This document summarizes a research study that analyzed citations related to e-learning quality from 2003 to 2012 to identify trends in the field. The study analyzed over 35,000 citations from 1,647 documents indexed in the Social Science Citation Index and Science Citation Index databases. Key findings included: 1) The top 10 most cited journals covered disciplines like education, medicine, management, and information science. 2) The most frequently cited works from 2003-2007 focused on machine learning, medicine, education, and statistics. From 2008-2012, works focused more on acceptance, satisfaction, effectiveness and success of e-learning and information technology. 3) The most cited authors from 2003-2007 conducted research across

1. Research trends in the field of e-learning quality, 2003-2012:
A citation analysis
Chin-Hsiu Tai1
, Che-Wei Lee2
, Yender Lee3
1
Graduate School of Business and Operations Management, Chang Jung Christian University, Tainan, Taiwan,
a8646165@yahoo.com.tw
2
Department of Administration and Policy Studies, University of Pittsburgh, Pittsburgh, Pennsylvania, USA,
chl138@pitt.edu
3
Graduate School of Business and Operations Management, Chang Jung Christian University, Tainan, Taiwan,
mcgill_lee@yahoo.com
Keywords: e-learning quality, research trends, citation analysis, informetrics
Abstract - This paper applies the citation analysis to identify
research trends in the field of e-learning quality, based on the
Social Science Citation Index (SSCI) and Science Citation
Index (SCI) databases from 2003 to 2012. To do this, 35,482
citations of 1,647 documents identified from SSCI and SCI
texts were analyzed. Results showed that research trends
varied rapidly and richly in many disciplines between the two
time periods (2003-2007 and 2008-2012). This study may be
of benefit to scholars seeking to understand the literature
surrounding e-learning quality and explore promising
research questions.
1. Introduction
In the field of e-learning, although recent decades have
seen growing significance placed on learning modules, and
the suitability, practices, employment, and the impact on
various facets of today’s education [1-4], more recently
research interests have shifted to focus on quality
enhancement, relations, and perceptions of e-learning [5,6].
However, the result of these qualitatively preliminary reviews
seems to oversimplify the scope of e-learning quality within
education. Few studies [7] systematically and quantitatively
examine the research trends in the field of quality in e-
learning from 2003 to 2012. Even fewer use citation analysis
[8,9,10] to investigate the interdisciplinary development of
research into the field of e-learning quality. Here we assume
that there has been a dramatic proliferation of, and a shift in,
patterns of research on e-learning in the twenty-first century.
This article applies citation analysis to investigate the most
frequently cited authors and the references on e-learning
quality from the Social Science Citation Index (SSCI) and
Social Citation Index (SCI) databases over the past ten years
to identify research trends. It also, however, goes further, by
reviewing the cross-disciplinary status of research on e-
learning quality. In this study, research trend was defined as
having three components: (1) highly cited journals, (2) the
most frequently cited works, and (3) the most frequently cited
authors. With this new information, it is hoped that scholars
of e-learning research may rapidly, efficiently, and accurately
identify the documented classic (must-read, best-quality, and
widely-cited) texts and discover the most influential scholars
in this domain. Three primary research questions guide this
study: (1) Which journals were cited the most from 2003 to
2012? (2) Which works were the most frequently cited in
2003-2007 compared to 2008-2012? (3) Which authors were
the most frequently cited in 2003-2007 compared to 2008-
2012?
2. Methods
2.1 Research Design
The citation analysis was derived from the methodology of
informetrics—also known as bibliometrics or scientometrics
[8,9,10], and was used to identify research trends in the field
of e-learning quality. Based on our assumption that studies of
e-learning quality over the last decade had become a
dominant trend in many disciplines, the time period was set
as 2003-2012 and divided in half (2003-2007 and 2008-2012)
for comparisons of citations to determine the dynamics of
research on e-learning quality. A database relating to studies
on e-learning quality was built for citation analysis by
retrieving data from Institute for Scientific Information (ISI)
Citation Indexes databases [11,12], consisting of three sub-
databases: (1) 2003-2012 document citations; (2) 2003-2007
author and document citations; and (3) 2008-2012 author and
document citations.
