=Paper=
{{Paper
|id=None
|storemode=property
|title=Design Characteristics of Virtual Learning Environments: An Expert Study
|pdfUrl=https://ceur-ws.org/Vol-570/paper011.pdf
|volume=Vol-570
}}
==Design Characteristics of Virtual Learning Environments: An Expert Study==
https://ceur-ws.org/Vol-570/paper011.pdf
Design Characteristics of Virtual Learning Environments: An Ex-
pert Study
Daniel Mueller, Saarland University, Germany
d.mueller@mis.uni-saarland.de
Stefan Strohmeier, Saarland University, Germany
s.strohmeier@mis.uni-saarland.de
Abstract. Virtual Learning Environments (VLE) constitute the current
Information Systems (IS) category for electronically supported corporate
training and development. Frequently supposed advantages of using VLE
refer, for instance, to the efficiency, individuality, ubiquity, timeliness, and
task orientation of learning. However, a crucial precondition of realizing
such advantages is an appropriate systems design. Hence, the question
which specific design characteristics actually characterize successful VLE
is of specific interest for training and development practice. The current
paper therefore addresses design characteristics by conducting an expert
study which is based on a general theory of IS success and previous insights
of the literature. As a result, a set of relevant, well-defined design
characteristics is presented and discussed while implications for research
and practice are derived.
Keywords: Virtual Learning Environments, Design Characteristics, Expert
Study.
1 Introduction
For decades, electronic learning systems constitute the basic enablers of corporate e-
learning. Though designations as categorizations of such learning systems are rather
heterogeneous and also change over time, current systems can be pooled under the
rubric of Virtual Learning Environments (VLE), which can be understood as electronic
Information Systems (IS) for the administrative and didactical support of learning
processes in vocational settings by systematically providing corporate learners adequate
learning materials as well as corresponding collaboration facilities so as to develop
intended qualifications [e.g. 8, 42, 49]. The usage of such systems in corporate training
and development is commonly justified based on diverse advantages such as efficiency,
individuality, ubiquity, convenience, timeliness, cost efficiency and task orientation of
VLE-based learning [e.g. 15, 20, 41]. Such advantages may also explain the ever
increasing adoption of VLE in corporate training and development [e.g. 15, 19, 48].
However, the actual realization of such advantages crucially depends on several
preconditions, while the specific characteristics of the used VLE constitute a prominent
Strohmeier, S.; Diederichsen, A. (Eds.), Evidence-Based e-HRM? On the way to rigorous and relevant
research, Proceedings of the Third European Academic Workshop on electronic Human Resource
Management, Bamberg, Germany, May 20-21, 2010, CEUR-WS.org, ISSN 1613-0073, Vol. 570, online:
CEUR-WS.org/Vol-570/ , pp. 167-185.
© 2010 for the individual papers by the papers´ authors. Copying permitted only for private and academic
purposes. This volume is published and copyrighted by its editors.
aspect. It is evident that only adequately designed VLE will offer the promising
potential for success, while ill designed systems may even cause harmful disadvantages.
This directly focuses on design characteristics of VLE as a crucial aspect of learning
success. Technically [e.g. 18] as managerially oriented literature [e.g.6, 7, 45]
congruently understands design characteristics as the set of those inherent information
system properties, which determine IS success (while IS success is differently
conceptualized as net benefits, user acceptance, or actual usage, among others). Though
termed "design" characteristics, such properties critical to the success of VLE gain
practical importance for the entire process of developing or else procuring,
implementing and applying VLE in organizations. It is not surprising that design
characteristics firstly are relevant for developing new VLE. Here design characteristics
offer a framework of requirements which mandatorily must be met by the future system
to assure its quality. Given that corporate VLE are getting purchased more and more
from external vendors, design characteristic also are relevant for the systems
procurement, since they offer a valuable set of selection criteria. Beyond development
and procurement, design characteristics may also instruct the technical implementation
process by defining technical implementation goals. Finally, design criteria offer
suitable evaluation criteria for already applied VLE, and hence support the inspection
and improvement of existing systems. Given the wide-spread and still increasing usage
of VLE, design characteristics of VLE hence are of relevance for a broader group of
technical and managerial decision makers in corporate training and development.
The current paper therefore aims at elaborating general VLE design characteristics. An
expert study is conducted for this purpose. As a general foundation for the study
theoretical bases are discussed first. In order to contribute to cumulative research and to
integrate the expert study with previous findings subsequently a review of previous
research is conducted. Based on this, the method of the expert study is exposed and the
results are presented and discussed. Finally, implications for practice and research are
derived.
