The Virtual Design Workshop
An Online Adaptive Resource for Teaching Design in Engineering
Alexandra Vassar, B. Gangadhara Prusty, Nadine Marcus and Robin Ford
Faculty of Engineering, UNSW AUSTRALIA, UNSW Sydney NSW 2052, Sydney, Australia
Keywords: Engineering Design, Adaptive Tutorials, eLearning.
Abstract: Design education aims to develop in students the confidence to apply engineering fundamentals to the
design of products and systems. This can only be achieved through intensive education and exposure to real-
life engineering problems. One of the pressing issues in teaching engineering design is the resources- and
labour-intensive nature of the subject. In practice, when developing a design, engineers are dependent on the
situation at hand, so goals, problems and constraints are often ill defined and may change as the problem
continues to unfold, providing no single ideal solution. Assumptions and estimations are required before
each analysis step, and the results need to be evaluated against the desired functional output. Often, many
analysis iterations are needed before a suitable solution is found. When teaching, providing the same
scenario requires that tutorial guidance must adapt to the particular solution of each individual student.
Conventional online tutorials help to combat some issues, but they are not able to track student progress in
detail, nor are they able to provide customisable feedback for individual students. The aim of the research is
to develop software tools that can address key problems in engineering design education and provide
students with a more effective and enriching educational experience. This paper discusses a response to the
issues in design education in engineering, in the form of adaptive tutorials, and puts forward the preliminary
analysis of their success in helping students overcome the limitations of current design education.
1 INTRODUCTION
Design is an essential component of any engineering
discipline, a combination of technical expertise and
creativity. Good design is vital in creating objects
and spaces that work. Design is widely considered to
be at the core of engineering and it is well
established that “…engineering programs should
graduate engineers who can design effective
solutions to meet social needs…” (Dym et al., 2005).
Engineering science education tends to focus on
developing skillsets within students, which allow
them to solve particular problems in particular ways.
The skills and knowledge build hierarchically on
what was previously learnt. Often many previously
learned concepts and capabilities need to be
employed in order overcome the challenges in the
problem to find a solution. It misleadingly implies
that there is an ideal approach to the problem and an
ideal solution. In reality, few true engineering
problems fit this model. In practice, when
developing a design, engineers are dependent on the
situation at hand, so goals, problems and constraints
are often ill defined and may change as the problem
continues to unfold (Lemons et al., 2010). There is
no single ideal solution in this situation.
Assumptions and estimations are required before
each analysis step, and the results need to be
evaluated against the desired functional output.
Often, many analysis iterations are required before a
suitable solution is found. Although engineers often
have general guidelines for the design process, there
is no consensus regarding one correct procedure to
follow in order to reach a solution (Lemons et al.,
2010).
Students are often uncomfortable with the notion
that there is no correct answer, as the majority of
their prior learning has been assessed with
examinations and quizzes where there are
definitively correct answers (Goldsmith et al., 2010).
Many initiatives have been taken to identify the
reasons for poor student engagement with
engineering design and to find ways to address the
problem, both by individual teachers and,
increasingly, by the community of engineering
academics. The problem may lie in graduate
452
Vassar A., Prusty B., Marcus N. and Ford R..
The Virtual Design Workshop - An Online Adaptive Resource for Teaching Design in Engineering.
DOI: 10.5220/0004945204520458
In Proceedings of the 6th International Conference on Computer Supported Education (CSEDU-2014), pages 452-458
ISBN: 978-989-758-020-8
Copyright
c
2014 SCITEPRESS (Science and Technology Publications, Lda.)
students’ capability to find solutions to previously
unseen problems. A theoretical position on this
capability and threshold concepts has been proposed
in a recent paper by (Baillie et al., 2013). Numerous
efforts have also been made to better integrate
design into engineering curricula (Carroll, 1997;
Kartam, 1998; Kurfess, 2003) and prepare graduate
engineers for the industry (Todd et al., 1995).