2.2 Data Sources
The data were retrieved from Science Citation Index (SCI)
and Social Science Citation Index (SSCI), both published by
the Institute for Scientific Information (ISI) Citation Indexes
of Thomson Reuters. SCI and SSCI currently cover over
6,700 leading scholarly journals (3,700 from SCI, 3,000 from
SSCI), representing 150 disciplines (100 from SCI, 50 from
SSCI) [13,14]. These two databases also provided the ISI
Journal Citation Reports (JCR) [11,12], which “offers a
systematic, objective means to critically evaluate the world’s
leading journals, with quantifiable, statistical information
based on citation data” [15], for helping us to see the journals
that were the most frequently used or cited.
Proceedings of the 19th ISSAT International Conference on Reliability and Quality in Design
August 5-7, 2013 - Honolulu, Hawaii, U.S.A.

2. We included journal articles, books, book reviews, reviews,
conference programs and proceedings, and editorial materials
in this study. There were 23,577 document citations 2003-
2012. With 18,472 articles, there were 8,807 journals 2003-
2007 and 14,164 authors. In 2008-2012 there were 45,964
articles, 17,626 journals, and 32,799 authors.
2.3 Data Collection
We used the keyword “e-learning quality” to search the
Web of Science from Thomson Reuters’ Web of Knowledge
[16], limiting the timespan of results to 2003-2007 and 2008-
2012 respectively. Search results were refined into the
disciplinary categories of Education & Educational (SSCI);
Education, Science Disciplines (SCI); Health Care Sciences
& Services (SCI); Medicine, General & Internal (SCI);
Management (SSCI); Information Science & Library (SCI);
and Multidisciplinary Sciences (SCI). Finally, 1,647 texts—
including journal articles and books—cited in 50,826
publications were retrieved from the initial 35,482 pool of
works. Citation counts, journal information, article titles,
publication dates, authors’ names, and attributed disciplines
were tabulated using Microsoft Excel 2010, divided in the
two periods of 2003-2007 and 2008-2012, and the top 10
most highly journals, cited references, and authors were
selected.
2.4 Data Analysis
By ranking the top 10 highly cited journals, references, and
authors according to citation counts, the relationships
between publications and the impact that particular references
and authors may have had on the subsequent development of
e-learning quality research can be discovered. Journals were
ranked by how frequently they were cited journals from 2003
to 2012. Their impact factor (IF) [17] was obtained from JCR,
and serves as a measure indicator of journal quality. It is
determined based on the average number of citations of works
published by the journals. The SCI/SSCI-generated rankings
highlight the status of the specific journal in respective
subject categories. The top 10 most highly cited works were
further classified into some disciplines in terms of their
article or book titles. The current working locations, areas of
expertise of the top 10 most frequently cited authors identified
were gathered from the authors’ professional websites,
available curriculum vitae, and representative publications.
3. Results
3.1 Which journals were cited the most?
Table I shows the top 10 highly cited journals in e-learning
quality from 2003 to 2012, in frequency order. The nine
journals other than Nature were cited over 200 times in the
past decade. According to the 2011 JCR Science Edition [11]
and Social Science Edition [12], Table II shows that these
journals associated with e-learning quality can be classified
into seven subject categories, and provides the IF and the
journal’s rank within a specific category or discipline.