2 Expert Study
2.1 Foundation
As a clear explorative empirical method, expert studies usually are employed to gain
insights in topical domains which are theoretically not or at least not well developed and
hence, are not open to confirmative research. In certain respects, this applies also to
research into design characteristics of VLE. At least, there is no completely developed
theory of VLE design which would allow for a direct elicitation of the desired design
characteristics. However, alternative foundations may be found in more general theories
of – given the subject of the study – in the area of general IS design or general IS
success. In the recently flourishing area of IS design the necessity of a general theory of
IS design is well recognized [e.g. 14]. However, so far rather procedural models of
design research have been offered [e.g. 14, 35], while an explicit theory of IS design,
which directly unfolds design characteristics or at least allows to derivate design
characteristics, is missing at present. Conversely, in the area of general IS success there
are some recognized theories [e.g. 7, 45]. Since explaining success of IS such theories
mandatorily present a set of success predictors. As long as such success predictors
constitute or at least refer to IS characteristics, these theories can also be used to found
design characteristic research. In view of this possibility, in particular the IS success
model (ISSM) [6, 7, 40] presents general success relevant IS characteristics and,
168
additionally, is repeatedly validated. Basically, ISSM offers three groups of success
predictors, namely, systems quality, information quality and service quality [6, 7].
Visibly, systems quality understood as a set of features which refers to the system as
such, and information quality, understood as a set of features which refers to the content
of the system, constitute system-related characteristics and hence, are appropriate for
design characteristics research. Service quality, however, understood as a set of features
which refers to the user support, does visibly not constitute a characteristic of the
system itself, and hence is not appropriable. Transferred to VLE design characteristic,
the ISSM hence clarifies that system-related (features of the VLE as such) and
information-related (learning content of the VLE) constitute essential groups of design
characteristics. Being a general theory, ISSM however is not able to provide more
detailed information about VLE design characteristics. It is hence the task of the expert
study to ascertain systems as information-related design characteristics of VLE
empirically.
2.2 Review
In order to add to cumulative research and integrate the expert study with previous
findings a comprehensive review of previous research in design characteristics of VLE
was conducted. The review considered studies which directly deal with design
characteristic of VLE in an empirical or conceptual way. Extensive searches of
electronic databases (EBSCO, ScienceDirect, and Scopus) as well as of selected
journals and conference websites were carried out to identify appropriate studies.
However, in order to assure the quality of results only outlets with double blind peer-
review were taken into account. To map existing studies comprehensively, a time frame
of 20 years (1989-2009) was analyzed. Based on this procedure 25 relevant studies
could be identified (these studies are marked with an asterisk in the references section
and are summarized in Appendix 1). The analysis of VLE design characteristics
identified within these studies yielded several interesting results.
Firstly and unexpectedly, a plethora of over thirty different design characteristics could
be identified (for details see Appendix 1). Though this may be judged as ample results
of previous research, this abundance also represents a certain problem like an increasing
number of design characteristics detracted from there applicability and usefulness.
Hence, future research should strive for a limited set of major design characteristics
rather than amassing a maximum of design characteristics. Secondly, as predicted by
the ISSM, all identified design characteristics could by classified as either system-
related or information-related, while quite frequently systems quality and information
quality were presented as design characteristics. Whereas this constitutes a consent
concerning the general design characteristics, there is dissent concerning more concrete
design characteristics within these groups. This heterogeneity adds to the problem of the
mere number, since it is still unclear which concrete design characteristics actually are
relevant for success. Hence, it is necessary to validate design characteristics to attain a
set of resilient characteristics. Thirdly, the design characteristics found are of rather
different granularities, understood as the grade of operativeness and detailedness of
design characteristics. Basically, very general, coarse-granular characteristics such as
the mentioned "systems quality" or "information quality" and rather medium-granular
characteristics such as "personalization" or "clear terminology" can be differentiated,
while fine-granular, detailed, i.e. very specific design characteristics could not be
detected. Granularity of design characteristics evidently is of major importance since
expressiveness and usability increase with granularity (for instance, ―develop/select/use
169
personalized VLE" constitutes a more expressive and usable statement than
―develop/select/use VLE with good systems quality‖). In view of this, at first glance one
may claim maximal granularity from the expert study, however increased specificity
commonly is aligned with a decreasing range of validity. Hence, to warrant general
validity the expert study may have to get by with a medium granularity. Fourthly, there
is a prevalent lack of explicit definitions of design characteristics (while there are some
exceptions). Since the design characteristic presented, such as ―perceived flexibility",
represent rather complex constructs which can be understood in quite different ways,
the lack of definition aggravates the understanding of design characteristics as well as
their further usage. It also complicates the detection of possible redundancies of
characteristics found in different studies such as ―personalization‖ and ―user
adaptation‖. Hence, the expert study mandatorily has to elaborate thorough and explicit
definitions of design characteristics.
In summary, previous research suggests a set of design characteristics which is copious,
of limited congruence, of different granularity, and frequently unclear in meaning. This
clearly justifies the necessity of the expert study. However, instead of just adding a
further unconnected study, the current state of knowledge is to be used as a base to
contrast but also enrich the expert study and thereby integrate it with previous work.
