CONSTRAINTS ON REUSABILITY OF LEARNING OBJECTS
Didactic Aspects of Modular e-Learning in Engineering Education
Michael May, Peter Munkebo Hussmann, Anne Skov Jensen
LearningLab DTU, Technical University of Denmark (DTU), Building 101, Kgs. Lyngby, Denmark
Helle Rootzén
Department of Informatics and Mathematical Modelling, DTU, Building 305, Kgs. Lyngby, Denmark
Steen Markvorsen, Karsten Schmidt, Kasper Skårhøj, Søren Enemark
Department of Mathematics, DTU, Building 303S, Kgs. Lyngby, Denmark
Keywords: Learning Objects, Metadata, Reuse, Multimedia, e-Learning, Learning Scenarios, Conceptual
Understanding, Didactics, Engineering Education.
Abstract: It is the aim of this paper to discuss some didactic constraints on the use and reuse of digital modular
learning objects. Engineering education is used as the specific context of use with examples from courses in
introductory electronics and mathematics. Digital multimedia and modular learning objects have been
proclaimed as important elements in e-learning for a long time, and there are good reasons to believe in the
benefits of interactive multimedia as well as flexible and modular learning objects. Nevertheless the use and
reuse of learning objects on a large scale seems to be a slow success. Constraints on reuse arise from the
nature of conceptual understanding in higher education and the functionality of learning objects within
present technologies. We will need didactic as well as technical perspectives on learning objects in
designing for understanding.
1 INTRODUCTION
In a general sense learning objects (LO) have been
defined as “any entity, digital or non-digital, that
may be used for learning, education or training”.
This is the broad definition given in the IEEE Draft
Standard for Learning Object Metadata (IEEE LOM,
2002). Conceptually it is appropriate to include non-
digital artifacts and learning resources like books
and laboratory equipment in the definition of
learning objects, even though most discussion focus
on digital media objects designed, stored, distributed
and displayed with the use of modern information
and communication technologies (ICT). As such
learning objects are at the core of “e-learning”. E-
learning is understood here in the broad sense of any
use of ICT to support teaching and learning (and
mainly for “blended learning” rather than distance
education).
A surprising aspect of the above definition, espe-
cially in the context of the LOM standard, is that
learning object metadata is not considered an
integral part of the learning object. This can be seen
as symptomatic because one of the problems facing
the reuse of learning objects is the missing or
inadequate metadata descriptions of resources to be
found in digital media archives, i.e. Learning Object
Repositories (LORs).
In the following the metadata problem and other
problems restraining the sharing of learning objects
will be considered, including (a) didactic issues in
supporting conceptual learning of scientific content,
(b) the pedagogical scenarios specifying how
learning objects should be used.
2 THE TECHNICAL AND THE
DIDACTIC PERSPECTIVE
Reuse of learning objects (LOs) outside their course
325
May M., Munkebo Hussmann P., Skov Jensen A., Rootz
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en H., Markvorsen S., Schmidt K., Sk
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arhøj K. and Enemark S. (2010).
CONSTRAINTS ON REUSABILITY OF LEARNING OBJECTS - Didactic Aspects of Modular e-Learning in Engineering Education.
In Proceedings of the 2nd International Conference on Computer Supported Education, pages 325-332
Copyright
c
 SciTePress

of origin will require descriptions of the objects as
learning resources, i.e. metadata descriptions of
their intended use that is relevant from pedagogical
and didactic points of view. This means that the
bibliographic metadata (e.g. author, title, year of
publication) required by library databases will not
suffice for LORs. Effective search and retrieval of
LOs from digital archives will have to take
information about the educational contexts-of-use
into account, e.g. information about the intended
pedagogical scenario for which the LOs were
originally designed as well as the learning objectives
and the competence level associated with their use.
For a teacher in e.g. chemical engineering it will
not be sufficient to know the title of a LO within a
given topic, e.g. thermodynamics. If she for instance
is looking for a simulation to be used within a
student exercise to visualize (: the pedagogical
scenario) heat flow in a fluid (: the topic), then LOs
just illustrating heat flow through static images will
not be relevant for the chosen learning scenario or
didactic situation. Even interactive java applets
within the topic might not be adequate, because they
would typically support a limited form of parameter
variation useful for physics teaching at a high school
level, but not the construction of models of heat flow
based on differential equations as needed in the
context of chemical engineering education.