TABLE I. THE TOP 10 HIGHLY CITED JOURNALS, 2003-2012
Rank Journal Title Database
Publisher’s
Country
Citation
Count
1 Computers & Education SSCI UK 425
2 JAMA-Journal of the
American Medical
Association
SCI USA 362
3 Management Science SSCI USA 297
4 British Medical Journal SCI UK 268
5 Academic Medicine SCI USA 262
6 MIS Quarterly SSCI USA 243
7 Science SCI USA 223
8 New England Journal of
Medicine
SCI USA 213
9 Medical Education SCI USA 212
10 Nature SCI UK 195
TABLE II. CATEGORIES, IMPACT FACTOR, AND RANK OF THE TOP 10
HIGHLY CITED JOURNALS, 2003-2012
Category Journal Title (Abbreviation)
Impact
Factor (IF)
Ranka
Education &
Educational
(SSCI)
 Computers & Education (CE) 2.261 7/206
Education,
Science
Disciplines
(SCI)
 Academic Medicine (AM) 3.524 1/33
 Medical Education (ME) 3.176 2/33
Health Care
Sciences &
Services (SCI)
 Medical Education (ME) 3.176 8/76
Medicine, General
& Internal (SCI)
 New England Journal of
Medicine (NEJM)
53.298 1/155
 JAMA-Journal of the
American Medical
Association (JAMA)
30.026 3/155
 British Medical Journal
(BMJ)
14.093 6/155
Management
(SSCI)
 MIS Quarterly (MISQ) 4.447 6/168
 Management Science (MS) 1.733 48/168
Information
Science &
Library (SCI)
 MIS Quarterly (MISQ) 4.447 1/83
Multidisciplinary
Sciences (SCI)
 Nature (NATE) 36.280 1/56
 Science (SINE) 31.201 2/56
a. This rankings was published by SSCI/SCI databases. “/” means “out of,” for example,
7/206 = the journal was ranked 7th out of 206 journals in the specific category.
3.2 Whose texts were the most frequently cited?
Table III presents the top 10 highly cited works from 2003
to 2007. Only two of the most frequently cited works are
journal articles; the others are books. These books and journal
articles highlight the following core research topics and
disciplines that trended in the field of e-learning quality from
2003 to 2007, including (1) Machine: theory of machine
learning [18,22,24]; (2) Medicine: neural networks [20,24];
(3) Education: cognition learning, situated learning (or a
model of learning in a community of practice) [21,23,26]; and
(4) Statistics: statistical pattern recognition [19,24,25].
TABLE III. THE TOP 10 HIGHLY CITED REFERENCES, 2003-2007
Rank Reference
Citation
Count
1 Mitchell, 1997 [18] 9
1 Vapnik, 1995 [19] 9
3 Bishop, 1995 [20] 8
3 Lave and Wenger, 1991 [21] 8
3 Quinlan, 1993 [22] 8
3 Wenger, 1998 [23] 8
7 Duda, Hart, and Stork, 2001 [24] 6
7 Vapnik, 1998 [25] 6
9 Brown, Collins, and Duguid, 1989 [26] 5

3. 9 Davis, et al., 1999 [27] 5
Table IV presents the top 10 frequently cited publications
from 2008 to 2012. Citation counts were notably higher than
the previous five year period, ranging from 15 to 25. Only
Cohen’s [31] work is a book, the other nine are journal
articles. The research trends in this period keep e-learning
quality mainly in the two fields of: (1) Statistics: structural
equation models, and statistical power analysis for behavioral
sciences [28,31]; and (2) Medicine: e-learning in medical
education [37]. However, new research directions related to e-
learning quality have emerged from these works, introducing
a focus on studies of acceptance [32,33], satisfaction [30,34],
effectiveness [36], and success [29,35] of e-learning,
computer, and information technology and systems.
TABLE IV. THE TOP 10 HIGHLY CITED REFERENCES, 2008-2012
Rank Reference
Citation
Counts
1 Fornell and Larcker, 1981 [28] 25
2 DeLone and McLean, 2003 [29] 20
2 Wang, 2003 [30] 20
4 Cohen, 1988 [31] 19
5 Davis, Bagozzi, and Warshaw, 1989 [32] 18
5 Davis, 1989 [33] 18
7 Sun, et al., 2008, [34] 17
8 DeLone and McLean, 1992 [35] 16
8 Piccoli, Ahmad, and Ives, 2001 [36] 16
10 Ruiz, Mintzer, and Leipzig, 2006 [37] 15
3.3 Who were the most frequently cited authors?
Table V shows the top 10 highly cited authors between
2003 and 2007. Five of these ten authors work in the United
States of America (USA), even though they are originally
from other countries. Others work in Canada, Germany,
India, the United Kingdom (UK), and the Netherlands. By
further examining these authors’ areas of expertise, we
discovered that work relating to e-learning quality was
integrated into the research trends of the following six
disciplines in this period: (1) Information Management; (2)
Medicine; (3) Computer Science and Electrical Engineering;
(4) Education; (5) Mechanics; and (6) Food and Water
Microbiology.