2.3 Method
To ascertain success relevant system- as well as information-related characteristics of
VLE with an expert study systematically, the Delphi method was considered as
promising approach [e.g. 11, 12, 13, 22]. Besides supporting practical forecasting and
practical decisions, the Delphi method is also appropriate for systematically analyzing
complex and multifaceted scientific topics that are not directly and easily accessible via
quantitative research approaches [e.g. 11]. To ascertain relevant design characteristics
systematically, a two-phased approach was performed.
Phase I was aimed at a general inquiry and categorization of generally imaginable
design characteristics. As a starting point of phase I, a group of appropriate experts was
to be appointed. Participants were selected based on different criteria, while it was
intended to arrange an international group of experts with extensive knowledge in the
design of VLE which is of diverse disciplinary provenience (computer science,
management, pedagogy, and psychology), and diverse institutional affiliation
(universities and private companies). The resulting group consisted of 13 international
experts with different affiliation and backgrounds (see Appendix). Subsequently, an
online-questionnaire was developed. Beside the provision of a general introduction into
the questionnaire, relevant terms such as VLE or design characteristic were thoroughly
defined in order to assure a consistent understanding of constructs and questions. In so
doing, the questions referred to the creation of a comprehensive list of design
characteristics in general, and to subsequently match this list to a categorization of
system- and information-related design characteristics of VLE. Balancing the trade-off
between specificity and validity it was asked for characteristics which were specific, but
generally valid. To avoid mere adjective lists with undefined and hence unclear
constructs, experts were explicitly encouraged to explain the stated design
characteristics in detail. The questionnaire was pre-tested and slightly modified based
on in-depth interviews with two experts. The online survey was carried out in autumn
2009, while all 13 experts participated.
A monitoring team of five independent researchers individually evaluated the results
obtained in phase I. In particular, based on the construct explanations synonymous
170
design characteristics were identified and adjusted, the adjusted set of design
characteristics was summarized respectively aggregated according to the principles of
―summarizing content analysis‖ [31], and finally, general definitions for the
summarized design characteristics were derived from the expert explanations. In a
subsequent group discussion, individual results of the monitoring team members were
mutually adjusted, while there was an initial high degree of inter-coder reliability [31]
within the monitoring team anyway.
During the preparation of phase II the result list of design characteristics of phase I was
compared with the results of the review of previous work. As there was substantial
agreement concerning several design characteristics, the result list from phase I missed
some of the design characteristics that proved to be significant for success. To be more
concrete, experts did not mention ―multimodal‖ [30, 36, 38], ―accessible‖ [30],
―appealing‖ [3, 4, 16, 27, 38], ―reliable‖ [27, 30, 47], ―secure‖ [30] and ―structured‖ [3,
36]. To test also the relevance of these characteristics, they were added to the results of
phase I. The resulting list of adjusted, aggregated, enriched, categorized and defined
design characteristics constituted the base of the second online-questionnaire. The 13
experts this time were asked to rank the presented system- and information-related
design characteristics of VLE from highest (rank 1) to lowest (rank n) priority for
success. The resulting priority lists were summarized by calculating means and standard
deviations of the respective rank positions.
2.4 Results
Interim results of phase I firstly revealed an unadjusted list of 55 design characteristics
(31 system-related, 24 information-related). This list was successively reduced by
adjustment of synonyms to 31 design characteristic (13 system-related, 16 information-
related) and the summarizing of design characteristics to 16 design characteristics (10
system-related, 6 information-related).
VLE Design Characteristic
A. System-Related
Reliable A1. 3.08 (1.44)
Secure A2. 4.38 (3.52)
Learning-Process-Supportive A3. 4.46 (3.13)
Interactive A4. 4.77 (3.11)
Appealing A5. 5.08 (2.25)
Transparent A6. 5.15 (2.79)
Structured A7. 5.92 (2.22)
171
Standard-Supportive A8. 6.46 (2.79)
Accessible A9. 6.85 (2.15)
Platform-Independent A10. 7.62 (2.90)
B. Information-Related
Understandable B1. 2.23 (1.48)
Consistent B2. 2.92 (1.66)
Credible B3. 3.23 (1.30)
Challenging B4. 3.54 (1.51)
Multimodal B5. 4.00 (1.78)
Enjoyable B6. 4.58 (1.44)
Table 1: Means and Standard Deviations of VLE Design Characteristics Ranks.
As depicted this list was enriched with 7 literature-based characteristics (6 system-
related, 1 information-related).
Final results are rendered in Table 1 and 2. Table 1 firstly depicts the results of the
prioritization process in phase II by presenting the mean values and the standard
deviations (in brackets).
The derived definitions of these characteristics are presented in Table 2, while each
definition is illustrated with selected statements of the literature review and/or experts to
make their origin more transparent.
Design
Definition Source Exemplary Statement
Characteristic
A. System-Related
VLE are reliable, if their
end-users/learners can ―Whenever I use the e-
literature
Reliable apply it without learning tool, it always
review
technology owed works correctly.‖ [30]
disturbances.
