 98.7 Ukraine 1 .4 99.2 Malaysia 1 .4 99.6   Kazakhstan 1 .4 100.0 Demographic Characteristics Frequency Percent Cumulative % Program BSc (Hons) Mgt (Acctg) 38 16.1 16.1 BSc (Hons) Mgt (Mktg) 62 26.3 42.4 BSc (Hons) Mgt (IBE) 29 12.3 54.7 BSc (Hons) Mgt (Hum Res) 9 3.8 58.5 BSc (Hons) Mgt (IS) 8 3.4 61.9 BSc (Hons) Mgt (Dec Mkg) 2 .8 62.7 BSc (Hons) Mgt (Oper) 2 .8 63.6   BSc (Hons) Management 86 36.4 100.0 Region OS 127 53.8 53.8 UK 86 36.4 90.3   EU 23 9.7 100.0 Age Regular 206 87.3 87.3 Mature 30 12.7 100.0 Gender Male 110 46.6 46.6   Female 126 53.4 100.0 Table 2. Summary of descriptive statistics (N = 236) Unit Title Mean Std. Deviation BMAN10001 (10) - Economic Principles : Microeconomics 70.02 14.77 BMAN10621(M) (10) - Fundamentals of Financial Reporting 46.06 19.88 BMAN10632(M) (10) - Fundamentals of Management Accounting 50.09 17.28 BMAN10732 (10) - Quantitative Methods for Bus & Mgmt 2 59.22 20.05 BMAN10780 (10) - Business & Management Skills 66.84 11.95 BMAN10791 (10) - People and Organisations 56.40 12.31 BMAN10801 (10) - Introduction to Work Psychology 55.97 11.69 BMAN10821 (10) - Quantitative Methods for B&M 1 59.52 18.87 BMAN10842 (10) - Law in a Management Context 48.40 14.05 BMAN10002 (10) - Economic Principles : Macroeconomics 63.29 12.61 BMAN10522(M) (10) - Financial Decision Making (M) 54.27 18.47 BMAN10812 (10) - The Modern Corporation 56.22 13.90 BMAN10852 (10) - Management in Society 53.42 16.79 Overall Performance 56.88 11.70 Table 3. Correlations between variables (N = 236). Variable 2 3 4 5 6 7 8 9 10 11 12 13 14 Overall Performance .765 .739 .862 .818 .473 .511 .690 .689 .708 .807 .833 .707 .756 BMAN10001 (10) - Economic Principles : Microeconomics - .662 .604 .642 .292 .409 .463 .644 .400 .618 .603 .384 .385 BMAN10621(M) (10) - Fundamentals of Financial Reporting - - .690 .604 .197 .366 .386 .631 .367 .555 .581 .395 .230 BMAN10632(M) (10) - Fundamentals of Management Acctg - - - .691 .304 .410 .535 .619 .634 .682 .716 .528 .571 BMAN10732 (10) - Quantitative Methods for Bus & Mgmt 2 - - - - .352 .279 .404 .636 .499 .604 .647 .469 .641 BMAN10780 (10) - Business & Management Skills - - - - - .270 .329 .236 .349 .323 .183 .307 .407 BMAN10791 (10) - People and Organisations - - - - - - .461 .185 .387 .264 .306 .391 .311 BMAN10801 (10) - Introduction to Work Psychology - - - - - - - .334 .582 .573 .462 .638 .638 BMAN10821 (10) - Quantitative Methods for B&M 1 - - - - - - - - .299 .477 .608 .232 .307 BMAN10842 (10) - Law in a Management Context - - - - - - - - - .573 .517 .587 .702 BMAN10002 (10) - Economic Principles : Macroeconomics - - - - - - - - - .643 .565 .633 BMAN10522(M) (10) - Financial Decision Making (M) - - - - - - - - - - - .599 .597 BMAN10812 (10) - The Modern Corporation - - - - - - - - - - - - .815 BMAN10852 (10) - Management in Society - - - - - - - - - - - - - ***all relationships significant at p < .01 1 = Overall Performance 2 = BMAN10001 (10) - Economic Principles : Microeconomics 3 = BMAN10621(M) (10) - Fundamentals of Financial Reporting 4 = BMAN10632(M) (10) - Fundamentals of Management Acctg 5 = BMAN10732 (10) - Quantitative Methods for Bus & Mgmt 2 6 = BMAN10780 (10) - Business & Management Skills 7 = BMAN10791 (10) - People and Organisations 8 = BMAN10801 (10) - Introduction to Work Psychology 9 = BMAN10821 (10) - Quantitative Methods for B&M 1 10 = BMAN10842 (10) - Law in a Management Context 11 = BMAN10002 (10) - Economic Principles : Macroeconomics 12 = BMAN10522(M) (10) - Financial Decision Making (M) 13 = BMAN10812 (10) - The Modern Corporation 14 = BMAN10852 (10) - Management in Society Table 4. Summary of chi square analysis. Chi-Square Tests Gender Value df Asymp. Sig. (2-sided) Male Pearson Chi-Square 5.630a 2 .060 Likelihood Ratio 6.966 2 .031 Linear-by-Linear Association 5.400 