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Transcript of Ict Acceptance and Use by Ukm Graduate Students_siti 12,07am_edited 1.30 Pm Friday_nawal_zaher...
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ICT ACCEPTANCE AND USE BY UKM GRADUATE STUDENTS
ZAHER ATWA (P 71592)NAWAL MUSTAFA (P 59223)SITI HASHIDAH BINTI MOHD NASIR (P 66513)
UNIVERSITI KEBANGSAAN MALAYSIA
FAKULTI PENDIDIKAN
GGGB6323 ANALYSIS DATA SEMESTER 2 2013/2014
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INTRODUCTION
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OPERATIONAL DEFINITION OF ICT UNESCO Institute for Information Technologies in Education, 2003
audiocassette tapes, radio, videotapes, CD-ROM, the Internet, wireline technology, wireless technology, web-based training, audioconferencing, audiographics, interactive television, videoconferencing
Toomey, 2001technologies that are used for accessing, gathering, manipulating and presenting or communicating information which could include hardware (e.g. computers and other devices); software applications; and connectivity (e.g. access to the Internet, local networking infrastructure, videoconferencing) as well as the increasing convergence of computer-based, multimedia and communications technologies and the rapid rate of change that characterises both the technologies and their use
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ISSUES IN ICT USAGE Gender disparities in ICT usage More males using ICT (Horvat, Oreski &
Markic, 2011, Madell & Muncer, 2004) Nachimas, Moiduser & Shemla, 2000, Sherman et. al., 2000)
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OBJECTIVES1. To find out the extent of ICT usage
among graduate students in UKM2. To find out the level of acceptance of
ICT among graduate students in UKM
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RESEARCH QUESTIONS1. What is the extent of usage of ICT
among graduate students in UKM in their academic life?
2. What is the acceptance level of ICT among graduate students in UKM?
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HYPOTHESIS1. There is no difference between male
and female graduate students of UKM in using ICT
2. There is no difference between Malaysia and non-Malaysian graduate students of UKM in using ICT
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VALIDITY & REALIBILITY UTAUT – Unified Theory of Acceptance
and Use of Technology (Venkatesh et al., 2003)
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RESEARCH MODEL THEORY
Venkatesh et al. (2003)
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DATA COLLECTION Sampling of population – convenience
sampling Due to researchers time constraints Limited access to large number of samples
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DATA INPUT The data was checked and screened for
any errors. Negatively worded items were recoded. Regrouped into 5 constructs
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DATA ANALYSIS
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ICT ACCEPTANCE SCALES Performance expectancy (PE1-4), Effort expectancy (EE5-8), Social influence (SI9-12), Facilitating condition (FC13-20) Behavioral intention (BI21-23).
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DATA ANALYSIS: RELIABILITYReliability and consistency of the scale (Chronbach’s alpha
coefficient)
Performan
ce expectanc
y
Effort expectan
cy
Social influen
ce
Facilitating
condition
Behavioral
intention
ICT Accepta
nce
(α) 0.835 0.876 0.804 .790 .946 .821Mean 4.03 3.89 3.76 3.98 3.66 3.94Std. Deviation .81629 .84976 .68403 .58004 .93036 .60641**Mean 4.32 3.87 3.03 3.75 3.31 **Std. Deviation .665 .562 .300 .592 .465
**Oye et al (2011)
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DATA ANALYSIS: RELIABILITYReliability and consistency of the scale (Chronbach’s alpha
coefficient)
Performan
ce expectanc
y
Effort expectan
cy
Social influen
ce
Facilitating
condition
Behavioral
intention
ICT Accepta
nce
(α) 0.835 0.876 0.804 .790 .946 .821Mean 4.03 3.89 3.76 3.98 3.66 3.94Std. Deviation .81629 .84976 .68403 .58004 .93036 .60641**Mean 4.32 3.87 3.03 3.75 3.31 **Std. Deviation .665 .562 .300 .592 .465
**Oye et al (2011)
All the scales are reliable and consistent with their samples. (α>0.7) for each one, although the number of the sample is less than 10 per each.
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DATA ANALYSIS: ACCEPTANCEReliability and consistency of the scale (Chronbach’s alpha
coefficient)
Performan
ce expectanc
y
Effort expectan
cy
Social influen
ce
Facilitating
condition
Behavioral
intention
ICT Accepta
nce
(α) 0.835 0.876 0.804 .790 .946 .821Mean 4.03 3.89 3.76 3.98 3.66 3.94Std. Deviation .81629 .84976 .68403 .58004 .93036 .60641**Mean 4.32 3.87 3.03 3.75 3.31 **Std. Deviation .665 .562 .300 .592 .465
**Oye et al (2011)
Among the UTAUT constructs, performance expectancy exerted the strongest effect. Therefore Performance expectancy is the most influential factor for the acceptance and use of ICT by the UKM Graduate Students.
