CHAPTER 4: EMPIRICAL RESULTS AND DISCUSSIONS OF QUANTITATIVE ANALYSIS
4.1. Correlation analysis
4.1.3. Summary of correlations sweep
The whole question of whether the total matric points or designated matric subject scores are good predictors of student success in undergraduate first-year accounting and economics modules in the FMS is tested with the above comprehensive correlations sweep across the five academic years measured.
The first observation concerns the statistically significant coefficients mined. Results across three out of five indicator academic years indicate in absolute terms that total matric points have some correlations that have statistically significant coefficients with student success in the ACCT101 module. Results across two out of five indicator academic years indicate in absolute terms that total matric points have some correlations that have statistically significant coefficients with student success in ACCT102 module. The result of only one out of five academic years indicates in absolute terms that total matric points have some correlations that have a statistically significant coefficient with student success in the ECON101 module.
Results across two out of five indicator academic years indicate in absolute terms that total matric points
108 have some correlations that have statistically significant coefficients with student success in the ECON102 module. These results are consolidated by the frequency distribution in the following Table 4-7.
Table 4-7: Frequency Distribution for Correlations between Total Matric Points and Student Success, FMS, CLMS, 2004-2008.
Modules Frequency Relative frequency (in %)
ACCT 101 3 60
ACCT 102 2 40
ECON 101 1 20
ECON 102 2 40
Source: Compiled from the Table 4-1.
In Table 4-7, there is some evidence of correlation between total matric points and student success at university, but not fully supported by probabilities which are very low, ranging from 20 to 60 percent.
In terms of correlations between matric subject scores and student success, the results indicate that student success in ACCT101 and matric Maths scores, matric English I scores, matric English II scores, and matric Accounting scores are correlated. The results indicate that student success in ACCT102 and matric Maths scores, matric English I scores, and matric Accounting scores are correlated; that student success in ECON101 and matric Maths scores, matric English I scores, and matric Economics scores are correlated;
and that student sucess in ECON102 and matric Maths scores, and matric English I scores are correlated.
These results are consolidated in the following Table 4-8.
Table 4-8: Consolidation of Correlations between Matric Subject Scores and Student Success, FMS, CLMS, 2004- 2008.
Modules Matric Maths Matric English I Matric English II Matric Accounting
Matric Economics ACCT 101 0.235 (40)(a) 0.094 (20) 0.2745 (40) 0.089 (40) 0.182 (20)
ACCT 102 0.124 (20) 0.1135 (40) - (0) 0.0915 (40) 0.1745 (40)
ECON 101 0.067 (20) 0.094 (40) - (0) 0.1245 (40) 0.1165 (40)
ECON 102 - (0) 0.086 (40) - (0) 0.073 (20) - (0)
(a) Average coefficients in absolute value and in parenthesis are the corresponding frequency distribution in percentage.
Source: Compiled from the Tables 4.3 to 4.6.
Interestingly, the results indicate that matric English II scores which is written by students whose home first language is not English, are not correlated with their academic performance in the ECON101, ECON102,
109 and ACCT 102 modules. However, their performance in ECON102 has correlations with matric English I scores.
Premised upon the evidence in Sections 4.1.1. and 4.1.2., as well as the frequency of statistically significant correlations from the Tables 4-1 to 4-6, their magnitudes, and in terms of probabilities in Tables 4-7 and 4- 8, both total matric points (or APS) and matric subject scores that include Maths, English I, Accounting and Economics, in their current status, have some correlation with student success in the FMS, but the magnitudes of these correlations are not very high, ranging from 0.06 to 0.27. The frequency of statistically significant correlations is not fully supported by probabilities which are very low, ranging from 20 to 60 percent.
To elicit the whole question of whether the predictors of student performance at the university intake level are wearing off as students progress to second- and third-year accounting and economics modules in the FMS, pair-wise correlations sweep between, on the one hand, total matric points, matric Maths, and English I and II scores, and on the other the hand, student performance in second- and third-year accounting and economics modules across the same five academic years were tested.
A perusal of the results also indicates that the total matric points, matric Maths, and matric English I achieved by students who have English as their home first language, are all correlated with student performance in the second- and third-year economics modules. Only matric English I is correlated with third-year accounting module. These results indicate that correlations factorized above are not wearing off as the student progresses in the FMS. Therefore, to some extent, the total matric points, matric Maths, and matric English I are predictors of student success after the intake level.
A perusal of the tables illustrating correlations sweep between the student performance in first-year accounting and economics modules, on the one hand, and their performance in second- and third-year modules at university level across the five academic years reveals that, in absolute terms, the student performance in first-year accounting modules are correlated with ACCT200, ACCT2ISR, and ACCT300.
The student performance in ACCT101 (ACC111S at the former UDW) and ACCT102 (ACC112S at the former UDW) in 2004 was correlated with their performance in ACCT2A0. Performance in ISTN101 and ISTN102 was also correlated with ACCT2ISR. The student performance in ACCT101 was correlated with ACCT102 in 2008. The student performance in first-year economics modules are correlated with their performance in second-year modules but were never correlated with the third-year module.