On top of these topical and pedagogical
constraints imposed on the relevance and reusability
of learning objects, there is an additional didactic
problem with regard to the specific conception of
thermodynamics within chemical engineering. Even
though e.g. heat flow seems to be a coherent topic
that could be used in a neutral and objective way to
index a given learning object, it turns out that
different branches of science and engineering
conceptualize thermodynamics in different ways
(Christiansen & Rump 2008). Heat flow as a topic is
thus treated slightly different in thermodynamics
within physics as compared to how it is “framed”
within mechanical engineering or within chemical
engineering. What counts as paradigmatic examples
and good illustrations will consequently be different
in these three disciplines although they could all
nominally be described as a part of the topic of “heat
flow in thermodynamics”.
Within the scientific community focusing on the
design and use of Digital Libraries the problem of
finding appropriate learning objects in LORs such as
e.g. Merlot, the Multimedia Educational Resource
for Online Learning and Teaching hosted at
www.merlot.org, have been noted (Najjar et.al.
2005), but the didactic and pedagogical problems of
reusability is often confused and obscured by
usability issues of the interfaces designed for these
archives. The problem of finding appropriate LOs is
then turned into the secondary issue of how to
support navigation in user interfaces. Important as
these HCI design issues are they should not mask the
underlying didactic problems of reusability.
There has been a similar trend in instructional
design theories to focus on the technical issues of
multimedia and LOs. The very idea of flexibility and
reusability of digital learning resources have arisen
in the context of advances in software engineering
such as object oriented programming, the separation
of content and layout with XML technologies, and
the development of Content Management Systems
(CMS) for web content (Schär 2006). The Learning
Management Systems (LMS) that support blended
learning in higher education, including access to
LOs, are basically specialized versions of CMS.
Given the discussion so far we can conclude that
we need extended metadata descriptions including
e.g. information about pedagogical scenarios of use
as an integral part of the digital learning objects in
order to support search, retrieval and reuse.
Content
Metadata
Learning object
Extended with information
about intended use context
(pedagogical scenarios)
Figure 1: A (digital) learning object must include metadata
as well as content.
Much work has been done on defining metadata
standards to secure the interoperability of LOs, and
with SCORM, i.e. the Sharable Content Object
Reference Model, reusability is explicitly addressed
as a functional requirement for the standard: “e-
learning content designed for one organization can
be redeployed, rearranged, repurposed, or rewritten
by other organizations that have similar learning
needs” (SCORM FAQ at www.adlnet.org).
This is however still a technical perspective on
LOs. To introduce a genuine didactic perspective we
will look at an example from a redesigned course in
introductory electronics for students in computer
science and engineering at the Technical University
of Denmark (DTU).
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3 LEARNING CIRCUIT THEORY
The example concerns the use of simple simulation
and visualization tools in an introductory course in
electronics. The introduction of these tools took
place within a reorganization of course contents in
order to enhance student learning and the flow of
competences acquired through the progression of
courses within a bachelor engineering program. This
work was in itself a part of the CDIO educational
framework (Conceive, Design, Implement, Operate)
(www.cdio.org) for the development of engineering
education (Crawley et.al. 2007).
In selecting simulation and visualization tools
for student’s learning of introductory electronics we
found that different dimensions of the media objects
(explained below) could be used to choose between
the topically relevant learning objects based on the
expected cognitive support for student learning
relative to didactic problems found in learning the
specific scientific content. We could, in other words,
give specific arguments for the learning objects used
rather than general arguments about e-learning.
One of the objectives of the redesigned course
was to have students build a conceptual bridge
between key concepts and components in analogue
electronics (e.g. behavior of electrical circuits,
resistance and capacitance) and key concepts and
components in digital electronics (e.g. transistors
and microprocessor circuits). This used to be
difficult because analogue and digital electronics
were taught in different courses without much
coordination of the examples used.
3.1 Didactic Problems in Learning
Electricity and Electronics
Another problem is that students have diverse prior
knowledge in mathematics and physics, and there
are well known didactic problems in learning
electricity and electronics, some of which concerns
the conceptual understanding of electricity and
circuit behavior (May et.al. 2008):
(a) Conceptual transfer problems in using prior
knowledge and skills in mathematics in introductory
electronics (Waks 1988) as well as in applying basic
knowledge of electricity to problems in electronics.
(b) Dissociation of computational skills from
model comprehension. It is a general problem in
science and engineering education that the ability of
students to perform calculations does not necessarily
indicate a deeper understanding of the theories and
models they use. In electronics students develop
skills for recognizing and solving standard problems
of electrical circuits without considering the
functional relations of the circuits. They can solve
equations given a set of values by using simple laws
(like Ohm’s law and Kirchhoff’s laws) but can not
always explain the properties and behavior of
electrical circuits in a qualitative manner.