172
VLE are secure, if the
system itself as well as
unauthorized users cannot
modify or delete the
learners' personal profile literature ―I trust the system security.‖
Secure
data, respectively their review [30]
learning history, progress
(i.e. learning outcomes),
and corresponding
resources.
VLE are learning-process-
supportive if they support
the provision of (further)
learning activities and/or
materials with their
Learning- inherent information (e.g.
expert ―Workflow-management
Process- activity description and/or
study component‖
Supportive instruction, etc.) according
to the learners‘ current
status in the unit of
learning, and help the
learners to coordinate audit
dates, group meetings, etc.
VLE are interactive if they ―[…] key to the learning
allow for learner-system- process are the interactions
(e.g. taking self-tests, among students themselves,
uploading assignments, literature the interactions between
Interactive
etc.), learner-learner-, review faculty and students, and the
and/or learner-teacher- collaboration in learning
communication and/or that results from these
collaboration (e.g. via interactions.‖ [34, 36]
173
audio/video conference, ―The core of learning
blackboard, chat, forum, remains a relationship
expert
etc.). between a learner and a
study
tutor. VLE must keep this
crucial factor in the loop.‖
VLE are appealing, if their ―Screen design is the way
literature
Appealing graphical user interface information is presented on
review
has a pleasant appearance. the screen.‖ [16, 23, 28]
―The e-learning system
VLE are transparent, if literature
allows the user to control
they allow the learners to review
his/her improvement.‖ [30]
keep an eye on their own
―The system enables users
and/or other learners‘
to trace why and how
learning history (i.e.
Transparent certain recommendations
completed and/or passed
expert are made, how much
learning activities of a unit
study personal data one allows the
of learning) and current
system to data mine
status in the learning
implicitly/explicitly to
process.
produce a user profile.‖
VLE are structured, if
learners can quickly detect
the allocated information
(e.g. learning resources
such as learning materials,
collaboration services, ―[…] the ease with which
literature
Structured assessment items, system- users can move around the
review
generated information such system.‖ [23]
as user guidance,
feedback, etc.) in,
respectively can easily
navigate the graphical user
interface.
174
VLE are standard-
supportive, if they
facilitate learning materials
which are compiled based
on approved eLearning
standards such as IMS
Standard- expert ―Interoperability and
Learning Design [17], or
Supportive study standards compliance‖
SCORM [1] as these
eLearning standards enable
learning materials to be
widely shared across VLE
which also support these
standards.
VLE are accessible, if
―The e-learning tool is
learners can access it literature
Accessible accessible according to my
according to their own review
own possibilities.‖ [30]
possibilities.
VLE are platform-
Platform- independent, if they run on expert ―VLE should be Web-
Independent a wide range of operating study based, not standalone.‖
systems.
B. Information-Related
The information provided ―Terminology refers to the
by VLE is understandable, literature words, sentences, and
if the words, sentences, review abbreviations used by a
and abbreviations applied system.‖ [23, 28]
within the learning
Understandable
materials are clear in
meaning (e.g. by use of expert ―Understandability vs.
definitions), easy to study complexity.‖
comprehend and easy to
read.
175
The information provided ―The use of terms
literature
by VLE is consistent, if the throughout the (E-library) is
review
learning materials consistent.‖ [16]
Consistent themselves are without
―Sequencing of learning
contradictions, coherent expert
objects, tasks, and
and presented in a logical study
assessments.‖
order.
The information provided
by VLE is credible, if they
―[…] how much one trust
originate from a
expert the credibility of the
Credible trustworthy source (e.g.
study material (i.e. it does not
teacher, certified and/or
convey wrong concepts)‖
reputable organizations,
etc.).
The information provided
by VLE is challenging, if
the learning materials ―For ambitious learners,
expert
Challenging contain difficult but focusing on learning
study
interesting tasks which objectives.‖
stimulate learners‘
curiosity to solve them.
The information provided
―The Web-based learning
by VLE is multimodal, if
system offers multimedia
the learning materials are literature
Multimodal (audio, video, and text)
presented in different review
types of (course) content.‖
media formats such as text,
[36]
audio, and video.
The information provided
―Positive user experience,
by VLE is enjoyable, if the
expert associated with pleasure,
Enjoyable learning materials
study fun, playability, and
provided do so in their
enjoyment.‖
own right aside from their
176
textual value, and
consequently make the
learning experience more
pleasant.
Table 2: Definitions, Sources and Exemplary Statements of VLE Design Characteristics.
2.5 Discussion
The present expert study provides a systematic set of well-defined, specific but
generally valid system- and information-related design characteristics based on the
ISSM and compatible to previous research results. Hence, the general objective of the
expert study could be satisfactorily achieved.
