Theme 13: Recommendations for university management and academics on the use of the internet to enhance students’ academic performance
II: Gender
7.3 INFERENTIAL STATISTICAL ANALYSIS
Data presentation in this section is meant to derive inferences, explain relationships between variables, for instance age, gender and level of study and university distribution of participants against a variety of continuous variables such as access and skills of computer and internet use. In this section, a few inferential statistics are computed and reported, e.g., the Pearson chi-square and the analysis of variance
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(ANOVA) which are meant to test the relationship between two continuous variables, for example level of study versus use of online databases. The chi-square tests for nominal variables with two categories and the ANOVA for variables with more than two categories. For any differences to be considered significant the chi-square test (Asymptotic significance [2 sided]) should equal 0 or be lower than 0.05.
A key component inferential statistics is the calculation of statistical significance of a finding. On the measure of statistical significance, Muijis (2004) states that the chi square test measures statistical significance of variables and gives a significance level or p-value. O’Leary (2004) states that in order to be able to state that the relationship studied is statistically significant, the p-value is less than 0.05 (which corresponds to a confidence level of 95%), e.g., a p-value of 0,002 is statistically significant.
The following sub-sections present these statistical findings and tests.
7.3.1 Relationship between university distribution of participants and access to a computer
The results illustrated in Table 7.29 indicate the relationship between the participants’
university distribution and their access to a computer. Thirty-seven per cent (37%) of the participants from the University of Venda, and 19% from the University of Limpopo accessed a computer from a computer laboratory on campus. Ninety-six per cent (96%) of the participants from TUT and 80% from the University of Limpopo either owned a laptop or a tablet.
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TABLE 7.29: UNIVERSITY DISTRIBUTION AND ACCESS TO COMPUTER
PARTICIPANTS' ACCESS TO A COMPUTER
Total Yes, on the computer
laboratories on campus
Yes, I own a laptop/desktop/tablet
Yes at home UNIVERSITY
DISTRIBUTION OF THE PARTICIPANTS
UL Count 23 96 1 120
% within UNIVERSITY DISTRIBUTION OF THE PARTICIPANTS
19.2% 80.0% 0.8% 100.0
%
UNIVEN Count 38 75 0 113
% within UNIVERSITY DISTRIBUTION OF THE PARTICIPANTS
33.6% 66.4% 0.0% 100.0
%
TUT Count 4 106 0 110
% within UNIVERSITY DISTRIBUTION OF THE PARTICIPANTS
3.6% 96.4% 0.0% 100.0
%
Total Count 65 277 1 343
% within UNIVERSITY DISTRIBUTION OF THE PARTICIPANTS
19.0% 80.8% 0.3% 100.0
%
TABLE 7.30: Chi-Square Tests - University distribution and access to computer
Value df Asymptotic Significance (2-sided)
Pearson Chi-Square 34.543a 4 .000
Likelihood Ratio 39.220 4 .000
Linear-by-Linear Association 7.169 1 .007
N of Valid Cases 343
a. 3 cells (33.3%) have expected count less than 5. The minimum expected count is .32.
As the Asymptotic Significance (2-sided) value is .000, this indicates that there are statistically significant differences between the participants’ university distribution and their access to a computer. This indicates that the technological infrastructure of the three universities had a direct influence towards students’ access to a computer. The University of Limpopo and University of Venda had two computer laboratories respectively, while Tshwane University of Technology Polokwane campus had a single computer laboratory.
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7.3.2 Relationship between university distribution of participants and access to the internet
The results in Table 7.31 show the relationship between the participants’ university distribution and their access to the internet. The study has discovered that 78 per cent of the participants from University of Limpopo access the internet through Wi-Fi connections at students’ hostels, while 39 per cent of the participants from University of Venda access the internet from computer labs. Eighteen per cent of the participants from TUT access the internet through Wi-Fi connections at the premises of the university.
