TEACHING DATABASE ANALYSIS AND DESIGN IN A
WEB-BASED CONSTRUCTIVIST LEARNING ENVIRONMENT
Thomas M. Connolly, Carolyn E. Begg
School of Computing, University of Paisley, High Street, Paisley, United Kingdon
Keywords: Database analysis and design, online learning, reflective practitioner, constructivist learning environments,
project-based learning.
Abstract: The study of database systems is typically core in undergraduate and postgraduate courses related to
computer science and information systems. However, there are parts of this curriculum that learners find
difficult, in particular, the abstract and complex domain of database analysis and design, an area that is
critical to the development of modern information systems. This paper reflects on these difficulties and
describes an approach for teaching database analysis and design online motivated by principles found in the
constructivist epistemology, which helps to overcome these difficulties and provides the learner with the
knowledge and higher-order skills necessary to understand and perform database analysis and design
effectively as a professional practitioner. The paper presents some preliminary results of this work and
reflects on the findings.
1 INTRODUCTION
The database is now the underlying framework of
the information system and has fundamentally
changed the way many companies and individuals
work. This is reflected within tertiary education
where databases form a core area of study in
undergraduate and postgraduate courses related to
computer science and information systems, and
typically at least an elective on other data-intensive
courses. The core studies, typically, are based on the
relational data model, SQL, data modeling,
relational database analysis and design and,
increasingly, object-relational concepts. This
supports industry where the object-relational DBMS
is the dominant data-processing software currently
in use. The core relational theory is a mature and
established area now in relation to other parts of the
computing curriculum. However, there are parts of
this curriculum that learners find difficult, in
particular, database analysis and design.
Mohtashami and Scher (2000) note that
pedagogical strategies for teaching database analysis
and design traditionally follow a similar modality to
that of other technical courses in computing science
or information systems. A significant amount of
technical knowledge must be imparted with the
teacher becoming a ‘sage on stage’ and the learners
passive listeners. This is the objectivist model of
learning, which views learning as the passive
transmission of knowledge from the teacher to the
learner, heavily criticized for stimulating surface
learning and knowledge reproduction. In contrast,
the central tenet of the constructivist view is that
learning is an active process where new knowledge
is constructed based on the learner’s prior
knowledge, the social context, and the problem to be
solved. In this paper, we describe a teaching
approach that we have used to teach database
analysis and design online motivated by principles
found in the constructivist epistemology to help
provide the learner with the knowledge and higher-
order skills necessary to understand and perform
database analysis and design effectively as a
professional practitioner.
In the following section, we outline the high-
level pedagogical aims of our database modules and
consider some of the difficulties that arise in
achieving these aims. In the subsequent section, we
examine related work on constructivism and
constructivist learning environments. In Section 4,
we discuss how we have applied constructivist
principles to our teaching of a database module
delivered fully online. In Section 5, we present some
164
M. Connolly T. and E. Begg C. (2006).
TEACHING DATABASE ANALYSIS AND DESIGN IN A WEB-BASED CONSTRUCTIVIST LEARNING ENVIRONMENT.
In Proceedings of WEBIST 2006 - Second International Conference on Web Information Systems and Technologies - Society, e-Business and
e-Government / e-Learning, pages 164-171
DOI: 10.5220/0001240301640171
Copyright
c
SciTePress
early findings from our approach followed by some
conclusions.
2 PEDAGOGICAL AIMS
The database modules in the School of Computing at
the University of Paisley have the following general
educational aims:
Develop a sound understanding of the principles
and underpinning theory related to the study of
database systems.
Assist the development of a business ethos in
the student that emphasizes fitness for purpose
as the guiding principle in the design,
development, and assessment of database
systems and their components.
Enable the student to take a disciplined
approach to problem definition, and to the
specification, design, implementation, and
maintenance of database systems.
Develop critical, analytical, and problem-
solving skills and the transferable skills to
prepare the student for graduate employment.
Assist the student to develop the skills required
for both autonomous practice and team-
working.
Create awareness of the continuing
development of database technologies and
applications and the need for continued study,
reflection, and development throughout a career
as a database professional.
In themselves, these aims are not unusual and are
typical for many undergraduate database modules.