TABLE V. THE TOP 10 HIGHLY CITED AUTHORS, 2003-2007
Rank Name, Degree, & Area of Expertise
Country of
Residence
Citation
Count
1 Barker, Kathryn Chang, Ph.D. in
Educational Administration and
Policy, e-learning quality standards
and certification; strategies to
transform learning systems; future
education consulting services
Canada 19
1 Schiffman, Susan S., Ph.D. in
Education, development of
instrumentation and sensors to assess
sensory and cognitive functioning in
humans
USA 19
3 Vapnik, Vladimir N., Ph.D. in
Statistics, machine learning
algorithms; the support vector
machine
USA 17
4 Khoshgoftaar, Taghi M., Ph.D. in
Computer & Electrical Engineering
and Computer Science, software
engineering; data mining and machine
learning; computational intelligence;
USA 16
computer security & instruction
detection systems
5 Stevenson, Richard J., M.D. in
Pediatric and General Surgery
(USA/internal medicine; pediatrics)
USA 15
5 Streufert, Siegfried, Ph.D. in
Experimental (Social) Psychology,
psychology; management; medicine
and pharmacology
USA 15
7 Beg, Mirza Mohd Sufyan, Ph.D. in
Computer Technology, computer
architecture; parallel and distributed
computing; high performance data
mining; web searching; fuzzy logic
and systems; genetic algorithms;
question answering systems; natural
language processing
India 14
8 Blum, Jochen, Ph.D. in Neurosurgery,
biomechanics; intramedullary rod or
nail; trauma surgery and orthopedics
Germany 13
8 Meyer, Jan H.F., Ph.D. in Education,
threshold concept; student learning;
approaches to teaching inventory
UK 13
8 Mossel, David Alexander Antonius,
Ph.D. in Food and Water
Microbiology, microbiology of foods
The
Netherlands
13
Table VI presents the top 10 highly cited authors from 2008
to 2012. In this group, eight scholars are based in the USA
and two are in Taiwan. These authors have conducted
research on e-learning quality primarily in five disciplines:
(1) Information Systems and Management; (2) Medical
Informatics; (3) Psychology; (4) Marketing; and (5)
Economics.
TABLE VI. LIST OF THE TOP 10 HIGHLY CITED AUTHORS, 2008-2012
Rank Name, Degree, & Area of Expertise
Country of
Residence
Citation
Count
1 Cohen, Jacob, Ph.D. in Clinical
Psychology, statistical analysis in the
behavioral sciences; psychology
USA 46
1 Davis, Fred D., Ph.D. in Management,
user acceptance of information
technology; computer training and skill
acquisition; computer-assisted decision
making; managing emerging
technologies
USA 46
3 Venkatesh, Viswanath, Ph.D. in
Information Systems, diffusion of
technologies in organizations and
society; management information
science; organizational behavior and
human decision; medical informatics;
human-computer studies
USA 45
4 DeLone, William H., Ph.D. in
Computers and Information Systems,
computers and information systems
USA 40
5 Wang, Yi-Shun (王怡舜), Ph.D. in
Information Management, information
technology and organizations; e-
learning; electronic commerce;
customer relationship management;
system dynamics
Taiwan 39
6 Cook, David A., M.D. in Medical
Education, USA/educational
technologies; clinical decision making;
assessment methods
USA 36
7 Stefano, George B., Ph.D. in
Neuroscience, neuroscience; medical
science; biological sciences
USA 32
8 Fornell, Claes G., Ph.D. in Economics,
customer satisfaction measurement and
customer asset management
USA 31

4. 9 Parasuraman, A., D.B.A. in Marketing,
services marketing; service quality
measurement and improvement;
technology’s role in marketing and
serving customers
USA 29
10 Liaw, Shu-Sheng (廖述盛), Ed.D. in
Technology Education, e-learning;
medical informatics
Taiwan 26
4. Discussion
Three of the top 10 highly cited journals from 2003 to 2012
are from the SSCI database, with the other seven from the
SCI database. E-learning quality research seems to develop
richly in the SCI disciplines, including Medicine, General &
Internal (JAMA, BMJ, and NEJM); Education, Scientific
Disciplines (AM and ME); Multidisciplinary Sciences (SINE
and NATE); and Health Care Sciences & Services (ME).