1 .020 N of Valid Cases 110 Female Pearson Chi-Square 4.620b 2 .099 Likelihood Ratio 6.032 2 .049 Linear-by-Linear Association 4.517 1 .034 N of Valid Cases 126 a. 1 cells (16.7%) have expected count less than 5. The minimum expected count is 1.54. b. 1 cells (16.7%) have expected count less than 5. The minimum expected count is 1.35. Table 5. Summary of t test results. Unit Course Prior Maths Education N Mean SD t df p BMAN10001 (10) - Economic Principles : Microeconomics No prior maths education 111 72.47 13.62 2.44 234 0.02 With prior maths education 125 67.85 15.45 BMAN10621(M) (10) - Fundamentals of Financial Reporting No prior maths education 111 49.27 20.05 2.36 229 0.02 With prior maths education 125 43.21 19.37       BMAN10632(M) (10) - Fundamentals of Management Accounting No prior maths education 110 50.38 16.86 0.24 232 0.81 With prior maths education 125 49.84 17.71 BMAN10732 (10) - Quantitative Methods for Bus & Mgmt 2 No prior maths education 110 60.95 20.15 1.25 228 0.21 With prior maths education 125 57.69 19.91       BMAN10780 (10) - Business & Management Skills No prior maths education 110 66.62 11.55 -0.27 232 0.79 With prior maths education 125 67.04 12.34 BMAN10791 (10) - People and Organisations No prior maths education 111 56.56 12.29 0.18 231 0.85 With prior maths education 125 56.26 12.37       BMAN10801 (10) - Introduction to Work Psychology No prior maths education 111 54.73 12.61 -1.53 217 0.13 With prior maths education 125 57.07 10.73 BMAN10821 (10) - Quantitative Methods for B&M 1 No prior maths education 111 61.84 15.77 1.79 234 0.08 With prior maths education 125 57.46 21.10       BMAN10842 (10) - Law in a Management Context No prior maths education 110 47.15 14.10 -1.29 229 0.20 With prior maths education 125 49.51 13.96 BMAN10002 (10) - Economic Principles : Macroeconomics No prior maths education 104 63.94 14.17 0.72 194 0.48 With prior maths education 116 62.71 11.05       BMAN10522(M) (10) - Financial Decision Making (M) No prior maths education 92 55.27 17.60 0.74 176 0.46 With prior maths education 89 53.22 19.37 BMAN10812 (10) - The Modern Corporation No prior maths education 94 55.41 14.37 -0.78 188 0.43 With prior maths education 98 56.99 13.46       BMAN10852 (10) - Management in Society No prior maths education 40 48.73 21.20 -2.27 107 0.03 With prior maths education 69 56.14 13.03 Overall Performance No prior maths education 111 57.35 11.90 0.57 229 0.57 With prior maths education 125 56.47 11.56       Table 6. Results of regression analysis Model Summaryb Model R R Square Adjusted R Square Std. Error of the Estimate dimension0 1 .997a .995 .994 .7193826 ANOVAb Model Sum of Squares df Mean Square F Sig. 1 Regression 15418.287 11 1401.662 2708.467 .000a Residual 80.214 155 .518 Total 15498.501 166 Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. B Std. Error Beta 1 (Constant) .491 .615 .799 .426 BMAN10001 (10) - Economic Principles : Microeconomics .090 .008 .110 11.840 .000 BMAN10621(M) (10) - Fundamentals of Financial Reporting .083 .005 .166 18.049 .000 BMAN10632(M) (10) - Fundamentals of Management Accounting .078 .007 .124 11.968 .000 BMAN10732 (10) - Quantitative Methods for Bus & Mgmt 2 .091 .005 .167 18.799 .000 BMAN10780 (10) - Business & Management Skills .095 .006 .099 16.373 .000 BMAN10791 (10) - People and Organisations .087 .006 .102 14.606 .000 BMAN10801 (10) - Introduction to Work Psychology .100 .008 .100 12.908 .000 BMAN10821 (10) - Quantitative Methods for B&M 1 .077 .005 .140 16.016 .000 BMAN10842 (10) - Law in a Management Context .107 .006 .133 16.798 .000 BMAN10002 (10) - Economic Principles : Macroeconomics .084 .008 .089 9.999 .000 BMAN10522(M) (10) - Financial Decision Making (M) .097 .005 .177 19.501 .000 a. Dependent Variable: Overall Performance Read More