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Chapter XXX
Developing Constructivist Learning Environments to Enhance
eLearning
Thomas Connolly and Mark Stansfield
Introduction
It is about twenty years since the conception of the Internet, yet in this relatively short time it
has had a profound effect on many aspects of society including business, government,
broadcasting, shopping, leisure, communication, and education and training. Its growth in the
past few years has been near expontential and it has started an information revolution that will
continue for many years to come. According to Internet World Stats (internetworldstats.com)
as of January 2006 over 1 billion people were using the Internet (approximately one sixth of
the world’s population). Buying goods and services over the Internet is becoming
commonplace and most organizations have recognized the potential of the Internet to market
and sell to a global market. Inevitably, the Internet is having a significant impact on Higher
Education, where eLearning has evolved from a marginal form of education to a more
commonly accepted and increasingly popular alternative to more traditional face-to-face
education (Connolly & Stansfield, 2006; Gundawardena & McIssac, 2004). Some faculty
members are strong proponents of eLearning and believe online courses can provide
educational opportunities to learners who would otherwise have to do without. They also
believe that the quality of courses based on eLearning are comparable to traditional place-
bound courses (Dutton, Dutton, & Perry, 2002).
While traditional education has been guided by the paradigm of didactic instruction, which
views the learner as passively receiving information, there is now an emphasis on
constructivism as a philosophical, epistemological, and pedagogical approach. Constructivism
focuses on knowledge construction, not knowledge reproduction. Many researchers have
expressed their hope that constructivism will lead to better educational software and better
learning. This has led to the development of constructivist learning environments (CLEs) that
guide and support learners to achieve their intended learning outcomes. Unfortunately, there
are many examples of eLearning that simply reproduce the traditional learning environment
and miss opportunities afforded by CLEs. In this chapter, we discuss the benefits of CLEs for
eLearning and provide guidelines for developing CLEs that create authentic learning
experiences. We discuss one such constructivist learning environment that we have used
successfully to deliver three fully online Masters courses in Information Systems and provide
some preliminary results from a three year quasi-experimental study.
eLearning
According to Connolly and Stansfield (2006), there have been six generations of distance
learning, the last three of which represent the first three generations of eLearning. This first
generation of eLearning is based on mainly passive use of the Internet (circa 1994-1999),
primarily consisting of repurposing of course material to an online format, basic mentoring
using email, and low-fidelity streamed audio/video. However, the educational philosophy still
belongs to the pre-Internet era. The second generation of eLearning (circa 2000-2003) is
based on the use of more advanced technologies consisting of high-bandwidth access, rich
streaming media, and Virtual Learning Environments that provide access to course material,
communication facilities and student services. Asynchronous communications support a
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constructivist form of learning and allow learners to communicate in writing. This in turn
encourages more reflection and disciplined and rigorous thinking, which helps learners to
make connections among ideas and to construct internal, coherent knowledge structures
(Garrison, 1997). The most recent developments in eLearning (since 2003) are more
collaborative learning environments based much more on the constructivist epistemology,
promoting reflective practice through tools like ePortfolios, blogs, wikis, using games-based
eLearning and highly interactive online simulations. We are also now starting to see the
development of mLearning (mobile learning) through devices like PDAs (Personal Digital
Assistants), mobile phones, and smartphones.
In terms of its contribution to Higher Education, the research literature cites many advantages
of an eLearning environment, particularly the convenience and flexibility offered by the
(asynchronous) ‘anytime, anywhere, anypace’ education (McDonald, 2002), which gives
learners time for research, internal reflection, and ‘collective thinking’ (Garrison, 1997).
Moreover, the text-based nature of eLearning normally requires written communication from
the learner, which along with reflection, encourage higher level learning such as analysis,
synthesis, and evaluation, and encourage clearer and more precise thinking (Jonassen, 1996).
McComb (1993) considers eLearning also provides efficient access to information, which
means that new resources and updates/corrections to course material can be posted relatively
quickly and at the same time learners have access to the wealth of related information
available nowadays on the Internet. In addition, eLearning courses also have the capability to
present multiple representations of a concept, which allows learners to store and retrieve
information more effectively (Kozma, 1987).
Increased social distance provides a number of distinct advantages to online conferences
(synchronous or asynchronous). In written communications anonymity of characteristics such
as gender, race, age, or social status can be preserved, which can reduce the feeling of
discrimination and provide equality of social interaction among participants. In turn, this can
permit the expression of emotion and promote discussion that normally would be inhibited.