Our modules have a vocational orientation and we
expect our graduates to become professional
database practitioners typically in a multi-
disciplinary environment. Previous approaches to
educating database designers and, more generally,
software designers 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 task
analysis, strategy selection, try-out, and repetition
(Armarego, 2002). While students tend to cope well
using this approach with many of the theoretical and
practical components of the core database
curriculum, for example, understanding the
properties of the relational data model, the basics of
SQL, and using a relational DBMS, one area that
tends to be problematic is the abstract and complex
domain of database analysis and design (for the
purposes of this paper, we use the term database
analysis and design to encompass system definition,
requirements collection and analysis, conceptual
database design, logical database design, and
physical database design). A comparable problem
has been identified with object-oriented analysis and
design, which is also highly abstract (Hadjerrouit,
1999), requirements engineering (Bubenko, 1995),
and software design and testing (Budgen, 1995).
While databases have become so essential to
organizations, some students become deceived by
the simplicity of creating small databases using
products such as Microsoft Access and believe they
can create more complicated databases just as easily.
Unfortunately, the resulting databases are hard to
use, barely meet system requirements, and are
difficult to redesign. In addition, students require
skills to work in a project team, skills to apply
appropriate fact-finding techniques to elicit
requirements from the client (both ‘soft’, people-
oriented skills), skills to conceptualize a design from
a set of requirements (‘soft’, analytical and problem-
solving skills), skills to map a conceptual model to a
logical/physical design (‘hard’, technical skills), and
skills to reflect and review intermediate designs,
particularly where information complexity is present
(a combination of ‘soft’ and ‘hard’ skills). These are
different skills from learning SQL, knowing the
components of an ER model, or being able to recite
the properties of the relational model. Students often
have considerable difficulty comprehending
implementation-independent issues and analyzing
problems were there is no single, simple, well-
known, or correct solution. They have difficulty
handling ambiguity and vagueness, which can arise
during knowledge elicitation. They can also display
an inability to translate classroom examples to other
domains with analogous scenarios, betraying a lack
of transferable analytical and problem-solving skills.
These problems can lead to confusion, a lack of self-
confidence, and a lack of motivation to continue.
Software engineering (and therein database
analysis and design) has been described 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 (DeGrace and Hulet
Stahl, 1998). According to Armarego (2002), there
is an educational dilemma in teaching such problems
in software engineering because:
complexity is added rather than reduced with
increased understanding of the problem;
metacognitive strategies are fundamental to the
process;
TEACHING DATABASE ANALYSIS AND DESIGN IN A WEB-BASED CONSTRUCTIVIST LEARNING
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165
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.
Schön (1983) argues that the primary challenge for
designers is how to make sense out of situations that
are puzzling, troubling, and uncertain. According to
Schön the following are some of the key problems in
teaching design:
It is learnable but not didactically or
discursively teachable: it can be learned only in
and through practical operations.
It is a holistic skill and parts cannot be learned
in isolation but by experiencing it in action.
It depends upon the ability to recognize
desirable and undesirable qualities of the
discovered world. However, this recognition is
not something that can be described to learners,
instead it must be learned by doing.
It is a creative process in which a designer
comes to see and do things in new ways.
Therefore, no prior description of it can take the
place of learning by doing.
As an additional complexity, to provide more
flexible modes of study and capture new markets,
tertiary education is providing more modules and
courses in an online format, resulting in students
who are geographical dispersed and have diverse
backgrounds. While online learning has many
advantages (“anytime, anywhere, anypace”) there
are also disadvantages such as increased setup costs,
more responsibility is placed on the learner who has
to be self-disciplined and motivated, increased
workload on students and staff, 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, and dropout rates tend to
be higher than in traditional face-to-face programs,
often 10 to 20 percentage points higher (Connolly
and Stansfield, 2006). To address these issues we
require a different approach to traditional (face-to-
face) teaching methods. Figure 1 provides a
representation of the types of knowledge and skills
required to undertake database analysis and design
and the associated problems.
The above discussions suggest an alternative
approach to teaching database analysis and design
may overcome some of the above difficulties and in
the next section we examine one such approach that
we have found useful.
3 PREVIOUS WORK
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. 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 and
McPhail, 1993). These two models are not mutually
exclusive but merely focus upon different aspects of
the learning process.
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 (eg. designing a database is
preferred to being told how to design a one).
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.
Dewey argued that knowing and doing are
intimately connected and that learning occurs in the
context of activity when an individual attempts to
accomplish some meaningful goal and has to
overcome difficulties in the process. Schön (1983)
describes professionals as individuals who make this
connection between knowing and doing through
reflective practice, suggesting that professionals
learn to think in action and learn to do so through
their professional experiences. For Schön,
practitioners (in our case, database designers) have
their own particular knowledge codes fully
embedded within their practices. They apply tacit
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knowledge-in-action, and when their problems do
not yield to it, they reflect-in-action, using the
languages specific to their practices. When they
evaluate the event afterwards, they reflect-on-action,
using the language of practice, not the language of
science. In this way, professionals enhance their
learning and add to their repertoire of experiences,
from which they can draw in future problem
situations. Schön believes that it is this ability to
reflect both in, and on, action that identifies the
effective practitioner from less effective
professionals. For Schön the ideal site of education
for reflective practice is the ‘design studio’ where,
under the direction of a master practitioner serving
as coach, the novice learns the vocabularies of the
professional practice in the course of learning its
‘operational moves’.
