A Confirmatory Factor Analysis on Task-Technology Fit for a Student Portal

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

Sunway Pyramid

Norshidah Mohamed1

norshidah@ic.utm.myhttp://www.ibs.utm.my

Muna Azuddin2

munaazuddin@gmail.comNor Shahriza Abdul Karim1

nshahriza@ic.utm.myRamlah Hussein3

ramlahh@sunway.edu.my1International Business School, Universiti Teknologi Malaysia

2Department of Information Systems, International Islamic University Malaysia3School of Computer Technology, Sunway University

OUTLINE

• Introduction• Literature review• Methodology• Findings• Conclusion

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)

INTRODUCTION

Research Question:What are the predictors of

Task-Technology Fit for a student portal?

LITERATURE REVIEW

Context of prior studies

Findings Authors

Online shopping Task-technology fit was stronglyassociated with perceived usefulness

Klopping and McKinney (2004)

Learning Management System (LMS)

Task-technology fit was an influencing factor in expectedconsequences of LMS use, attitudes towards LMS use,perceived impacts on students’ learning and students’grades

McGill and Klobas (2009)

Definition: Task-Technology Fit measures the degree to which a technology assists users in performing their tasks (Goodhue and Thompson, 1995) .

LITERATURE REVIEW ..CONT’

Context of prior studies

Findings Authors

Hotel guest empowermenttechnology (GET)

• Task and technology characteristics are positively and significantly related to fit • Users’ experiential characteristics are negatively and significantly associated to fit.

Schrier et al. (2010)

METHODOLOGY

• 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

Context of Study

METHODOLOGY .. CONT’

• Population – approximately 8,000 students at three faculties

• Respondents – 570 students• Cluster sampling based on courses offered in

a particular semester

Population and Sample

Code Item DescriptionsTask1 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.

METHODOLOGY .. CONT’

InstrumentAdapted from Klopping and McKinney (2004)

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)

FINDINGS

Loading values

Square multiplecorrelation values

FINDINGS .. CONT’

• Top three predictors come from Task2, Task3, Task4

• Answer to research question: All items except Task6 are predictors.

Code Item DescriptionsTask2 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.

FINDINGS .. CONT’

Fit measure Recommended value Value for the research model

Before MI After MI

2 56.01 15.22Degrees of freedom (df)

9 4

2 /df <3 6.22 3.81p-value >.05 .00 .00GFI >.90 .96 .99Adjusted GFI >.90 .91 .96

Normed fit index (NFI)

>.90 .95 .99

Relative fit index (RFI)

>.90 .92 .97

Incremental fit index (IFI)

>.90 .96 .99

GOODNESS OF FIT INDICES

FINDINGS .. CONT’

Fit measure Recommended value Value for the research model

Before MI After MI

Tucker Lewis index (TLI)

>.90 .93 .97

Comparative fit index (CFI)

>.90 .96 .99

Root mean square error of approximation (RMSEA)

<.08 .11 .07

Closeness of fit (PCLOSE)

>.05 .00 .12

Root mean square residual (RMR)

<.08 .02 .01

GOODNESS OF FIT INDICES

CONCLUSION

• 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

CONTRIBUTIONS

CONCLUSION

• Cross-sectional approach• Only undergraduate students at three

faculties as research participants

LIMITATIONS

THANK YOU