However, there is some evidence that the social equality factor may not extend to participants
who are poor writers but who must communicate primarily in a text-based format
(Gunawardena, 1993).
eLearning is not without its disadvantages; for example:
•costs may initially exceed more traditional methods;
•more responsibility is placed on the learner who has to be self-disciplined and motivated
(this is particularly true for eLearning that consists simply of repurposed face-to-face
material, with minimal or no interactivity, which can be unengaging);
•some learners lack access to a PC/Internet or have difficulty with the technology;
•increased workload for both students and faculty (Connolly et al., 2006);
•non-involvement in the virtual community may lead to feelings of loneliness, low self-
esteem, isolation, and low motivation to learn, which in turn can lead to low achievement
and dropout (Rovai, 2002);
•dropout rates tend to be higher in eLearning courses than in traditional face-to-face
courses, often 10 to 20 percentage points higher (Carr, 2000).
Perhaps one of the most damaging criticisms is that some eLearning simply replicates the
social organization of traditional education and that the potential benefits of eLearning - of
personalized and accessible learning experiences - are missed. For many years, the
technology (the ‘e’ part of eLearning) seemed to dominate the development of eLearning and
it is only recently that there has been a wider recognition that the learning is more important –
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“creating technology-enhanced experiences designed to change future understanding and
performance” (Squire, 2005).
There is also significant debate about whether online learners perform as well as traditional
face-to-face learners with some researchers suggesting that much of the media comparison
studies are flawed in a variety of ways that render establishing cause-and-effect relationships
or generalizations questionable (Joy & Garcia, 2000). However, a recent meta-analysis of
such studies found that 1998 was a dividing time with studies published before 1998 finding
no significant difference, while studies published in and after 1998 finding eLearning to be
significantly more effective than face-to-face education (Zhao et al., 2005).
Constructivist Learning Environments
While traditional education has been guided by the paradigm of didactic instruction, which
views the learner as passively receiving information, there is now an emphasis on
constructivism as a philosophical, epistemological, and pedagogical approach to learning.
Cognitive constructivism views learning as an active process in which learners construct new
ideas or concepts based upon their current/past knowledge. The learner selects and transforms
information, constructs hypotheses, and makes decisions, relying on a cognitive structure to
do so (Piaget, 1968). In addition, constructivism asserts that people learn more effectively
when they are engaged in constructing personally meaningful artifacts. Social constructivism,
seen as a variant of cognitive constructivism, emphasizes that human intelligence originates in
our culture. Individual cognitive gain occurs first in interaction with other people and in the
next phase within the individual (Forman & McPhail, 1993). These two models are not
mutually exclusive but merely focus upon different aspects of the learning process. In fact,
Illeris (2003) believes that all learning includes three dimensions, namely, the cognitive
dimension of knowledge and skills, the emotional dimension of feelings and motivation, and
the social dimension of communication and cooperation – “all of which are embedded in a
societally situated context”.
According to Gance (2002) the main pedagogical components commonly associated with
these models are:
•A cognitively engaged learner who actively seeks to explore his environment for new
information.
•A pedagogy that often includes a hands-on, dialogic interaction with the learning
environment.
•A pedagogy that often requires a learning context that creates a problem-solving situation
that is realistic.
•An environment that typically includes a social component often interpreted as actual
interaction with other learners and with mentors in the actual context of learning.
The ultimate goal of a constructivist approach is metacognition, which has powerful problem-
solving potential. When the learner encounters a problem he can reflect not just on the
structure of the problem, but on the structuring of his approaches to the problem and thereby
attempt to generate alternative, more productive strategies. Not only is this a useful ability,
but the ultimate expression of education - to reflect back on what has been created by the
process of education (Boyle, 2000).
According to Ben-Ari (2001) constructivist principles have been more influential in science
and mathematics education than in computer science education. However, there are examples
of the application of constructivism within computer science from the development of Logo –
a programming language for schoolchildren (Papert, 1980), the teaching of programming (for
example, Pullen, 2001; Van Gorp & Grisson, 2001), computer graphics (Taxén, 2003), CASE
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tools (Fowler et al., 2001), object-oriented design (for example, Hadjerrouit, 1999; Yazici et
al., 2001), communication skills in computer science (Gruba & Søndergaard, 2001), to
collaborative learning using the Web (for example, Cook & Boyle, 2000; Hadjerrouit, 2003;
Connolly et al., 2004 and 2005).