Seven publishers come from the USA and three from the UK.
SCI journals have a higher IF than those in SSCI. Except for
AM and ME, which have IFs of around 3, the other SCI
journals have IFs between 14 and 50. In contrast, all three
SSCI journals have an IF between 1 and 4. Five of seven SCI
journals were ranked in the top 3 in their respective subject
categories by JCR, while two of SSCI journals were ranked
within top 7.
As can be seen from Table III and Table IV, the authors
with highly cited works in the first five years of the decade
under study do not overlap with those of the latter five years.
This suggests that the field of e-learning quality has a rapid
turnover in author citation. From 2003 to 2007, Vladimir
Vapnik and Etienne Wenger were the only two authors with
more than one work included in the list of the top 10 highly
cited references. From 2008 to 2012, William DeLone and
Ephraim McLean co-authored two journal articles, and Fred
Davis also wrote two that were in the top 10 highly cited
references. Citation counts of the works were not affected by
the year in which the work was published. Nine works
published in the 1990s were still being highly cited in the
former five year period, whereas four works published in the
1980s were in the latter five year period.
The works included in Tables III and IV provide
researchers of e-learning quality studies with helpful
guidance in starting a literature review of how the field has
evolved over the past decade. The increase in citations more
recently suggests that interest in e-learning research is
growing. Highly ranked citations are frequently considered
field-defining titles, and become important pointers for how
the field develops. Table IV also shows that the field has
matured to the point of tackling the issues of acceptance,
satisfaction, effectiveness, and success of e-learning. This
evidence verifies the significance of our present research
focus on quality in e-learning. A comparison of Tables III and
IV reveals two patterns between the two five year periods.
First, way in which the highly cited works crossed different
disciplines in these two periods varied notably. Second, the
most frequently cited publications in the first five years had
fewer citations than those in the second five years.
There is a geographic distinction between the influential
authors in the first period and those in the second. In the first,
there are four non-Northern American scholars (from India,
Germany, the UK, and the Netherlands), whereas in the
second there are only two who are not based in North
America. American scholars thus increasingly dominated the
research directions in this field, but Taiwanese scholars’
research efforts are gaining attention and recognition.
Two major disciplines—Information Systems and
Management and Medicine—retained the dominant influence
in this field during the past decade. Nonetheless, disciplines
such as Psychology, Marketing, and Economics have more
recently gained some prominence in this field.
5. Conclusion
This study has demonstrated that research on e-learning
quality is expanding and gaining greater recognition in the
interdisciplinary literature besides education. Computers &
Education was the most cited journal from 2003 to 2012.
Mitchell’s [18] and Vapnik’s [19] works were the most
frequently cited references 2003-2007, while Fornell and
Larcker’s [28] was 2008-2012. Barker and Schiffman were
the most cited authors 2003-2007, while Cohen and Davis
rose to the top during the second period. Shifts in the
rankings of the most influential journals, works, and authors
from the first to the second five years indicate that various
topics within the field of e-learning quality develop rapidly
and from diverse fields. The highly ranked authors’
professional fields encompassed education, statistics,
computer and technology science, medicine, neuroscience,
psychology, microbiology, information management,
economics, and marketing. Although e-learning quality as a
researchable topic has been described in many divergent
disciplines to capture its multidimensionality, this study has
documented the more recent move towards the disciplines of
Psychology, Marketing, and Economics.