Ultimately, engineering design seeks to find a
technical solution that best satisfies a particular set
of requirements. This design process takes into
account a range of factors, including economics,
buildability, sustainability, technical performance
and safety, but it is largely driven by the
requirements of the problem space.
2 BACKGROUND
Despite incorporating long-practiced teaching and
learning approaches for engineering design courses,
current methodologies still suffer from inherent
shortcomings. Design courses are resource intensive.
With each passing year, there is a trend toward
resources to teach becoming more limited despite
increasing student enrolments, making authentic
design experiences difficult to achieve (Dougherty
& Parfitt, 2009). This is further exacerbated by the
inability to provide feedback to such a large number
of students in a timely and efficient manner.
Traditional design teaching (workshops, studios,
laboratories, etc.) does not translate well spatially or
temporally. The interactivity of design teaching
requires students to be located in the same time and
place as the teacher. This limits opportunities for
distance education (MOOCs) and also limits a
student’s capability to learn at an individual pace.
Furthermore, it can be difficult to evaluate student
performance in complex design assignments due to
the variability of student responses. This problem is
exacerbated when students work in teams, as
accurate evaluation based on individual effort is
difficult to implement (Dutson et al., 1997). Design
courses require lecturers to put extra time into
devising suitable projects for students, looking for
suitable industry-sponsored projects, and
coordinating the course itself (Todd et al., 1995;
Wilczynski & Douglas, 1995). Faculty members
have limited professional and industrial experience
in design disciplines (Dutson et al., 1997). The
reason for this could be today’s increased focus on
research output. An increasing proportion of faculty
staff are recruited directly upon the completion of a
fruitful post-doctoral period – staff with little, if any,
professional industrial design experience.
Two particularly effective educational
frameworks already integrated into engineering
design education are “project-based learning” and
“problem-based learning”. Generally, project-based
learning is directed at the application of knowledge
in projects, whereas problem-based learning
involves the acquisition of knowledge and skills in
the process of solving previously unseen problems
(Heywood, 2005; Perrenet et al., 2000). These two
approaches are similar in that they focus on student
learning rather than teaching (Kolmos, 1996). They
are also similar to providing students with many
worked out problems and their solutions, another
effective means of improving problem solving
(Sweller & Cooper, 1985). However, current
project/problem/studio-based learning (PBL) and
teaching methods have proven very costly to run.
This cost arises because typical hands-on projects or
design assignments in physical laboratories,
workshops and studios require space, logistics,
equipment, time and money, which are traditionally
limited resources. Consequently, the extent to which
these teaching methods can be utilised is restricted,
often to cornerstone design courses (e.g. ENGG1000
at UNSW). With ever increasing enrolment
numbers, the sustainability of even these major
hands-on courses is under threat. PBL curricula are
also difficult to scale to very large classes or to
move online (MOOC) due to the substantial
requirement for students to physically attend
laboratories and work on projects collaboratively.
There thus exists a need for complementary tools to
augment existing design education in the online
space. These tools need to replicate, as closely as
possible, authentic design experiences and surround
students in the design ethos. A number of software
solutions are currently on the market for the purpose
of teaching design-based engineering subjects.
Gibson et al. (2002) evaluated a software
package, Design Builder, based on its content,
operational measures, technical ability and feedback
and assessment. They found that Design Builder
scored extremely well under all the headings, in
particular scoring above 90% in its Feedback and
Assessment section, concluding that the program has
achieved its goals in teaching students. The article
(Gibson et al., 2002) goes on to recommend that
Design Builder be adopted as an aid in teaching
engineering design at the undergraduate level. One
of the main benefits of Design Builder, and its
potential success as an aid in teaching the concepts
of design, is the ability to easily portray the practical
application of the problem before design can
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commence. The software also allows students some
control over specific variables of their design,
allowing them to see first hand the effects of
practical applications of the design. However, the
limited control does not allow students to effectively
evaluate the different characteristics of design of the
system, and therefore does not provide feedback on
all aspects of system design.