(c) Confusion of cause and effect in learning
about electricity and electronics in the sense that
students have a tendency to focus on electrical
current rather than on voltage (Cohen, Eylon, &
Ganiel 1983). This is sometimes called the “battery-
centred” model of electricity, since batteries are seen
as the sole sources and agents of flows in simple
circuits (Steinberg 1985). Unfortunately this
conceptual problem can by worsened by the use of
analogies that are otherwise supposed to enhance
mental models of electrical flow, i.e. by analogy to
fluid flow (Dupin & Johsua 1989). The water
models of electricity give rise to misconceptions
about electricity since they tend to focus students on
localized events at the expense of global properties
of electrical circuits and simultaneous events.
(d) Conceptual difficulties in considering global
phenomena. It is a general problem in science and
engineering education that students have difficulties
in considering global phenomena and simultaneous
changes in several variables. In electricity,
electromagnetism and electronics the problem is not
just a problem of visualization in a narrow sense, but
a problem of conceptualization of a link between
observed global effects and microscopic processes
implied by theoretical models e.g. movement of
electrons (Thacker, Ganiel & Boys 1999).
3.2 Dimensions of Media Objects and
their Cognitive Support for
Learning
As we stated above the point of considering didactic
problems in the context of LOs is to provide specific
reasons for the relevance of pedagogical scenarios
and their inclusion of digital learning objects, since
students need different forms of cognitive support to
overcome these problems and this can be found
selectively in different dimensions of the media
objects used in blended learning. This is a general
hypothesis that can only be exemplified here.
A simple form of learning objects that have been
promoted to support student learning in e.g. physics
is interactive java applets, where simple physical
models are visualized and animated. Students can
explore the effects of adjusting a limited set of
parameters in the models. In physics education these
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327

java applets are known as “Physlets” (Christian &
Belloni 2004). A collection of java applets for
science education can be found at www.falstad.com.
As media objects these applets can be described
through dimensions such as interactive, animation
and 2D visualization. In introductory electronics
interactive applets might play a role in establishing a
conceptual bridge between analogue and digital
electronics by supporting student’s exploration of
simple RC-circuits (i.e. circuits with a resistance and
a capacitor), and the observation of graphs of current
and voltage as functions of time as a capacitor is
charged and decharged (Figure 1). The RC-circuit in
analogue electronics is important for didactic
reasons because students can observe that charging a
capacitor takes time, and they learn that this delay
(in principle) is responsible for the constraint
imposed on the possible speed of computer chips in
digital electronics (i.e. the clock frequency).
Figure 2: The Circuit Simulator java applet used to
visualize the behavior of a simple RC-circuit. The graphs
show current (yellow line) and voltage (green line) as a
function of time (www.falstad.com).
Dimensions of media objects relevant for
cognitive support for learning include (slightly
revised from May et.al. 2008):
- Static visualization versus animation
- Spatial dimensionality (2-D, 3-D etc.)
- Mono-media versus multimedia
- Representational forms or “sign types” (e.g.
images, maps, graphs, diagrams, language)
(cf. May 2007, May & Petersen 2007)
- Linear versus hypermedia organization
- Supported user control and interaction forms
(e.g. playback, simulation etc.)
Parameter variation is an important part of the
exploration of models and the construction of mental
models in science and engineering. The support for
students to construct and simulate their own models
is however quite limited in simple java applets.
There are a number of other Open Source programs
that can be used to construct and simulate electrical
circuits such as “5spice” (www.5spice.com) and the
Circuit Simulator (hosted at www.sourceforge.net).
In the present course the Circuit Simulator was
used as a digital LO to build virtual circuits and test
hypotheses about circuit behavior based on student’s
initial calculations and circuits sketches (Figure 2).
Students were then instructed to construct selected
circuits on breadboards, perform measurements and
thus compare the virtual and the physical circuits.
This way the LO was an integral part of a larger
pedagogical scenario inspired by the learning cycle
(Kolb 1984; Crawley et.al. 2007), according to
which learning occurs in iterative phases of abstract
conceptualization (e.g. students mental models and
initial sketching), active experimentation (e.g. the
virtual circuits), concrete experience (the physical
construction and the measurements) and reflective
observation (from virtual and physical circuits). This
leads to the reconstruction of student’s mental
models (i.e. revision of the initial conceptualization).