Many researchers have expressed their hope that constructivism will lead to better educational
software and better learning (for example, Brown et al., 1989; Jonassen, 1994). They
emphasise the need for open-ended exploratory authentic learning environments in which
learners can develop personally meaningful and transferable knowledge and understanding.
This has led to the development of guidelines and criteria for the development of a
constructivist learning environment (CLE) - “a place where learners may work together and
support each other as they use a variety of tools and information resources in their guided
pursuit of learning goals and problem-solving activities” (Wilson, 1996, pp. 28). See, for
example, Cunningham et al., 1993; Grabinger & Dunlap, 1995; Savery & Duffy, 1995;
Gance, 2002).
The concept of authentic learning environments also underlies the theory of pedagogical
praxis proposed by Shaffer (2004a), which links learning and doing within an extended
framework of communities of practice (Lave, 1991; Lave & Wenger, 1991). Pedagogical
praxis is based on the concept that different professions (for example, lawyers, doctors,
software engineers) have different epistemologies (epistemic frames) – different ways of
knowing, of deciding what is worth knowing, and of adding to the collective body of
knowledge and understanding. For a particular community, the epistemic frames define
“knowing where to begin looking and asking questions, knowing what constitutes appropriate
evidence to consider or information to assess, knowing how to go about gathering that
evidence, and knowing when to draw a conclusion and/or move on to a different issue”
(Shaffer, 2004b, pp. 4). Implementation of pedagogical praxis requires a faithful recreation of
the professional community, one that is thickly authentic; that is, one where (a) learning is
personally meaningful for the learner, (b) learning relates to the real-world outside the
classroom, (c) learning provides an opportunity to think in the modes of a particular
profession, and (d) learning where the means of assessment reflect the learning process
(Shaffer & Resnick, 1999). Connolly and Begg (2006) have suggested that the term thickly
authentic be extended to incorporate: (e) learning using the tools and practices of the modern-
day professional.
Constructivist learning environments and problem/project-based learning
The problem-based learning model encompasses these principles. This model started out in
the 1960s in medical education in the USA and Canada where groups of students were
presented with a problem in the form of a patient with particular symptoms (Biggs, 1999).
The students’ task is to diagnose the patient’s condition and be able to justify the diagnosis
and recommend treatment. In diagnosing the condition, the students have to discuss the
symptoms, generate hypotheses based on whatever knowledge and experience they have and
identify learning issues. At the end of each session, the students reflect verbally on their
current hypotheses and each student assumes responsibility for investigating one of more of
the identified learning issues through self-directed learning.
A second authentic, constructivist approach is project-based learning (PBL). Esch (1998)
offers two continua for distinguishing between problem-based and project-based learning:
•The extent to which the end product is the organizing center of the project. At one end of
this continuum, end products are elaborate and shape the production process and, at the
other end, end products are simpler and more summative, such as a group’s report on
their research findings. The former case typifies project-based learning, where the end
product drives the planning, production, and evaluation process and the latter, where the
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inquiry and research is the primary focus of the learning process, typifies problem-based
learning.
•The extent to which a problem is the organizing center of the project. In this case, at one
end are projects in which it is implicitly assumed that any number of problems will arise
and students will require problem-solving skills to overcome them and, at the other end,
are projects that begin with a clearly articulated problem and require a set of conclusions
and/or solution. Again, the former example typifies project-based learning and the latter
typifies problem-based learning.
In both problem-based and project-based learning, the teacher (facilitator) is available for
consultation and plays a significant role in modeling the metacognitive thinking associated
with the problem-solving processes. These reflect a cognitive apprenticeship environment
(Collins et al., 1990) with coaching and scaffolding (e.g. offering hints, reminders, and
feedback) provided to support the learner in developing metacognitive skills. As these skills
develop, the scaffolding is gradually removed. The intention is to force learners to assume as
much of the task on their own, as soon as possible. The cognitive apprenticeship model also
advocates:
•modeling, which involves an expert (the teacher) performing a task so that the learner can
observe and build a conceptual model of the processes required to accomplish it;
•articulation (either verbal or written) to encourage learners to communicate their
knowledge and thinking;
•exploration, to push learners into a mode of problem-solving on their own;
•reflection, as previously discussed.
A similar concept to articulation that has been cited as an important element is debriefing,
which provides the opportunity for learners to consolidate their experience and assess the
value of the knowledge they have obtained in terms of its theoretical and practical application
to situations that exist in reality (Kriz, 2003).