An additional software package (unnamed) that
can aid in learning, allows the student to explore
elements of shaft design (Álvarez-Caldas et al.,
2007). The software provides the student design
with a high degree of control, allowing changes to
the overall structure and also the specific variables
of design. This is an advantage to learning, as
students are given the opportunity to see what effect
specific variables and elements have on the overall
design of a shaft and can be provided with detailed
feedback relating to each of the elements.
The objective of the Heat Exchanger package
(Tan & Fok, 2006) is to educate the student in heat
exchanger design, and to “…bridge the gap between
theoretical consideration and engineering
practice…” (Tan & Fok, 2006) The software allows
the students to become acquainted with heat
exchanger designs through thermo-hydraulic
analysis, and to understand the fabrication, costing
and maintenance aspects of the design through its
mechanical drawings. The program provides the
student with control over specific variables that
influence the overall design and also provides a
customized overview of the design, however, it lacks
the mechanical design capabilities for the students to
understand the practical engineering application of
the final design (Tan & Fok, 2006). Furthermore,
other limitations of the Heat Exchanger software are
that feedback is not instantaneous, and an academic
is not easily able to see the progress of the students.
West Point Bridge Design (WPBD) is a
nationwide competition organized by the United
States Military Academy (USMA) (Symans, 2000;
Ressler & Ressler, 2004). The competition is aimed
at increasing interest in engineering among middle
and high school students, by allowing them to
engineer a solution to a real-world problem. The
WPBD software provides the tools that students
need to design and create a steel highway bridge,
based on real-life parameters. This allows students
to learn more about engineering design, by applying
mathematics, science and technology principles to
create a device that will service human needs.
Students are required to use the WPBD software to
design a bridge based on the specified criteria and
constraints. The WPBD software allows students to
graphically create a structural design, in which the
student chooses the material and mechanical
properties of each structural member. The student is
then able to run a simulated load, determining the
ability of the bridge to carry a specified load.
Creating a successful design with this software is
fairly simple; however, creating an optimal design at
the lowest possible cost is the real challenge, thereby
replicating a real-world situation (S. J. Ressler & E.
K. Ressler, 2004). The target audience of this
competition is limited to high school students and
there is no direct educator feedback. This is strictly a
design competition, so whilst it is effective in
demonstrating some of the elements of design, it is
not effective in teaching, or providing information to
improve future design decisions. Students are
required to conduct outside research that they can
then use to design and test a bridge. Specifically, a
survey conducted by Ressler et al. (2004) found that
whilst students demonstrated a high level of
perceived learning about structures, they
demonstrated a relatively lower levels of learning
about engineering design.
Design teaching initiatives have also been
implemented by Khan Academy (www.
khanacademy.org). One of the biggest advantages of
the Khan Academy resources is its ability for
students to progress at their own pace, with feedback
provided as needed, ensuring individualised
learning. Perhaps, the most unique thing about Khan
Academy is the incredibly reach that it has.
Globally, in 2012, the site was used by
approximately 6 million unique students each month
(Noer, 2012). Whilst the benefits of the Khan
Academy cannot be denied, the setback to this mode
of learning is the lack of guidance from an educator,
when it is required.
The University of Pennsylvania has also
undertaken an online design course. Web-based
learning technologies including student generated
electronic portfolios, an e-studio website and
asynchronous discussion board technologies were
implemented and tested throughout a multiphase
research study. The study was constructed as part of
curriculum improvement activities for the capstone
design course sequence in the Department of
Architectural Engineering. A major part of the
Capstone design program is the e-studio practitioner
mentorship program, providing online access to staff
members who are experts in the student’s field of
study. The use of web-based technology has proven
a success, and has provided improved course
management, enhanced practice-based course
content, increased visibility of student-generated
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projects and improved student/practitioner
interaction (Dougherty & Parfitt, 2006).