Findings concerning the system-related design characteristics show that ―reliable‖ was
unambiguously rated as the most important system-related design characteristic,
followed by ―secure‖, ―learning-process-supportive‖, ―interactive‖, ―appealing‖,
―transparent‖, ―structured‖, ―standard-supportive‖, ―accessible‖, and ―platform-
independent‖. It should be noted, ―interactive‖, ―appealing‖, and ―transparent‖ show
almost the same mean values, that may be a consequence of the prioritization procedure
within phase II as study participants were ―forced‖ to rank the given design
characteristics even though they may have preferred similar priorities of different design
characteristics. However, the salient disagreement amongst study participants
concerning the relative importance of ―secure‖ (SD: 3.52) as the second important
system-related design characteristic of VLE in particular might be engendered by its
diverse understanding (―[…] the system itself as well as unauthorized users cannot
modify or delete the learners' personal profile data […]‖, etc.). The same may count for
―learning-process-supportive‖ (SD: 3.13), ―interactive‖ (SD: 3.11) as well as
―transparent‖ (SD: 2.79) and ―standard-supportive‖ (SD: 2.79). Once again, this result
may originate in the way the prioritization procedure was conducted. It is noticeable,
amongst the five system-related design characteristics considered to be the most
important ones, rank number one (―reliable‖), two (―secure‖), and five (―appealing‖) are
design characteristics from the literature review which were added subsequently. This
shows that even though study participants did not even mention these system-related
design characteristics within the first survey wave, they considered them as highly-
relevant system-related design characteristics of VLE. Thus, the prioritization of
preceding expert statements and theoretical-founded design characteristics proved to be
a feasible and promising approach. Hence, the set of system-related design
characteristics presented should always be under consideration when designing, and
evaluating VLE.
Regarding information-related design characteristics, findings show that
―understandable‖, is considered to be the most important design characteristic, followed
by ―consistent‖, ―credible‖, ―challenging‖, multimodal as well as ―enjoyable‖. It should
be pointed out that not similar to their system-related counterparts, all information-
related design characteristics show high levels of agreement amongst study participants
regarding their relevance for VLE (SD spectrum: 1.30 - 1.78). Hence, when designing
and evaluating VLE one should consider the set of information-related design
characteristics presented.
177
To conclude, the results of the expert study presents a comprehensive set of VLE
specific information- and system-related design characteristics, which should be
considered when developing, purchasing, implementing or evaluating VLE.
3 Implications
The above-mentioned results should generally provide a basic starting point for future
research as design endeavors, while there are some implications for research as well as
practice.
Concerning research implications, firstly, some further theoretical deliberations may
improve future research. The used ISSM is able to roughly categorize relevant design
characteristics, but however does not allow to deduce directly specific design
characteristics. This likely applies to further imaginable theoretical foundations, in
particular to the prominent TAM-approach, what could be proved within the frame of
the literature review (see e.g. the TAM-based studies of [3, 38]). Again, the basic TAM
does rarely directly propose concrete design characteristics. In order to overcome this
theoretical gap, more recent theoretical developments that are orientated towards design
and intervention (e.g. the TAM 3 offered by [45]) may offer deeper foundations. In
addition, also amalgamations of such approaches with the ISSM may be worth of a trial
(see the example in [32]). Furthermore, given that expressiveness and usability of
design characteristics increase with growing specificity, future research should aim at
increasing specificity of design characteristics, however without losing general validity.
One imaginable way is to work out different facets of the design characteristics by
constituting sub-characteristics. For instance, based on the definitions elaborated certain
sub-characteristics of ―flexible‖, ―learning-process-supportive‖ or ―transparent‖ could
be established. As an important aspect considered by one previous study [30] and
confirmed in the expert study, possible interdependencies of design characteristics
should be taken into account. Basically, design characteristics may not be arbitrarily
combinable for logical and/or technical reasons [10], hence, future research should also
strive for (in-)compabilities of design characteristics found. This also entails a question
that has not been tackled till now, whether different system- and information-related
design characteristics contribute rather individually and independently to VLE success,
or whether whole bundles or entire configurations of design characteristic are triggering
success. Moreover, given the benefits of an experimental design, such as controlling
relevant while excluding confounding variables, ensuring direct relevant experiences of
respondents, and, particularly enabling the manipulation of specific design
characteristics [21], experimental designs seem to be a promising approach to ascertain
and evaluate relevant design characteristics empirically (cf. the pioneering work of [36]
who conducted an offline experiment to determine relevant design characteristics).
Finally, given the costs and duration of developing prototypes, and, all the more, full
versions of a VLE, it would be highly beneficial if relevant design characteristics could
be ascertained as early as possible, in order to avoid misconceptions and failure [5].
Hence, the usage of simple prototypical models (paper prototypes, video mockups, etc.)
of the system planned may allow ascertaining relevant characteristics in very early
phases of the corresponding software development process [32].
Additionally, the results of the study yield some implications for practice. Managerial
and technical decision-makers in the process of developing new, selecting pre-packaged
VLE-software, or evaluating and improving already adopted VLE are offered a valuable
general (check-)list of criteria relevant for success. Beyond, with a particular view to
information-related design characteristics, learning designers and teaching staff may
178
profit from their application while preparing their learning materials. Hereby,
information-related design characteristics could also be understood as a checklist in how
far their learning materials fulfill the proposed requirements (e.g. understandable,
consistent, and credible learning materials).