These arguments suggest that students can only
learn about design by doing design, and rely less on
overt lecturing and traditional teaching. This
approach requires a shift in the roles of both students
and teachers, with the student becoming an
apprentice, exploring and learning about the problem
in the presence of peers (who may know more or
less about the topic at hand) and the teacher moving
from being the ‘knowledgeable other’ towards
becoming a facilitator, who manages the context and
setting, and assists students in developing an
understanding of the material at hand (Koehler and
Mishra, 2005).
Figure 1: Types of knowledge and skills required to undertake database analysis and design.
Domain-specific Skills
Capturing data requirements
Representing data requirements
ER to relation mapping
Relation to table mapping
…..
Database Analysis &
Design
Fact-finding techniques
Database design
methodology
ER to relation mapping
Relation to table mapping
Denormalization
Problems with analysis & design
Ill-defined
Ambiguous
Complex
Changing requirements
Multi-disciplinary
People-oriented
Knowledge & intuition required
Experience required
Eclectic
Skills
Intellectual Skills
Problem-solving
Critical thinking
Analytical
Metacognitive
Reflection
Creativity
People-oriented
Skills
Communications
(verbal & written)
Interpersonal Skills
Team working
Business-oriented
Skills
Management
Leadership
Innovation
Enterprise
Personal Skills
Time management
Independent worker
Knowledge &
Understanding
Business &
Management
Project Management
Quality Management
Business environment
Business processes
Professional, Legal and
Ethical Aspects
Background
Knowledge
Depends on each
individual
Database
Implementation
DBMS Architectures
Commercial DBMSs
Commercial SQL
Monitoring & Tuning
Security
Transaction Mgt
Database Concepts
Database approach
Database environment
Relational model
SQL (DDL + DML)
ER Modeling
Normalization
Database Analysis and
Design Project
Problems with online delivery
Setup costs
Increased responsibility on learner
Increased workload
Potential lack of social interaction
Potential for high dropout
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3.1 Constructivist Learning
Environments
Many researchers have expressed their hope that
constructivism will lead to better educational
software and better learning (for example, Brown,
Collins, & Duguid, 1989). They emphasize 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).
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 (Pullen, 2001),
computer graphics (Taxén, 2003), object-oriented
design (Hadjerrouit, 1999), communication skills in
computer science (Gruba and Søndergaard, 2001), to
collaborative learning using the Web (Connolly,
Stansfield, & McLellan, 2005).
Project-based learning (PBL) is a constructivist
approach to learning knowledge and skills through a
process structured around projects with complex and
authentic tasks, objectives, questions, and problems.
In PBL, 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., 1989)
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. A
further 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.
4 APPLYING THESE
PRINCIPLES
We have developed a Web-based CLE using the
above principles built around the cognitive
apprenticeship model and project-based learning to
teach some of the database modules in our
undergraduate/postgraduate courses. A more
complete discussion of the CLE can be found in
Connolly and Begg (2006), however, in this paper
we focus on the use of the online CLE for the
Fundamentals of Database Systems (FDBS) module,
a core module in the School’s MSc Information
Technology course, a conversion course for non-
computing graduates. The students taking this
module are reasonably experienced learners
although not experienced in computing.
The FDBS module runs in a traditional face-to-
face mode for full-time and part-time cohorts and
since session 2001/2 in a fully online format for a
part-time cohort. Since session 2002/3, we have used
a CLE for the online cohort, which 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 businesses 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. To support the notion of
cognitive preference (Connolly, MacArthur,
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Stansfield, & McLellan, 2006), each
group/individual is given scope to use whatever
tools they feel most appropriate and most
comfortable with. The FirstClass VLE is used for the
online material as well as providing email facilities
and discussions boards, both public (ie. available to
the students and facilitators) and private (a student-
only discussion area). Interestingly, while groups
initially use these basic facilities, they also develop
their own wikis and blogs, while using
Skype/mobiles and 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. We discuss some of these issues in the next
section.