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DATA ANALYSIS: ACCEPTANCEReliability and consistency of the scale (Chronbach’s alpha
coefficient)
Performan
ce expectanc
y
Effort expectan
cy
Social influen
ce
Facilitating
condition
Behavioral
intention
ICT Accepta
nce
(α) 0.835 0.876 0.804 .790 .946 .821Mean 4.03 3.89 3.76 3.98 3.66 3.94Std. Deviation .82 .85 .68 .58 .93 .60641**Mean 4.32 3.87 3.03 3.75 3.31 **Std. Deviation .67 .56 .30 .59 .47 This result is consistent with Oye et al (2011) study which conducted in Nigeria University. Performance expectancy has the strongest effect and is the most influential factor for the acceptance and use of ICT by the UKM Graduate Students.**Oye et al (2011). Awareness, Adoption and Acceptance of ICT Innovation in Higher Education Institutions, International Journal of Engineering Research and Applications (IJERA):1(4), pp.1393-1409
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CORRELATIONS Performance expectancy
Effort expectancySocial influence
Facilitating conditionBehavioral intention
Performance expectancy
Pearson Correlation 1 .755** .671** .549** .230Sig. (2-tailed) .000 .000 .000 .133N 44 44 44 44 44
Effort expectancy
Pearson Correlation .755** 1 .737** .702** .323*
Sig. (2-tailed) .000 .000 .000 .033
Social influence
Pearson Correlation .671** .737** 1 .557** .305*
Sig. (2-tailed) .000 .000 .000 .044
Facilitating condition
Pearson Correlation .549** .702** .557** 1 .278Sig. (2-tailed) .000 .000 .000 .068
Behavioral intention
Pearson Correlation .230 .323* .305* .278 1Sig. (2-tailed) .133 .033 .044 .068
**. Correlation is significant at the 0.01 level (2-tailed).*. Correlation is significant at the 0.05 level (2-tailed).Correlation is positive for all of them,, small r=.10 to .29,,, medium r=.30 to .49,,, large r=.50 to 1.0
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DATA ANALYSIS: GENDER SIGNIFICANT
No significant difference concerning gender
Group Statistics Gend
erN Mean Std.
DeviationStd. Error
MeanICT Acceptance
Male 23 3.9506 .58547 .12208Female 20 3.9341 .65944 .14745
Independent Samples Test Levene's Test
for Equality of Variances
t-test for Equality of Means
F Sig. t df Sig. (2-tailed)
Mean Difference
Std. Error
Difference
95% Confidence Interval of
the Difference
Lower Upper
ICT Acceptance
Equal variances assumed
.000 .993 .087 41 .931 .01650 .18982-.3
6684
.39985
Equal variances not assumed
.086 38.3
94 .932 .01650 .19143-.3
7090
.40390
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DATA ANALYSIS: NATIONALITY SIGNIFICANT
No significant difference concerning Nationality
Group Statistics
Nationality N Mean Std. Deviation
Std. Error Mean
ICT Acceptance (B1-23)
Malaysian 13 4.0699 .40470 .11224Non Malaysian 25 3.8891 .70578 .14116
Independent Samples Test Levene's Test
for Equality of Variances
t-test for Equality of Means
F Sig. t df Sig. (2-tailed)
Mean Differen
ce
Std. Error
Difference
95% Confidence
Interval of the Difference
Lower Upper
ICT Acceptance
Equal variances assumed
3.594.066>0.05
.850 36 .401 .18084 .21263 -.25039 .612
07
Equal variances not assumed
1.00
3 35.533 .323 .18084 .18034 -.18508 .54676
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DATA ANALYSIS: MARITAL STATUS SIGNIFICANT
There is significant difference concerning Marital Status.
Group Statistics MaritalSt
atusN Mean Std.
DeviationStd. Error
MeanICT Acceptance Single 23 4.1285 .48796 .10175
Married 21 3.7359 .66644 .14543Independent Samples Test
Levene's Test for
Equality of Variances
t-test for Equality of Means
F Sig. t df Sig. (2-
tailed)
Mean Difference
Std. Error
Difference
95% Confidence Interval of the
DifferenceLower Upper
ICT Acceptance
Equal variances assumed
1.768
.191 2.23 42 .03
0 .3925 .17501
.03935
.74571
Equal variances not assumed
2.22 36.45 .033 .3925 .1774
9.0327
2.7523
4
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Thanks YouTerima Kasih
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