Refining and customizing this (check-)list towards individual corporate settings and
subsequently considering the list may lead to practical VLE design- and selection-
processes which minimize learner resistance, increase learner satisfaction, and support
overall learning success.
4 Conclusions
Within this paper a comprehensive literature review and an initial expert study were
carried out yielding a systematic list of well-defined system- and information-related
design characteristics of VLE. This hopefully will stimulate future research, especially
quantitative studies which evaluate and deepen the insights offered, but may also
instruct future practical development, selection and evaluation projects, while both
streams may finally contribute to improved VLE which support better corporate training
and development endeavors.
References
[1] ADL (2004), SCORM 4th Edition - Version 1.1 (Documentation), available at:
http://www.adlnet.gov/Technologies/scorm/SCORMSDocuments/2004%204th%20
Edition/Documentation.aspx, accessed on the 11th of April 2010.
[2] *Arbaugh, J. B. (2000). Virtual Classroom Characteristics and Student Satisfaction
with Internet-based MBA Courses, Journal of Management Education, 24 (1), 32-
54.
[3] *Chang, S.-C. & Tung, F.-C. (2008). An Empirical Investigation of Students‘
Behavioural Intentions to Use the Online Learning Course Websites, British
Journal of Educational Technology, 39 (1), 71–83.
[4] *Chiu, C.-M., Hsu, M.-H., Sun, S.-Y., Lin, T.-C. & Sun, P.-C. (2005). Usability,
Quality, Value and E-Learning Continuance Decisions, Computers & Education,
45, 399-416.
[5] Davis, F. D. & Venkatesh, V. (2004). Toward Preprototype User Acceptance
Testing of New Information Systems: Implications for Software Project
Management, IEEE Transactions on Engineering Management, 51 (1), 31-46.
[6] DeLone, W. H. & McLean, E. R. (1992). Information Systems Success: The Quest
for the Dependent Variable, Information Systems Research, 3 (1), 60-95.
[7] DeLone, W. H. & McLean, E. R. (2003). The DeLone and McLean Model of
Information Systems Success: A Ten-Year Update, Journal of Management
Information Systems, 19 (4), 9–30.
[8] Fry, H., Ketteridge, S. & Marshall, S. (2009): A Handbook for Teaching and
Learning in Higher Education: Enhancing Academic Practice, 3rd edition.
Routledge.
179
[9] *Fu, F.-L., Chou, H.-G. & Yu, S.-C. (2007). Activate Interaction Relationships
between Students Acceptance Behavior and E-Learning, in G. Dong, X. Lin, W.
Wang, Y. Yang, & J. Xu Yu (eds.): Joint 9th Asia-Pacific Web Conference
(APWeb 2007) and 8th International Conference on Web-Age Information
Management (WAIM 2007), LNCS 4505, 670–677.
[10] Galletta, D. F. & Lederer, A. L. (1989). Some Cautions on the Measurement of
User Information Satisfaction, Decision Sciences, 20 (3), 419–439.
[11] Grisham, T. (2009). The Delphi Technique: A Method for Testing Complex and
Multifaceted Topics, International Journal of Managing Projects in Business, 2 (1),
112-130.
[12] Haeder, M. (2002): Delphi-Befragungen: Ein Arbeitsbuch. VS Verlag für
Sozialwissenschaften.
[13] Haeder, M. & Haeder, S. (2000): Die Delphitechnik in den Sozialwissenschaften:
Mehtodische Forschungen und innovative Anregungen. Westdeutscher Verlag.
[14] Hevner, A. R., March, S. T., Park, J. & Ram, S. (2004). Design Science in
Information Systems Research, MIS Quarterly, 28 (1), 75–105.
[15] *Holsapple, C. W. & Lee-Post, A. (2006). Defining, Assessing, and Promoting E-
Learning Success: An Information Systems Perspective, Decision Sciences Journal
of Innovative Education, 4 (1), 67-85.
[16] *Hong, W., Thong, J. Y. L., Wong, W.-M. & TAM, K.-Y. (2001-2002).
Determinants of User Acceptance of Digital Libraries: An Empirical Examination
of Individual Differences and System Characteristics, Journal of Management
Information Systems, 18 (3), 97-124.
[17] IMS (2003), ‗IMS Learning Design Information Model - Version 1.0 (Final
Specification)‘, available at: http://www.imsglobal.org/learningdesign/ldv1p0/
imsld_infov1p0.html, accessed on the 11th of April 2010.
[18] ISO/IEC (2005), ‗ISO/IEC 25000: Software Product Quality Requirements and
Evaluation (SQuaRE)‘, available at: http://www.iso.org/iso/iso_catalogue/
catalogue_tc/catalogue_detail.htm?csnumber=35683, accessed on the 11th of April
2010.