5 PRELIMINARY RESULTS
This section presents some preliminary findings
from using the project-based learning approach to
teach database analysis and design in the FDBS
module. A quantitative analysis of students’
performance in the FDBS module is presented in
Connolly et al. (2006). The paper compares the
performance of 977 students divided into three
groups, one of which used the constructivist project-
based approach albeit through online delivery. The
evidence supports our view that the constructivist
approach can improve student learning. The results
were not fully conclusive because the effect could
have been entirely attributable to online delivery
rather than the project-based approach and further
quantitative research is required. However, 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.
Finally, a qualitative analysis of student and
faculty feedback provide further insight into this
approach. 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. The students
were also very receptive to the concept of a
reflective journal and, while it was sometimes
difficult to find the time to maintain it, many
reported that they had benefited from this approach
and would keep a reflective journal for the
remainder of their studies and into employment. 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.
Faculty were also enthusiastic of this approach
and felt the students had learned more than with the
case study approach, particularly in areas not
traditionally covered in the database modules (use of
fact-finding techniques, and people- and business-
oriented 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 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 case study approach.
Nevertheless, faculty found that their workload was
significantly higher than with traditional approaches
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and that it was necessary to develop in-depth
knowledge of each 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.
Faculty observed that students generally
underestimated the time required to undertake the
project and the facilitator needed to discuss the
similarities and differences between case study
assessments and project-based assessments. For
example, some students underestimated the time
spent securing a company’s involvement in their
project and establishing that relationship cannot
always be rushed to fit a timescale that suits the
students and meets the demands of faculty. It was
also important for the facilitator to identify the gaps
in the students’ knowledge and skills and direct
them to appropriate sources to enable them to
undertake the project effectively. Failing to do this
in a timely manner, led some students to lose
confidence and meant they simplified and converted
the project into a form of case study that they could
cope with. However, this should and can be avoided
with sufficient support from the facilitator to
encourage students to accept the realities and
complexities of PBL as a positive aspect of their
work. It is the students’ ability to cope with and
manage the project that is being assessed and
therefore it is necessary that they do not ignore or
smooth over the problems of working with a real
company.
While assessments based on case studies for
database analysis and design usually present a
simplified and contrived set of requirements that the
students then analyse and solve, our PBL approach
requires that the students must first capture the
requirements for the new database. Capturing
requirements require that students use fact-finding
techniques that may be known in theory but not
practised. Therefore, while case study assessments
cover requirements analysis through to physical
database design and possibly thereafter to
implementation, PBL extends the coverage of the
database system development lifecycle from the
systems definition stage through to implementation.
It is therefore clear that the skills required to
undertake PBL differs to that of the case study
approach.
As the success of the PBL approach is dependent
on the support of industry, faculty emphasized that
the facilitator must carefully guide students in their
relationship with the company while ensuring that
students achieve the specified learning outcomes.
This sometimes required significant diplomacy from
the facilitator when the academic objectives did not
fully match the commercial objectives. It is
important that faculty explain to companies at the
outset what constitutes reasonable expectations for
parameters such as project size, project complexity,
and overall timescales. However, in most cases, both
students and companies benefited from the
relationship and this is why PBL has been well
supported by companies over the last few years.
Occasionally, faculty encountered problems with
group dynamics, for example, autonomous students
tend to prefer to work individually, there can be lack
of group cohesion, dominant group members,
insecure group members, and free-riders (referred to
in group dynamics research as ‘diffusion of
responsibility’). To highlight that these can occur in
industry and need to be overcome, students were
encouraged to tackle these problems as a group and
only in extreme cases did faculty intervene to
facilitate a solution acceptable to all.
There was agreement among faculty that the
PBL 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 rather than moving from being a
‘sage on the stage’ to a ‘guide on the side’, the
facilitator had to be more of a ‘fount of all
knowledge’ with project-based learning.
6 CONCLUSIONS
This paper has examined some of the issues
surrounding the teaching of database analysis and
design and has described a teaching approach
motivated by principles found in the constructivist
epistemology, based on the cognitive apprenticeship
model and PBL. The approach used points toward
learning about design by doing design, and relying
less on overt lecturing and traditional teaching.
Design is learned by becoming a practitioner, albeit
for the duration of the module, 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
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working on solving problems 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 being the ‘sage on the stage’ to the ‘guide on
the side’ (possibly, in the extreme, the ‘fount of all
knowledge’), 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 shows the approach can be used
successfully. The preliminary qualitative findings
show that students and faculty reacted extremely
positively to the approach and found it more
motivating and engaging than the more traditional
case study approach. 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 approach required
mature learners and may not be entirely appropriate
for first and second year undergraduates.
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