Virtual circuits
and hypothesis
testing about
circuit behavior
Students
mental
models of
electricity &
electronics
Initial circuit sketches
Construction of
physical circuits and
measurements
Digital learning object
Figure 3: The Kolb learning circle for learning as applied
to electrical circuit theory to show the didactic context of a
digital learning object.
The learning cycle is however disrupted if the
digital LO is abstracted from the pedagogical
scenario in order to be reused in another context
(Figure 2). This is an important counter-argument to
reusability because experiments and hands on
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experiences in laboratories are seen as essential parts
of engineering education. For students in
engineering learning will often occur over longer
periods of time as a topic is treated again in more
advanced courses and concepts and models are seen
from different perspectives or applied to physical
constructions or experiments. Learning should
perhaps not be seen as an effect that can be
encapsulated within a single learning object or even
within a single course, but rather as an extended
process of conceptual change.
Virtual experiments and web-based instructions
can be used to prepare students for lab work, but
virtual labs can never be a complete replacement for
physical experiments, because virtual experiments
are simulations (cf. the “nomological machines” in
science and engineering discussed in Christiansen &
Rump 2006). Virtual labs do not offer (real)
measurement errors and the learning experience of
failure when experimental designs are flawed or
theoretical assumptions refuted.
In learning about circuit theory in electronics
students need several iterations of the elements of
the Kolb circle: they need to make mistakes in
sketching their own circuits, they need to explore
interactively how different proposed circuits might
work (as a form of thought experiments to be carried
out through virtual circuits), and they need to build
their own physical circuits and experience how real
circuits behave and observe whether measurements
correspond to the ideal conditions of the simulation.
All elements are needed in order to promote
conceptual change and the gradual construction of
adequate mental models of e.g. circuit theory in
electronics.
4 INSTRUCTIONAL DESIGN
As indicated above the tradition for research and
development in Instructional Design is itself to some
extend caught up in the technical perspective on
teaching and learning. A good example is provided
by one of the most advanced theories in Instructional
Design, i.e. the theory of Instructional Components
(Merrill 2001).
The theory of David Merrill can be seen as a
kind of radical “object-oriented” approach to
multimedia instruction. Learning and instruction is
here assumed to be decomposable into small chunks
of information (Schär 2006) much like the modular
and flexible building blocks of a LEGO world
(Wiley 2001).
An advanced aspect of this cognitively based
theory of instructional design is its semiotic
possibilities: modular objects of learning can
perhaps be understood as the “words” of a grammar
of instruction to be discovered. Just as layout and
content is separated in modern XML based semantic
technologies, we might be able to describe relevant
properties as “affordances” of these multimedia
components arising from combinations of features of
the media (sound, graphics, haptics etc.) and features
of the representational forms used (images, maps,
graphs, diagrams, language), both being distinct
from the specific content expressed (May 2007, May
& Petersen 2007). Merrill suggests a series of
pragmatic functions of instructional components, i.e.
simple actions or “instructional transactions” like
showing, telling, asking and doing. These are the
kind of simple “actions” that human agents and
artifacts engage in within learning and instruction, or
rather as seen from a technical perspective on
learning objects (instructional components).
There are however limits to this technical view.
If we extend the LOs from small components to
larger collections of components and includes
strategies to support student learning (such as
learning styles etc.) we will need to integrate these
threads of learning activities within Learning
Management Systems and support instructed
navigation, and this threatens the idea of modular
LOs. Flexibility of LOs can be realized, but not
necessarily reusability and repurposing of modules.
5 LEARNING WITH E-MATH
Our second exemplification of learning objects
concerns a course in introductory mathematics for
engineers covering major topics in linear algebra,
complex numbers and differential equations (fall
semester), as well as Taylor series, integration, and
topics in differential geometry (spring semester).
The Computer Algebra System (CAS) Maple is well
integrated in the course and Maple is used for
computations and visualizations in lectures as well
as in student exercises.
In the course given in fall 2009 a pilot project in
e-learning called e-math had “taken oven” a
particular week with the purpose of studying the
non-linear and individual forms of learning made
possible by a collection of web-based learning
objects including modular e-notes covering the
theoretical content (the content that would normally
be presented in a linear way by textbooks and
lectures), Maple demonstrations and exercises, video
appetizers motivating and exemplifying topics,
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329

video recorded lectures, interactive visualizations in
Maple and Geometer, and multimedia pen casts
(recorded voice and drawing/writing) explaining
particular methods. A related project for a “virtual
mathematics learning environment” for engineering
students have been described by (Vinuesa & Fornos,
2007), but the aim of this project has been to support
distance learning rather than blended learning and
without the focus on flexible learning objects.