Guiding Principles for the Development of Online Constructivist
Learning Environments
As a consolidation of the above research work, we put forward our own principles for
development of an online constructivist learning environment based on project-based
learning.
1. Allow learners to choose a (thickly) authentic project grounded in professional
practice. The project should be sufficiently complex to develop analytical and
problem-solving skills. It should also be both personally meaningful (to facilitate
intrinsic motivation) and relate to the real-world outside the classroom. The latter
implies the project should be group-based (although it may be challenging for the
team to find a project that is personally meaningful to all team members).
2. Encourage learners to take responsibility (ownership) for learning and to be aware of
the knowledge construction process.
3. Allow learners to develop their own processes to reach a solution.
4. Provide learners with the opportunity to experience and appreciate other perspectives
(this may come about as part of the next principle).
5. Provide opportunities for interaction and collaboration (learner-learner, learner-
teacher, or learner-system).
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6. For group-based work, there must be ‘group goals’ and ‘individual accountability’ for
effective collaborative learning (Slavin, 1989).
7. Ensure that the learning environment motivates, engages, and challenges the learner.
The environment should support the cognitive preference of the learners (Connolly
et. al., 2006).
8. Provide feedback mechanisms to enable learners to be fully aware of their progress.
9. Provide support mechanisms for learners using coaching and scaffolding (which
should gradually be removed).
10. Be flexible to support different learning styles.
11. Encourage learners, and provide mechanisms for learners, to articulate knowledge
and thinking throughout the project.
12. Encourage learners, and provide mechanisms for learners, to reflect on their activities
both during the project and after completion of the project. This reflection should be
both group-based and individual-based.
13. Provide opportunities for debriefing at the end of the project.
14. Provide an integrated assessment (in our case, the instrument of assessment is the
project itself, which can be assessed in a variety of ways).
Applying these Guiding Principles to eLearning
By way of an example, this section discusses how we have been using these guidelines within
three fully online Masters courses in Information Systems: the MSc Information Technology
with eBusiness, the MSc Information Technology with Web Technology, and the MSc
Management of eBusiness. We first outline the main educational aims of these courses and
then discuss the issues that commonly arise with teaching such courses. At the end of this
section, we present some preliminary findings from using these guiding principles.
At the start of these courses many students are likely to view knowledge as an authoritative
given, that is right or wrong, that can be gained through rote and practice (surface) learning
techniques, and that exists independently of context. By the time they graduate, students are
expected to (Research Forum, 2005):
•have understood the relative and provisional nature of knowledge related to eBusiness
and organizations;
•be able to generate new knowledge through critical enquiry and demonstrate it in an
appropriate form;
•be able to form their own judgments from evidence and challenge the judgments of
others;
•be able to synthesize and apply knowledge in various contexts, and
•approach performance and professional practice from a reflective, critical, and evidenced
base, rather than simply a competence one.
In themselves, these expectations are not unusual and are typical for many postgraduate IS
courses. Our course has a vocational orientation and we expect our graduates to become
professional IS practitioners typically in a multi-disciplinary environment. Previous
approaches to educating IS students model scientific and engineering methodologies, with
their focus on process and repeatability. In general, this approach is based on a normative
professional education curriculum, in which students first study basic science, then the
relevant applied science, so that learning may be viewed as a progression to expertise through
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task analysis, strategy selection, try-out, and repetition. Students tend to cope well using this
approach with many of the theoretical and practical components of the curriculum, for
example, from more softer/people-oriented IS-related techniques such as systems maps and
rich pictures to the more structured data-oriented IS-related techniques such as dataflow
diagrams and entity relationship diagrams. However, some of the abstract, less rule-based and
complex areas such as knowledge elicitation and strategy formulation can be problematical
for certain students since they cannot always be readily applied within a realistic real-world
environment that can be forgiving of mistakes and allow for feedback, reflection and
opportunities to develop different problem-solving strategies to a range of problem scenarios.
Students often have considerable difficulty analyzing problems were there is no single,
simple, well-known, or correct solution. They have difficulty handling ambiguity and
vagueness and they can also display an inability to translate tutorial examples to other
domains with analogous scenarios, betraying a lack of transferable analytical and problem-
solving skills. Kriz (2003) highlights the point that the majority of students are not competent
enough to put their knowledge into practice and they are unable to cope successfully with the
everyday tasks associated with the practice of their chosen field. These problems can lead to
confusion, a lack of self-confidence, and a lack of motivation to continue.