In this article, we have shown the emergence of e-learning
quality as a field of research, using citation count rankings to
map the relevant research trends. This paper contributes the
research trends that define the foci, topics, and historic value
of e-learning quality research. These highly cited journals,
works, and scholars have not just the greatest impact on the
evolution of e-learning quality studies, but also collectively
define the boundary of this field. The works and authors listed
here may usefully guide researchers as documented classic
texts and experts in the field.
6. References
[1]Elsabé Cloete. “Electronic Education System Model”;
Computers & Education, Vol. 36, Issue 2, 171-182, 2001.
[2]Maggie McPherson. “Developing Innovation in E-Learning:
Lessons to Be Learned”; British Journal of Educational Technology,
Vol. 36, No. 4, 585-586, July 2005.
[3]Tak-Wai Chan, Chin-Wei Hue, Chih-Yueh Chou, and Ovid
J.L. Tzeng. “Four Spaces of Network Learning Models”; Computers
& Education, Vol. 37, Issue 2, 141-161, Sep 2001.
[4]Ambjörn Naeve, Miltiadis Lytras, Wolfgang Nejdl, Nicolas
balacheff, and Joseph Hardin. “Advances of the Semantic Web for

5. E-Learning: Expanding Learning Frontiers”; British Journal of
Educational Technology, Vol. 37, No. 3, 321-330, May 2006.
[5]E.S.I. Ossiannilsson. “Quality Enhancement on E-Learning”;
Campus-Wide Information Systems, Vol. 29, Issue 4, 312-323,
2012.
[6]Javier Sarsa, and Rebeca Soler. “E-Learning Quality:
Relations and Perceptions”; International Journal of Information and
Communication Technology Education, Vol. 8, Issue 2, 46-60, April
2012.
[7]Meilun Shih, Jui Feng, and Chin-Chung Tsai. “Research and
Trends in the Field of E-Learning from 2001 to 2005: A Content
Analysis of Cognitive Studies in Selected Journls”; Computers &
Education, Vol. 51, Issue 2, 955-967, Sep 2008.
[8]Sean Eom. “Author Cocitation Analysis: Quantitative
Methods for Mapping the Intellectual Structure of an Academic
Discipline.” Information Science Reference, 2009.
[9]Henk F. Moed. “Citation Analysis in Research Evaluation.”
Springer, 2005.
[10] Eugene Garfield. “Citation Indexing—Its Theory and
Application in Science, Techonology, and Humanities.” John Wiley
& Sons, 1979.
[11] ISI (Institute for Scientific Information) Web of
Knowledge, Thomson Reuters. “2011 JCR (Journal Citation
Reports) Science Edition.” Accessed March 1, 2013. http://admin-
apps.webofknowledge.com/JCR/JCR?RQ= HOME.
[12] ISI Web of Knowledge, Thomson Reuters. “2011 JCR
(Journal Citation Reports) Social Science Edition.” Accessed March
1, 2013. http://admin-apps.webofknowledge.com/JCR/JCR?RQ=
HOME.
[13] Thomson Reuters. “Science Citation Index.” Accessed
March 2, 2013. http://thomsonreuters.com/
products_services/science/science_products/a-
z/science_citation_index/.
[14] Thomson Reuters. “Social Science Citation Index.”
Accessed March 2, 2013. http://thomsonreuters.com/
products_services/science/science_products/a-
z/social_sciences_citation_index/.
[15] Thomson Reuters. “Web of Knowledge Factsheet.”
Accessed March 2, 2013.
http://thomsonreuters.com/content/science/pdf/Web_of_Knowledge
_factsheet.pdf.
[16] Thomson Reuters. “Web of Knowledge: All Databases.”
Accessed March 3, 2013.
http://apps.webofknowledge.com/WOS_GeneralSearch_input.do?pr
oduct=WOS&search_mode=GeneralSearch&SID=IE@PIFHeicGEN
abj9bH&preferenceSaved=&highlighted_tab=WOS.
[17] Thomson Reuters. “The Thomson Reuters Impact Factor.”
Accessed March 7, 2013. http://thomsonreuters.com/
products_services/science/free/essays/impact_factor/.