TABLE 7.31: UNIVERSITY DISTRIBUTION AND ACCESS TO THE INTERNET
PARTICIPANTS' ACCESS TO THE INTERNET
Total Yes, on the
computer laboratories on
campus
Yes, via WI-FI at the students'
residences
Yes, via WI-FI at the premises of the university UNIVERSITY
DISTRIBUTION OF THE PARTICIPANTS
UL Count 22 94 4 120
% within UNIVERSITY DISTRIBUTION OF THE PARTICIPANTS
18.3% 78.3% 3.3% 100.0
%
UNIVEN Count 44 60 9 113
% within UNIVERSITY DISTRIBUTION OF THE PARTICIPANTS
38.9% 53.1% 8.0% 100.0
%
TUT Count 21 69 20 110
% within UNIVERSITY DISTRIBUTION OF THE PARTICIPANTS
19.1% 62.7% 18.2% 100.0
%
Total Count 87 223 33 343
% within UNIVERSITY DISTRIBUTION OF THE PARTICIPANTS
25.4% 65.0% 9.6% 100.0
%
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TABLE 7.32: Chi-Square Tests - University distribution and access to the internet
Value df Asymptotic Significance (2-sided)
Pearson Chi-Square 31.717a 4 .000
Likelihood Ratio 30.875 4 .000
Linear-by-Linear Association 3.177 1 .075
N of Valid Cases 343
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 10.58.
As the Asymptotic Significance (2-sided) value is .000, this means that there are statistically significant differences between the participants’ university distribution and their access to the internet. This indicates that university distribution of the participants had direct influence concerning their internet access. Therefore, the findings presented in Table 7.32 support those of Table 7.31 in the sense that there were more students from UNIVEN who access the internet through computer labs, while majority of participants from TUT access the internet through Wi-Fi connection in the premises of the university.
7.3.3 Relationship between participants’ level of study and computer skills The results in Table 7.33 indicate the relationship between the participants’ level of study and their computer skills. The study revealed that 57 per cent of the participants at first year level and 10 per cent of students at second year level rated their computer skills as “moderate”. However, 94 per cent of the participants from the third year level rated their computer skills as “good’. Thirty-nine per cent of participants from the fourth year level, 31 per cent from the Honours level and 53 per cent from the Masters level rated their computer skills as “excellent’.
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TABLE 7.33: LEVEL OF STUDY AND COMPUTER SKILLS OF THE PARTICIPANTS
COMPUTER SKILLS OF THE PARTICIPANTS
Total Poor Moderate Good Excellent
LEVEL OF STUDY OF THE
PARTICIPANTS
First level
Count 1 16 11 0 28
% within LEVEL OF STUDY OF THE
PARTICIPANTS
3.6% 57.1% 39.3% 0.0% 100.0%
Second level
Count 0 8 67 3 78
% within LEVEL OF STUDY OF THE
PARTICIPANTS
0.0% 10.3% 85.9% 3.8% 100.0%
Third level
Count 0 1 147 8 156
% within LEVEL OF STUDY OF THE
PARTICIPANTS
0.0% 0.6% 94.2% 5.1% 100.0%
Fourth level
Count 0 1 21 14 36
% within LEVEL OF STUDY OF THE
PARTICIPANTS
0.0% 2.8% 58.3% 38.9% 100.0%
Honours level
Count 0 0 18 8 26
% within LEVEL OF STUDY OF THE
PARTICIPANTS
0.0% 0.0% 69.2% 30.8% 100.0%
Masters level
Count 0 0 9 10 19
% within LEVEL OF STUDY OF THE
PARTICIPANTS
0.0% 0.0% 47.4% 52.6% 100.0%
Total Count 1 26 273 43 343
% within LEVEL OF STUDY OF THE
PARTICIPANTS
0.3% 7.6% 79.6% 12.5% 100.0%
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TABLE 7.34: Chi-Square Tests - Level of study and computer skills of the participants
Value df Asymptotic Significance (2-sided)
Pearson Chi-Square 198.559a 15 .000
Likelihood Ratio 137.815 15 .000
Linear-by-Linear Association 93.520 1 .000
N of Valid Cases 343
a. 14 cells (58.3%) have expected count less than 5. The minimum expected count is .06.