Connolly and Stansfield (2006) believe that IS can be considered as a wicked problem,
characterized by incomplete, contradictory and changing requirements, and solutions that are
often difficult to recognize as such because of complex interdependencies. According to
Armarego (2002), there is an educational dilemma in teaching such problems because:
•complexity is added rather than reduced with increased understanding of the problem;
•metacognitive strategies are fundamental to the process;
•a rich background of knowledge and intuition are needed for effective problem-solving;
•a breadth of experience is necessary so that similarities and differences with past
strategies are used to deal with new situations.
Analysis of results obtained using this approach
As a result of the particular difficulties involved in teaching such courses, we decided to
adopt a CLE based on project-based learning in some of the modules. A full discussion of the
results of a three-year quasi-experimental study is beyond the scope of this paper and the
interested reader is referred to Connolly et al. (2006) for a complete discussion. In this
section, we briefly discuss the findings for one module, Fundamentals of Database Systems
(FDBS).
The FDBS module runs in a traditional face-to-face mode for full-time and part-time groups
and since session 2001/2 in a fully online format for a part-time group. Since session 2002/3,
we have used a constructivist learning environment for the online group. The online group
typically consists of 15-25 students, all from similar professional backgrounds. Scaffolding is
provided through the teacher (facilitator) as well as through the creation of visualizations for a
number of database concepts (eg. ER modeling, normalization, mapping an ER model to
relations) and lower-level online units covering the relevant module material. When the
students encounter problems they can drill down to the relevant material or use the higher-
level visualizations. In the early stages, asynchronous online tutorials are run to discuss
worked examples covering activities that groups would have to undertake as part of database
analysis and design. It is important that students fully understand these examples and can
apply the principles in the different contexts they will find themselves in.
The students self-select themselves into groups of size 3-4 and each group chooses a project
that is of interest to all group members. These projects are generally from Small and Medium-
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sized Enterprises (SMEs) in the West of Scotland, which has the added advantage of
benefiting these businesses and thereby the local economy. The facilitator provides
background advice to ensure that a group does not take on a project that is too large or
complex or alternatively too trivial. Students are encouraged to keep sufficiently detailed and
formal records of their work and, in particular, the decisions made with supporting
justifications. They are also encouraged to frequently reflect on these decisions and the
processes that led to the decisions both as a group and as individuals. Each group/individual is
given scope to use whatever tools they feel most appropriate and most comfortable with (to
support cognitive preference). The FirstClass Virtual Learning Environment (VLE) is used for
the online material and this system provides email facilities and discussions boards, both
public (ie. available to the facilitator) and private (a students-only discussion area).
Interestingly, while groups initially use these basic facilities, they also develop their own wikis
and blogs, while using voice-over-IP tools like Skype and mobiles/instant messaging for more
urgent communication. Groups use laptops and PDAs for recording meetings with the clients
and the facilitator.
Support is provided by the facilitator as and when necessary but this is only in an advisory
capacity: groups are not provided with solutions or partial solutions but are instead directed to
where appropriate information can be found. This reinforces the principles of constructivism
and emphasizes to the students that they are acting as professional database design consultants
and have to act in this capacity. Debriefing is conducted at the end for all parties (facilitators,
students, and clients) to reflect on the learning outcomes and to reflect on issues that had
arisen in the performance of the projects.
A quantitative analysis of students’ performance in the FDBS module was based on 977
students divided into three groups, one of which used the constructivist project-based
approach through online delivery (another was taught using traditional methods online and a
control group was taught using traditional methods face-to-face). The analysis showed that the
students using the constructivist project-based approach consistently performed better than the
other two groups. The evidence supports our view that the constructivist approach can
improve student learning. In addition, the qualitative analysis of student and faculty feedback
from the FDBS module that we undertook in parallel provides some interesting results to
further support our view as we now discuss.
Student feedback was obtained from end-of-module questionnaires and faculty feedback from
interviews. Generally, student feedback was extremely positive, all students reporting that they
had enjoyed the experience. They were able to compare this approach with the more
traditional case study approach that they had encountered in their previous studies and had felt
that the project-based approach with learning in situ had provided a better, more motivating,
more engaging method to learn about database analysis and design. They also appreciated that
this approach gave them relevant work experience that could help their employment prospects
on completion of the course. On the negative side, most students reported that the workload
was significantly higher than in other modules. They also found time-management was an
issue, particularly as they had no real feeling at the outset for scope and complexity of the
projects they had selected (many were led by their enthusiasm for working as a professional
consultant). All were in agreement that the approach should be extended to other modules, but
rather than having a project per module, they suggested that one assessment-based integrative
project that extended over a number of modules would be an extremely powerful approach to
teaching and learning. This was something faculty had discussed on several occasions but had
never progressed the idea for resource reasons rather than pedagogic reasons.
