Symposium on Information & Computer Sciences (ICS 2011), 28 June 2011, Sunway Pyramid

1. A Confirmatory Factor Analysis on
Task-Technology Fit for a Student Portal
Norshidah Mohamed1
norshidah@ic.utm.my
http://www.ibs.utm.my
Muna Azuddin2
munaazuddin@gmail.com
Nor Shahriza Abdul Karim1
nshahriza@ic.utm.my
Ramlah Hussein3
ramlahh@sunway.edu.my
1International Business School, Universiti Teknologi Malaysia
2Department of Information Systems, International Islamic University Malaysia
3School of Computer Technology, Sunway University
Symposium on Information & Computer Sciences (ICS 2011)
28 June 2011
Sunway Pyramid

2. OUTLINE
• Introduction
• Literature review
• Methodology
• Findings
• Conclusion

3. INTRODUCTION
• Portal derives from the Latin word porta i.e.
something that will be passed in order to get to
another place.
• Web-based portal assists Web users by leading
them to the ultimate location of their choice (Clarke
and Flaherty, 2003).
• A system that gathers a variety of useful
information resources into a single one-stop Web
page (Krishnamurthya and Chan, 2005)

4. INTRODUCTION
Research Question:
What are the predictors of
Task-Technology Fit for a student portal?

5. LITERATURE REVIEW
Definition: Task-Technology Fit measures the degree to which
a technology assists users in performing their tasks (Goodhue
and Thompson, 1995) .
Context of prior Findings Authors
studies
Online shopping Task-technology fit was strongly Klopping and
associated with perceived usefulness McKinney (2004)
Learning Task-technology fit was an influencing McGill and Klobas
Management System factor in expected (2009)
(LMS) consequences of LMS use, attitudes
towards LMS use,
perceived impacts on students’
learning and students’
grades

6. LITERATURE REVIEW ..CONT’
Context of prior Findings Authors
studies
Hotel guest • Task and technology characteristics Schrier et al.
empowerment are positively and significantly related (2010)
technology (GET) to fit
• Users’ experiential characteristics are
negatively and significantly
associated to fit.

7. METHODOLOGY
Context of Study
• Undergraduate students as research
participants
• Public institution of higher learning in
Malaysia
• Web-portal manages the information among
students, academic personnel
• Been in implementation since 2006
• Developed and currently managed by the
university’s Information Technology Division

8. METHODOLOGY .. CONT’
Population and Sample
• Population – approximately 8,000 students at
three faculties
• Respondents – 570 students
• Cluster sampling based on courses offered in
a particular semester

9. METHODOLOGY .. CONT’
Instrument
Adapted from Klopping and McKinney (2004)
Code Item Descriptions
Task1 Sufficiently detailed student information is maintained in the Student
Portal.
Task2 Information about services for students is obvious in the Student
Portal.
Task3 I can get information about services for students quickly and easily
from the Student Portal when I need it.
Task4 The information about services for students that I need is displayed
in a readable and understandable form in the Student Portal.
Task5 The information about services for students maintained in the
Student Portal is what I need to carry out my tasks as a student.
Task6 The information about services for students is stored in so many
forms in the Student Portal that it is hard to know how to use it
effectively.

10. DATA ANALYSIS
• AMOS Version 16
• Convergent validity is established if the
loadings of the measures to their
respective constructs are at least 0.60
(Bagozzi and Yi)
• All squared multiple correlations (R-
square) must be at least 0.40 (Bollen
1989)

11. FINDINGS
Loading values
Square multiple
correlation values

12. FINDINGS .. CONT’
• Top three predictors come from Task2,
Task3, Task4
Code Item Descriptions
Task2 Information about services for students is obvious in the Student
Portal.
Task3 I can get information about services for students quickly and easily
from the Student Portal when I need it.
Task4 The information about services for students that I need is displayed
in a readable and understandable form in the Student Portal.
• Answer to research question: All items
except Task6 are predictors.

13. FINDINGS .. CONT’
GOODNESS OF FIT INDICES
Fit measure Recommended value Value for the research
model
Before MI After
MI
2 56.01 15.22
Degrees of freedom 9 4
(df)
2 /df <3 6.22 3.81
p-value >.05 .00 .00
GFI >.90 .96 .99
Adjusted GFI >.90 .91 .96
Normed fit index >.90 .95 .99
(NFI)
Relative fit index >.90 .92 .97
(RFI)
Incremental fit index >.90 .96 .99
(IFI)

14. FINDINGS .. CONT’
GOODNESS OF FIT INDICES
Fit measure Recommended value Value for the research
model
Before MI After
MI
Tucker Lewis index >.90 .93 .97
(TLI)
Comparative fit index >.90 .96 .99
(CFI)
Root mean square <.08 .11 .07
error of
approximation
(RMSEA)
Closeness of fit >.05 .00 .12
(PCLOSE)
Root mean square <.08 .02 .01
residual (RMR)

15. CONCLUSION
CONTRIBUTIONS
• Support prior researches in other contexts
of studies & in other countries
• Added new knowledge that model is valid
& reliable in Malaysian higher education
environment for a student portal
• Application of instrument for practice

16. CONCLUSION
LIMITATIONS
• Cross-sectional approach
• Only undergraduate students at three
faculties as research participants