The Asymptotic Significance (2-sided) value is .000, with expected level of 0.05, which demonstrates that there are statistically significant differences between the participants’ level of study and their computer skills. This confirms that the educational level had an impact on participants’ computer skills. Thus, the majority of the participants especially from the lower levels rated their computer skills as moderate, while participants from the senior levels rated their computer skills as good and excellent.
7.3.4 Relationship between participants’ level of study and internet skills
The findings in in Table 7.35 indicate the relationship between the participants’ level of study and their internet skills. The study findings revealed that 36 per cent of the participants at first level rated their internet skills as being moderate, while 25 per cent from the second year level and 91 per cent from third year level rated their internet skills as being good. Nonetheless, 22 per cent of the participants from the fourth year level, 27 per cent from Honours and 26 per cent from masters’ level rated their internet skills as being excellent.
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TABLE 7.35: LEVEL OF STUDY AND INTERNET SKILLS OF THE PARTICIPANTS
INTERNET SKILLS OF THE PARTICIPANTS
Total Moderate Good Excellent
LEVEL OF STUDY OF THE PARTICIPANTS
First level
Count 10 17 1 28
% within LEVEL OF STUDY OF THE
PARTICIPANTS
35.7% 60.7% 3.6% 100.0%
Second level
Count 5 71 2 78
% within LEVEL OF STUDY OF THE
PARTICIPANTS
6.4% 91.0% 2.6% 100.0%
Third level
Count 4 140 12 156
% within LEVEL OF STUDY OF THE
PARTICIPANTS
2.6% 89.7% 7.7% 100.0%
Fourth level
Count 4 24 8 36
% within LEVEL OF STUDY OF THE
PARTICIPANTS
11.1% 66.7% 22.2% 100.0%
Honours level
Count 0 19 7 26
% within LEVEL OF STUDY OF THE
PARTICIPANTS
0.0% 73.1% 26.9% 100.0%
Masters level
Count 0 14 5 19
% within LEVEL OF STUDY OF THE
PARTICIPANTS
0.0% 73.7% 26.3% 100.0%
Total Count 23 285 35 343
% within LEVEL OF STUDY OF THE
PARTICIPANTS
6.7% 83.1% 10.2% 100.0%
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TABLE 7.36: Chi-Square Tests - Level of study and internet skills of the participants
Value df Asymptotic Significance (2-sided)
Pearson Chi-Square 71.677a 10 .000
Likelihood Ratio 55.493 10 .000
Linear-by-Linear Association 34.103 1 .000
N of Valid Cases 343
a. 8 cells (44.4%) have expected count less than 5. The minimum expected count is 1.27.
As the Asymptotic Significance (2-sided) value is .000, this indicates that there are statistically significant differences between the participants’ level of study and their internet skills. This finding means that educational level had direct influence on students’ internet skills. Thus, the findings presented in Table 7.36 support those of Table 7.35 in the sense that there were more participants from first year level who rated their internet skills as being moderate and majority of the participants from senior levels rated their internet skills as being good and excellent.
7.3.5 Relationship between university distribution and use of online databases The findings in Table 7.37 demonstrate the relationship between university distribution of the participants and the use of online databases. The study findings revealed that 66 per cent of the participants from the UL and 74 per cent from the UNIVEN indicated that they used online databases when searching academic information on the internet.
Nonetheless, 86 per cent of the participants from TUT indicated that they did not use online databases for information search.