110 In absolute terms, all the pair-wise correlation coefficients between the student performance in first-year economics modules and second-year modules are statistically significant. Information systems and technology modules at the first-year level (ISTN101 and ISTN102) are good predictors of success in second-year accounting information systems (ACCT2ISR) modules and the student performance in accounting 1 modules was a good predictor of success in accounting 2 module at the former UDW. First- year performance is not correlated with the third-year module. Correlations between second-year and third- year modules were never statistically significant.
A further deduction that can emanate from the empirical results is that passing students are more likely to do extremely well when they progress to second-year modules. Alternatively, struggling students are more likely to do extremely badly. Therefore, student performance in first-year ECON101 and ECON102 modules, as well as in the quantitative method course are good predictors of whether the student will perform well in the second-year economics modules, but they are inconclusive in predicting third-year modules. An important finding is also that the correlation between undergraduate modules and matric subject scores (or their aggregate total matric points) is not wearing off as the student progresses in the FMS, except that there is a relatively weak positive correlation between the student performance in ECON202S modules and matric English II, suggesting that students whose the home first language is not English and who wrote matric English II, are more likely to perform less well even at the second-year level.
These results shed some light on the issue and are in line with the findings of the few existing institutional studies commissioned within UKZN.
Table 4-9 examined the correlation between total matric points and pass rates in individual first-year modules in the FMS for the 2005 academic year (Tewari et al., 2008). A perusal of this table highlights the following salient features of students’ performance trends: (1) in general students are performing poorly in modules involving quantitative skills, and (2) specifically, below the total matric points (or APS) of 36 – the requirement for acceptance to the BCom (Accounting) and BCom (General) degree in the FMS - students were much less likely to be successful in the approved first-year curriculum.
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Table 4-9: Total Matric Points and Pass Rate per Selected First-year Modules, FMS, CLMS, 2005.
Total Matric Points
Module Code Students Blank Below 20 20-29 30-39 40-50 Grand Total
ACCT101 Registered Passed Pass Rate
70 42 60%
3 1 33%
161 100 62%
661 496 75%
558 535 96%
1453 1174 81%
ACCT102 Registered Passed Pass Rate
45 29 64%
3 1 33%
131 71 54%
565 387 68%
548 493 90%
1292 981 76%
ECON101 Registered Passed Pass Rate
49 29 59%
8 3 38%
140 26 19%
744 318 43%
598 494 83%
1539 870 57%
ECON102 Registered Passed Pass Rate
49 36 73%
4 0 0%
92 18 20%
547 268 49%
562 442 79%
1254 764 61%
ISTN101 Registered Passed Pass Rate
67 38 57%
10 6 60%
135 53 39%
680 464 68%
606 543 90%
1498 1104 74%
ISTN102 Registered Passed Pass Rate
38 19 50%
8 5 63%
103 25 24%
513 212 41%
554 377 68%
1216 638 52%
MGNT102 Registered Passed Pass Rate
31 30 97%
1 1 100%
15 15 100%
161 146 91%
137 134 98%
345 326 94%
MATHS134 Registered Passed Pass Rate
52 39 75%
9 6 67%
72 41 57%
523 344 66%
548 456 83%
1204 886 74%
MATHS137 Registered Passed Pass Rate
5 3 60%
37 11 30%
135 52 39%
38 27 71%
215 93 43%
STAT171 Registered Passed Pass Rate
41 26 63%
1 0 0%
45 15 33%
386 180 47%
477 324 68%
950 545 57%
Source: Tewari et al. (2008).
Evidence to support these results is drawn from a symposium on the correlations between the NSC and first-year students’ performance at UKZN (UTLO, 2010). Student success in ACCT101 was found to be correlated with matric Maths scores, and matric English I scores while student success in ACCT102 had no statistically significant correlation with all the designated matric subject scores. Student success in ACCT101 was not correlated with matric English II scores. In the same study, student success in ECON101 was found to be correlated with matric Maths scores, matric English I scores and matric English II scores, whereas student success in ECON102 had no statistically significant correlation with the designated matric subject scores.
Another study found that a higher proficiency in Maths is associated with a higher level of performance at university for students who are also competent in English. This is to say that even though a student may be
112 competent in Maths, his or her performance in a module such as accounting or economics can be negatively affected by poor language skills (Wong and Chia, 1996).
This study, however, cannot confirm these studies’ results as they only incorporated students enrolled in a single academic year: 1996 for Wong and Chia; 2005 for Tewari et al.; or 2009 for the UTLO, respectively.
These results are demanding further examination. Total matric points and matric subject scores data were fitted into regression analysis (Sections 4.2. and 4.3.) to further establish and quantify, holistically, their linear relationship in predicting student success in the FMS. Only the records of active students of the cohorts of 2004 (the initial year) and 2008 (the end year that will capture any change if occurred) are fitted in the modelled educational production function in equations 3-3 and 3-6. The consolidation of the findings is discussed in more detail in Chapter 6.
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