[18] Tom M. Mitchell. “Machine Learning.” McGraw-Hill,
1997.
[19] Vladimir N. Vapnik. “The Nature of Statistical Learning
Theory.” Springer, 1995.
[20] Christopher M. Bishop. “Neural Networks for Pattern
Recognition.” Oxford University Press, 1995.
[21] Jean Lave and Etienne Wenger. “Situated Learning:
Legitimate Peripheral Participation.” Cambridge University Press,
1991.
[22] J. Ross. Quinlan. “C4.5: Programs for Machine Learning.”
Morgan Kaufmann, 1993.
[23] Etienne Wenger. “Communities of Practice: Learning,
Meaning, and Identity.” Cambridge University Press, 1998.
[24] Richard O. Duda, Peter E. Hart, and David G. Stork.
“Pattern Classification.” Wiley, 2000.
[25] Vladimir N. Vapnik. “Statistical Learning Theory.”
Wiley, 1998.
[26] John Seely Brown, Allan Collins, and Paul Duguid.
“Situated Cognition and the Culture of Learning”; Educational
Resarcher, Vol. 18, Issue 1, 32-42, Jan 1989.
[27] Dave Davis, Mary Ann Thomoson O’Brien, Nick
Freemantle, Fredric M. Wolf, Paul Mazmanian, and Anne Taylor-
Vaisey. “Impact of Formal Continuing Medical Education: Do
Conferences, Workshops, Rounds, and Other Traditional
Continuing Education Activities Change Physician Behavior or
Health Care Outcomes?”; JAMA: The Journal of the American
Medical Association, Vol. 282, Issue 9, 867-874, Sept 1999.
[28] Claes Fornell, and David F. Larcker. “Evaluating
Structural Equation Models with Unobservable Variables and
Measurement Error”; Journal of Marketing Research, Vol. 18, Issue
1, 39-50, Feb 1981.
[29] William H. DeLone, and Ephraim R. McLean. “The
DeLone and McLean Model of Information Systems Success: A
Ten-Year Update”; Journal of Management Information Systems,
Vol. 19, Issue 4, 9-30, April 2003.
[30] Yi-Shun Wang. “Assessment of Learner Satisfaction with
Asynchronous Electronic Learning Systems”; Information &
Management, Vol. 41, Issue 1, 75-86, 2003.
[31] Jacob Cohen. “Statistical Power Analysis for the
Behavioral Sciences. 2nd ed.” Erlbaum Associates, 1988.
[32] Fred D. Davis, Richard P. Bagozzi, and Paul R. Warshaw.
“User Acceptance of Computer Technology: A Comparison of Two
Theoretical Models”; Management Science, Vol. 35, No. 8, 982-
1003, Aug 1989.
[33] Fred D. Davis. “Perceived Usefulness, Perceived Ease of
Use, and User Acceptance of Information Technology”; MIS
Quarterly, Vol. 13, No. 3, 319-340, Sep 1989.
[34] Pei-Chen Sun, Ray J. Tsai, Glenn Finger, Yueh-Yang
Chen, and Dowming Yeh. “What Drives a Successful E-Learning?
An Empirical Investigation of the Critical Factors Influencing
Learner Satisfaction”; Vol. 50, Issue 4, 1183-1202, May 2008.
[35] William H. DeLone, and Ephraim R. McLean.
“Information Systems Success: The Quest for the Dependent
Variable”; Information Systems Research, Vol 3, Issue 1, 60-95,
Mar 1992.
[36] Gabriele Piccoli, Rami Ahmad, and Blake Ives. “Web-
Based Virtual Learning Environments: A Research Framework and
A Preliminary Assessment of Effectiveness in Basic IT Skills
Training”; MIS Quarterly, Vol. 25, No. 4, 401-426, Dec 2001.
[37] Jorge G. Ruiz, Michael J. Mintzer, and Rosanne M.
Leipzig. “The Impact of E-Learning in Medical Education”;
Academic Medicine: Journal of the Association of American
Medical Colleges, Vol. 81, Issue 3, 207-212, Mar 2006.