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TABLE 7.37: UNIVERSITY DISTRIBUTION AND USE OF ONLINE DATABASES
USE OF ONLINE DATABSES FOR INFORMATION SEARCH
Total
Yes No
UNIVERSITY DISTRIBUTION OF THE PARTICIPANTS
UL Count 41 79 120
% within UNIVERSITY DISTRIBUTION OF THE PARTICIPANTS
34.2% 65.8% 100.0%
UNIVEN Count 29 84 113
% within UNIVERSITY DISTRIBUTION OF THE PARTICIPANTS
25.7% 74.3% 100.0%
TUT Count 16 94 110
% within UNIVERSITY DISTRIBUTION OF THE PARTICIPANTS
14.5% 85.5% 100.0%
Total Count 86 257 343
% within UNIVERSITY DISTRIBUTION OF THE PARTICIPANTS
25.1% 74.9% 100.0%
TABLE 7.38: Chi-Square Tests - University distribution and use of online databases
Value df Asymptotic Significance (2-sided)
Pearson Chi-Square 11.793a 2 .003
Likelihood Ratio 12.245 2 .002
Linear-by-Linear Association 11.689 1 .001
N of Valid Cases 343
a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 27.58.
The Asymptotic Significance (2-sided) value is .003, which means that there are statistically significant differences between university distribution of the participants and their use of online databases when searching for academic information on the internet – because the Asymp. Sig is less than 0.05, the level of significance. This implies that participants’ university distribution had a slight influence on the use online databases for information search. The findings in Table 7.37 indicate that most of the participants from the UL and TUT agreed that they used online databases when searching for information, while 37 per cent of the participants from TUT indicated that they did not use online databases when searching for information.
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7.3.6 Relationship between level of study and use of online databases
The findings in Table 7.39 indicate the relationship between the level of study of the participants and the use of online databases. Of the 28 participants who studied at first year level, only one (4%) indicated that one used online databases. Seventy-eight per cent (78%) of the participants from the third year level indicated that they did not use online databases when searching for information through the internet. Of the 26 participants who were enrolled for Honours degrees, 92 per cent indicated that they used online databases to search for academic information. Seventy-nine per cent (79%) of participants at Masters level agreed that they used online databases when searching for academic material.
TABLE 7.39: LEVEL OF STUDY AND USE OF ONLINE DATABASES
USE OF ONLINE DATABSES FOR INFORMATION SEARCH
Total
Yes No
LEVEL OF STUDY OF THE PARTICIPANTS
First level
Count 1 27 28
% within LEVEL OF STUDY OF THE PARTICIPANTS
3.6% 96.4% 100.0%
Second level
Count 3 75 78
% within LEVEL OF STUDY OF THE PARTICIPANTS
3.8% 96.2% 100.0%
Third level
Count 34 122 156
% within LEVEL OF STUDY OF THE PARTICIPANTS
21.8% 78.2% 100.0%
Fourth level
Count 9 27 36
% within LEVEL OF STUDY OF THE PARTICIPANTS
25.0% 75.0% 100.0%
Honours level
Count 24 2 26
% within LEVEL OF STUDY OF THE PARTICIPANTS
92.3% 7.7% 100.0%
Masters level
Count 15 4 19
% within LEVEL OF STUDY OF THE PARTICIPANTS
78.9% 21.1% 100.0%
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Total Count 86 257 343
% within LEVEL OF STUDY OF THE PARTICIPANTS
25.1% 74.9% 100.0%
TABLE 7.40: Chi-Square Tests - Level of study and use of online databases
Value df Asymptotic Significance (2-sided)
Pearson Chi-Square 118.408a 5 .000
Likelihood Ratio 114.522 5 .000
Linear-by-Linear Association 94.155 1 .000
N of Valid Cases 343
a. 1 cells (8.3%) have expected count less than 5. The minimum expected count is 4.76.
The Asymptotic Significance (2-sided) value is .000, this indicates that there are statistically significant differences between the participants’ level of study and their use of online databases for researching academic information. This indicates that students’
level of study had direct influence on the use of online databases to search for academic material. Thus, the findings presented in Table 7.40 support those of Table 7. 39 in the sense that there was a majority of participants from undergraduate level who indicated that they did not use online databases when searching for academic information.
7.3.7 Relationship between gender and use of the internet for academic purposes
The results in Table 7.41 indicate the relationship between gender of the participants and their satisfaction on the use of the internet for academic purposes. The study findings discovered that 88 per cent of participants were often while six per cent (6%) were more often satisfied with using the internet for academic purposes for both males and females respectively.