One of the issues with current software-based
design education is the inability to provide feedback
and to engage in discussion with students. The need
to address these issues are seen in such packages as
Khan Academy Online, Pennsylvania Capstone
Design and Udacity Online, which provide the
students with a discussion forum aimed at improving
learning and understanding. A proposed solution to
the current issues faced in engineering design is the
use of adaptive tutorials (Ben-Naim et al., 2008),
where interactive instructions are adapted to
student’s level of understanding. Online Adaptive
Tutorials (ATs), already well established in
engineering science courses, promise particular
benefits for design education. Similarly, they have
been successfully trialed in other domains such as
medicine (Velan et al., 2009). AT’s have been
shown to help overcome the constraints of limited
resources while providing students with improved
and personalised support when and where they want
it. Engineering design problems present imperfect
input information and have no predefined result.
Each student must devise their own solution to each
design problem they face. The problem factors to be
analysed during the design process are difficult to
specify at the outset, meaning that the tutorial
guidance must adapt to the particular solution that
each individual student devises. Adaptive tutorials
provide a complete feedback loop to the students.
They are designed so that a student is able to interact
with a simulation whilst being guided, and given
unique feedback based on student input into the
system (Marcus et al., 2011; Prusty, et al., 2011b;
Prusty, 2011; Prusty & Russell, 2011; Prusty, Ben-
Naim, et al., 2011a; Ben-Naim & Prusty, 2010;
Prusty, 2010). This can allow for customised student
learning and real-time feedback for educators from a
large group of students, thereby reducing the load on
the educator and minimising course resources. The
educator receives feedback on student learning via
the Solution Trace Graph (STG), a visual summary
of overall student performance, and can use this to
update and modify instructional content as needed
(Ben-Naim et al., 2009) (Figure 1).
An increasing enrolment base of students
restricts the courses that can be run due to the
physical space and physical equipment restrictions
that come with large group sizes. Thus exists a need
for complementary tools, such as adaptive tutorials
to augment existing design education in the online
space. These tools need to replicate, as closely as
possible, authentic design experiences and surround
Figure 1: An example of a Solution Trace Graph.
students in the design philosophy that will ensure a
future generation of engineers capable of
approaching a range of different problem spaces and
solutions.
2 PILOT STUDY
This pilot study used the Adaptive Tutorial system
pioneered at The University of New South Wales
(UNSW) (Ben-Naim et al., 2008; Prusty, et al.,
2011b; Prusty et al., 2009; Prusty et al., 2013).
Adaptive Tutorials (ATs) are web-based, intelligent
and interactive eLearning tools, implemented on an
Adaptive eLearning Platform (AeLP). ATs have
been implemented since 2006 at UNSW and various
other international universities in science-based
education. Prusty and his colleagues (Prusty et al.,
2013) have found adaptive tutorials to be effective
tools in teaching science-based engineering subjects.
ATs supply a valuable teaching tool with the
possibility of providing a highly customised learning
environment for each student (Khawaja et al., 2013).
There are two features in particular that make the
application of adaptive tutorials suitable to design
instruction. Firstly, the visual and interactive
capabilities of the AeLP offer a virtual environment
with interactive tools to better engage students in
engineering design. And secondly, the Adaptive
Tutorial provides timely feedback, tailored to each
student’s actions and responses. This provides
students with improved and personalised support
when and where they need it – vital elements for
effective design education.
The Design Adaptive Tutorial was implemented
as a learning and assessment exercise to help
students understand the fundamentals of design in
the Solid Mechanics course offered at the second
year level at the University of New South Wales
(Figure 2).
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Figure 2: A screenshot from gantry beam design AT.
The tutorial was implemented for the last two
years, in 2012 and 2013. Qualitative analysis of
student feedback was undertaken in the form of a
questionnaire based on student experience with
Adaptive Tutorials in Semester 1 in 2013. In total,
304 students attempted the tutorial with an average
mark of 92% scored in the tutorial material.
3 RESULTS AND DISCUSSION
A survey was given to 304 students with questions
gauging the effectiveness of the adaptive tutorial in
learning the concepts for the mechanical design of a
gantry beam (Figure 3).