[19] Johnson, R. D., Gueutal, H. & Falbe, C. M. (2009). Technolgy, Trainees,
Metacognitive Activity and E-Learning Effectiveness, Journal of Managerial
Psychology, 24 (6), 545—566.
[20] Kiser, K. (1999). 10 Things We Know so far about Online Training, Training, 36
(11), 66-74.
[21] Koenigstorfer, J. (2008): Akzeptanz von technologischen Innovationen:
Nutzungsentscheidungen von Konsumenten dargestellt am Beispiel von mobilen
Internetdiensten. Gabler.
[22] Landeta, J. (2006). Current Validity of the Delphi Method in Social Sciences,
Technological Forecasting and Social Change, 73 (5), 467-482.
[23] *Lee, G. T., Dahlan, N., Ramayah, T., Karia, N. & Hasmi Abu Hassan Asaari, M.
(2005). Impact of Interface Characteristics on Digital Libraries Usage, Malaysian
Online Journal of Instructional Technology, 2 (1), 1-9.
180
[24] *Lee, Y.-C. (2006). An Empirical Investigation into Factors Influencing the
Adoption of an E-Learning System, Online Information Review, 30 (5), 517-541.
[25] *Liaw, S.-S., Chang, W.-C., Hung, W.-H. & Huang, H.-M. (2006). Attitudes
toward Search Engines as a Learning Assisted Tool: Approach of Liaw and
Huang‘s Research Model, Computers in Human Behavior, 22, 177–190.
[26] *Liaw, S.-S. & Huang, H.-M. (2003). An Investigation of User Attitudes toward
Search Engines as an Information Retrieval Tool, Computers in Human Behavior,
19, 751–765.
[27] *Lin, H.-F. (2007). Measuring Online Learning Systems Success: Applying the
Updated DeLone and McLean Model, Cyber Psychology & Behavior, 10 (6), 817-
820.
[28] Lindgaard, G. (1994): Usability Testing and System Evaluation: A Guide for
Designing Useful Computer Systems. Chapman & Hall.
[29] *Liu, S.-H., Liao, H.-L. & Peng, C.-J. (2005). Applying the Technology
Acceptance Model and Flow Theory to Online E-Learning Users‘ Acceptance
Behavior, Issues in Information Systems, 6 (2), 175-181.
[30] *Martínez-Torres, M. R., Toral Marín, S. L., Barrero Garciá, F., Gallardo Váquez,
S., Arias Oliva, M. & Torres, T. (2008). A Technological Acceptance of E-
Learning Tools Used in Practical and Laboratory Teaching, according to the
European Higher Education Area, Behaviour & Information Technology, 27 (6),
495-505.
[31] Mayring, P. (2003): Qualitative Inhaltsanalyse: Grundlagen und Techniken, Vol. 8.
Beltz.
[32] *Mueller, D. & Zimmermann, V. (2009). A Learner-Centered Design,
Implementation, and Evaluation Approach of Learning Environments to Foster
Acceptance, International Journal of Advanced Corporate Learning, 2 (3), 50-57.
[33] *Nov, O. & Ye, C. (2008). Users‘ Personality and Perceived Ease of Use of Digital
Libraries: The Case for Resistance to Change, Journal of the America Society for
Information Science and Technology, 59 (5), 845-851.
[34] Palloff, R. M. & Pratt, K. (1999): Building Learning Communities in Cyberspace:
Effective Strategies for the Online Classroom. Jossey-Bass.
[35] Peffers, K., Tuunanen, T., Rothenberger, M.A. & Chatterjee, S. (2007). A Design
Science Research Methodology for Information Systems Research, Journal of
Management Information Systems, 24 (3), 45–77.
[36] *Pituch, K. A. & Lee, Y.-K. (2006). The Influence of System Characteristics on E-
Learning Use, Computers & Education, 47, 222-244.
[37] *Poelmans, S., Wessa, P., Mills, K., Bloemen, E. & Doom, C. (2008). Usability
and Acceptance of E-Learning in Statistics Education, based on the Compendium
Platform, International Conference of Education, Research and Innovation (ICERI
2008), 1-10.
[38] *Roca, J. C., Chiu, C.-M. & Martínez, F. J. (2006). Understanding E-Learning
Continuance Intention: An Extension of the Technology Acceptance Model,
International Journal of Human-Computer Studies, 64, 683-696.
181
[39] *Sahin, I. & Shelley, M. (2008). Considering Students‘ Perceptions: The Distance
Education Student Satisfaction Model, Educational Technology & Society, 11 (3),
216–223.
[40] Seddon, P. B. (1997). A Respecification and Extension of the DeLone and McLean
Model of IS Success‘, Information Systems Research, 8 (3), 240–253.
[41] Sitzmann, T., Kraiger, K., Stewart, D. & Wisher, R. (2006). The Comparative
Effectiveness of Web-based and Classroom Instruction: A Meta-Analysis,
Personnel Psychology, 59, 623-64.