Faculty were also enthusiastic of this approach and felt the students had learned more than
with the more traditional approach, particularly in areas not normally covered in database
modules (application of fact-finding techniques, and people-oriented and business-oriented
8
skills). It was important that sufficient guidance was given during the project, particularly in
the early stages when the groups were selecting projects (as noted above, student enthusiasm
had to be tempered with realistic expectations). At the same time, as students were now
working in an environment that had not been purpose-built for their effective learning, care
had to be taken to ensure students were not overwhelmed with all the complexities that a real-
world project can present, otherwise their initial enthusiasm quickly dissipated. The students
needed quite a lot of guidance with both group and personal reflection initially until they
found tools they were comfortable with (eg. wikis, blogs).
Typically each faculty member handled between 4-6 project groups compared to sometimes as
many as 20 groups with the traditional case study approach. Nevertheless, faculty found that
their workload was significantly higher than with traditional approaches and that it was
necessary to develop in-depth knowledge of each industrial project to be able to support the
students effectively. This gave rise to grave concerns over scalability and faculty felt that they
could not have coped with any further project groups.
There was agreement among faculty that the project-based learning approach was
pedagogically sound for postgraduate courses and for third/fourth years of undergraduate
courses, but were reluctant to use this approach in first or second year, on the grounds that
students may not be sufficiently mature learners and may not have developed the necessary
discipline and time-management skills required. Further, it was generally felt that the
facilitator had to have a fairly extensive knowledge of Computing/IT and a solid foundation in
business concepts to be able to handle the variety of projects that students selected with
project-based learning.
Conclusions
While eLearning has significant potential, there are many examples of eLearning that simply
reproduce traditional (didactic) learning environments. At the same time, there is now
increased emphasis on constructivism as a philosophical, epistemological, and pedagogical
approach to learning. Constructivist Learning Environments (CLE) have the potential to
provide authentic and engaging environments for eLearning. In this paper we have provided
some guidelines for the creation of one such CLE based on the cognitive apprenticeship
model and project-based learning.
The approach used points toward learning about Information Systems by doing Information
Systems, and relying less on overt lecturing and traditional teaching. Information Systems is
learned by becoming a practitioner, albeit for the duration of the module/course, not merely by
learning about practice. In brief, students should engage in challenging problems that reflect
real-world complexity. The problems should be authentic and ill-structured; that is, they
should not have one predetermined, foregone solution but rather be open to multiple
interpretations and multiple ‘right answers’. Students should engage in actively working on
solving the problem in collaborative groups to reflect the social nature of learning.
This approach requires a shift in the roles of both students and faculty. The student becomes a
cognitive apprentice, exploring and learning about the problem in the presence of peers.
Faculty shifts from overt lecturing to becoming a facilitator who assists students in developing
an understanding of the professional practice of database analysis and design.
The paper presents some preliminary results of this work that suggests the approach can be
used successfully to teach students how to design effective modern information systems. The
qualitative findings show that students and faculty reacted extremely positively to the
approach and found it more motivating and engaging than the more traditional teaching
approaches. However, both students and faculty found the workload higher than with more
traditional teaching methods and that scalability was an issue. Faculty also felt that this
9
approach required mature learners and may not be entirely appropriate for first and second
year undergraduates.
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AUTHORS
Thomas Connolly is a Professor in the School of Computing at the University of Paisley and
has worked for over 15 years in industry as a Manager and Technical Director in international
software houses before entering academia. His specialisms are online learning, online games-
based learning, and database systems. He has published papers in a number of international
journals that include the Computers and Education, International Journal of IT Management,
British Journal of Educational Technology, Journal of Information Systems Education, and
Journal of IT Education and as well as authoring the highly acclaimed books ‘Database
Systems: A Practical Approach to Design, Implementation, and Management”, and ‘Database
Solutions’ both published by Addison Wesley Longman.
Mark Stansfield is a Senior Lecturer in the School of Computing at the University of
Paisley. He has a PhD in Information Systems and has published papers on online learning,
online games-based e-learning, information systems and e-business in a number of
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international journals that include the Journal of Further and Higher Education, the Journal
of Electronic Commerce Research, the Journal of IT Education and Computers and
Education. He also serves on the editorial boards of several international journals.
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