Figure 3: Design Loop for a gantry beam using Solid
Mechanics fundamentals.
A number of students commented on the
effectiveness of immediate feedback mechanism, as
one of their most important learning resources, to the
question “Do you find this Adaptive Tutorial useful
to apply the fundamentals of Solid Mechanics?”
Immediate feedback provided students with the
ability to complete the tutorial and learn at an
individual pace suitable to the student’s learning
needs. Table 1 documents the identified themes
taken from students commenting in response to the
survey question on whether the AT was useful is
applying the fundamentals of Solid Mechanics.
The vast majority of students found the tutorial
to be helpful in applying fundamental principles, and
82% indicated that the tutorial was indeed useful to
apply principles of Solid Mechanics (Figure 4).
Table 1: Identified themes from student comments on the
usefulness of the AT to the fundamentals of Solid
Mechanics.
Theme
Comments
No
Helpful 41
Instant feedback 37
More interactive than classroom learning 29
Revision of basic concepts 15
Incorporates many necessary
fundamentals
13
Shows design process in action 13
Enjoyable experience 11
Applicable to current study 9
Step by step 7
Not sure if useful to me 2
Figure 4: Applying ATs to the fundamentals of Solid
Mechanics course.
More importantly, it appears that students found
it easy to navigate their way through the adaptive
tutorial and found the tutorials to be easy to learn
Figure 5: Ease of use of AT interactive elements.
(Figure 5). A number of students also commented on
the ease with which they were able to manipulate the
interactive elements of the tutorial, therefore using
their limited cognitive resources to complete the
tutorial as opposed to learning the tutorial interface.
A positive response was also obtained from
students on the preference of using Adaptive
Tutorial as a learning tool in Solid Mechanics
(Figure 6). Approximately one third of the students
Problem
Definition
Preliminary
Design
FreeBody
Diagram
Internal
Forces
PrincipalStresses
Redesign/Opti
misation
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surveyed, or 32%, strongly agreeing that Adaptive
Tutorials are their preferred teaching method as
opposed to traditional written assignments and 33%
of students surveyed agreeing that adaptive tutorials
are a preferred method of learning.
Figure 6: Preference for teaching methods.
4 CONCLUSIONS
The pilot study has indicated that adaptive tutorials
could be an effective solution to design education in
engineering. Adaptive tutorials enrich student
knowledge with the instantaneous real-time and
customised feedback, based on student input into the
system. In particular, for larger groups of students,
educators are able to instantly discern problems that
a student might be experiencing with coursework
material without the need for individual consultation
via the STG, a visual summary of overall student
performance. This can be used to update and modify
instructional content as needed, thereby reducing the
load on the educator and minimising course
resources (Ben-Naim et al., 2009).
Furthermore, an increasing enrolment base of
students restricts the courses that can be run due to
the physical capacity and equipment restrictions that
come with large group sizes. Thus exists a need for
complementary tools, such as adaptive tutorials, to
augment existing design education in the online
space. These tools need to replicate, as closely as
possible, authentic design experiences and support
students with the development of design that will
ensure a future generation of engineers capable of
approaching a range of different problem spaces and
solutions.
Leading on from the pilot, further studies will
utilise not just qualitative survey data, but will also
include information regarding course marks and
overall course performance. The program of
adaptive tutorials will also be expanded to
encompass different engineering disciplines, such as
Mechanical Engineering, Civil Engineering, Naval
Architecture and Aerospace Engineering and also
include Architectural design problems. This will aid
in providing an overall picture into the effectiveness
of adaptive tutorials in student understanding of
fundamental design concepts in engineering.
ACKNOWLEDGEMENTS
This project is funded by the Office for Learning &
Teaching, an initiative of the Australian Government
Department of Education, Employment and
Workplace Relations (Project OLT ID 13-2837).
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CSEDU2014-6thInternationalConferenceonComputerSupportedEducation
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