[42] Strohmeier, S. (2008): Informationssysteme im Personalmanagement: Architektur
– Funktionalität – Anwendung. Vieweg+Teubner.
[43] *Sun, P.-C., Tsai, R. J., Finger, G., Chen, Y.-Y. & Yeh, D. (2008). What Drives a
Successful E-Learning? An Empirical Investigation of the Critical Factors
Influencing Learner Satisfaction‘, Computers & Education, 50, 1183-1202.
[44] *Tobing, V., Hamzah, M., Sura, S. & Amin, H. (2008). Assessing the
Acceptability of Adaptive E-Learning System, 5th International Conference on
eLearning for Knowledge-Based Society, 1-10.
[45] Venkatesh, V. & Bala, H. (2008). Technology Acceptance Model 3 and a Research
Agenda on Interventions, Decision Sciences, 39 (2), 273-315.
[46] *Wang, W.-T. & Wang, C.-C. (2009). An Empirical Study of Instructor Adoption
of Web-based Learning Systems, Computers & Education, 53, 761-774.
[47] *Wang, Y.-S. (2003). Assessment of Learner Satisfaction with Asynchronous
Electronic Learning Systems, Information & Management, 41, 75–86.
[48] *Wang, Y.-S., Wang, H.-Y. & Shee, D. Y. (2007). Measuring E-Learning Systems
Success in an Organizational Context: Scale Development and Validation,
Computers in Human Behavior, 23, 1792–1808.
[49] Weller, M. (2007): Virtual Learning Environments: Using, Choosing and
Developing Your VLE. Routledge.
[50] *Yeung, P. & Jordan, E. (2007). The Continued Usage of Business E-Learning
Courses in Hong Kong Corporations, Education and Information Technologies, 12
(3), 175–188.
182
Appendices:
1) Literature Review – Results Overview
Study Theory Design Characteristic Construct Method
Definition
System-Related
TAM ISSM …
Information-Related
1. [26] System Quality Offline
X X
- Survey
Perceived Usability,
2. [4] Perceived System Quality) Survey with
X X
Application
Information Quality
3. [25] System Quality Offline
X X
- Survey
System Quality Online
4. [38]
X X X X Survey with
Information Quality
Application
-
Online
5. [24] Perceived
X Survey with
Content Quality,
Application
Course Attributes
System Quality Survey with
6. [15]
X Prototype and
Information Quality Application
System Quality Offline
7. [27]
X X Survey with
Information Quality
Application
System Quality Offline
8. [50]
X X X Survey with
Information Quality
Application
System Quality Evaluation of
9. [48]
an
Information Quality Applicatoin
System Quality Offline
10. [37]
X X X Survey with
Information Quality
Application
11. [3] Perceived System Quality Survey with
X X
- Application
System Quality
12. [32]
X X Conceptual
Information Quality
183
13. [46] System Quality
X X X Online Survey
Information Quality
System Adaptability Offline
14. [44] Experiment
X X
- with
Application
Perceived Course Offline and
15. [2] Interaction, Online Survey
X
Perceived Flexibility with
(time, location, methods) Application
Screen Design
Online
16. [16]
X Relevance, X Interview with
Application
Terminology
Learner Interface
Learning Community Interview and
17. [47]
X Survey with
Personalization
Application
Content
-
18. [29] Survey with
X X eLearning Materials
Application
Presentation Types:
1. Text-Audio,
2. Audio-Video,
3. Text-Audio-Video
Screen Design,
Evaluation of
19. [23]
X Navigation X an
Application
Terminology
System Functionality,
Offline
System Interactivity,
20. [36] Experiment
X x
System Response with
Application
-
Functionality,
Online Survey
21. [9]
X Interface Design with
Application
-
e-Learning Course Flexibility
Online Survey
22. [43] (time, location, methods)
X X X with
Course Quality Application
184
Accessibility,
Communicativeness,
Feedback,
Interactivity and Control,
23. [30] Reliability, Survey with
X
User adaptation, Application
User tools
Format
Flexibility Online
24. [39]
X Survey with
-
Application
Screen Design Offline
25. [33]
X Survey with
Relevance
Application
2) Expert List
Name Affiliation Background
Anh Vu, N.-N. University of Leicester, UK Computer Scientist
Christina, H. IMC, Germany Pedagogue
Dominique, V. OUNL, the Netherlands Pedagogue
Effie L. University of Leicester, UK Psychologist
Elisabetta, P. Giunti Labs, Italy Computer Scientist
Jad, N. WUW, Austria Computer Scientist
Kai, H. TU Darmstadt, Germany Computer Scientist
Luis, de la F. UC3M, Spain Computer Scientist
Marvin, S. DFKI, Germany Computer Scientist
Milos, K. OUNL, the Netherlands Computer Scientist
Patrick, P. IMC, Germany Computer Scientist
Susanne, N. University of Vienna, Austria Pedagogue
Volker, Z. IMC, Germany Management, and
Business Informatics Specialist
185