The e-math prototype was developed in the open
source Content Management System (CMS) TYPO3,
the development of which was initiated by one of the
authors.
A basic assumption of the e-math project is that
modular learning objects can be used for flexible
teaching and learning by supporting individual
differences in prior knowledge and skills and in
approaches to learning (“learning styles”). In the
context of engineering education the learning styles
suggested by the chemical engineer Richard Felder
have gained some popularity. According to Felder
individual learning styles can be identified through
the answers to four questions (Felder & Brent 2005):
Preferred type of information: sensory or intuitive?
Most effective perception: visual or verbal?
Preferred information process: active or reflective?
Progress to understanding: sequential or global?
In the e-math prototype tested in the first week of
November 2009 we included an option for students
to select a particular learning style (using a slightly
different typology) in browsing the learning objects
for the topics of the week. Selecting a learning style
would simply rearrange the recommended sequence
of learning objects (e.g. to watch an appetizer video
on the topic before reading the theoretical e-note),
but would not change the obligatory core of learning
objects that students had to study. The e-math
prototype was deliberately designed to contain “too
much” learning resources in order to support
individual exploration on different topics on
different levels of detail. Some students found
learning styles useful, whereas others ignored this
option by following a generic order of objects.
Learning styles is a disputed concept and as
Felder himself points out it can be misused if
teaching is adapted individually to these styles, since
students need to develop skills characteristic of each
type of learner in order to function effectively as
future engineers. The pedagogical concern should be
to support variation in teaching methods and
variation in the presentation of content.
The challenge raised by the diversity of student’s
prior knowledge and skills seems to be much more
important to address in higher education and here
adaptation based on online testing is more promising
(Clark & Feldon 2005). Learning objects can play an
important role in harmonizing competence levels of
students and in providing individualized assistance
for students with deficient prior knowledge in
specific areas. At DTU the web-based e-math was
used after the ordinary lectures in the time slots
assigned for computational exercises and other
assignments, but e-math was also used by students to
prepare for lectures and as repetition.
The e-learning content of the e-math prototype
was focused on a particular week for purely
pragmatic reasons, but it is expected that more
learning objects will be added. The week chosen has
a significant role in the course as a whole: after the
introduction of linear algebra and complex numbers
in the previous weeks, the content of the selected
week returns to the topic of differential equations
that students know from high school mathematics,
but now with the added learning objective of using
linear algebra and complex numbers for exploring
and solving 1. and 2. order differential equations.
Figure 4: The web interface of the e-math prototype
(November 2009).
Student navigation of the learning objects in the
test week of November 2009 was based on a
selection of available topics and subtopics for the
week (left column in figure 3). In the figure the
subtopic “linearity and solution structure” have been
selected, and this brings up a list of activities
contained in the learning object, some of which are
obligatory (an example to demonstrate the solution
structure of a differential equation, a video recording
of the lecture on the topic, and an assignment in
solving equations with and without the use of
Maple) and some of which are optional (in this case
an e-note on linearity and solution structure, and a
Livescribe SmartPen pencast that play through a
written exercise with voice over explanation (figure
4).
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Figure 5: Multimedia pencast (flash animation) with
animated writing, drawing and voice. The exercise is an
optional activity contained in a learning object.
Figure 6: Screencast with voice over explaining an
example in Maple syntax.
Maple examples included not only exercises
where students should use Maple themselves, but
also screencasts of worked out examples (with voice
over explanations). Students found these video
examples useful because they exemplified the Maple
syntax in important areas where it is significantly
different from the notation used in the e-notes (and
the textbooks on which they are based).
Students were still expected to follow lectures
even though they were also recorded and uploaded
to e-math. Video lectures were mainly used for
repetition, but in the future they could be used as
replacements for some lectures (or parts of them),
thereby liberating time for focused discussion with
students on difficult topics and for the development
and maintenance of e-math learning objects.
Video recorded interviews and lectures were
however also used in e-math as appetizers for the
different topics. These optional activities included
lectures given at other departments in order to
exemplify the application of differential equations in
different domains of science and engineering, and
thereby motivate the topics.
An example is show below where Ph.D. student
Qiyuan Li (Department of Systems Biology, DTU)
gives a lecture on biological modeling with
differential equations (e.g. predator-prey systems).
Figure 7: Karsten Schmidt giving a lecture recorded and
uploaded to e-math.
Figure 8: Screen shot from an e-math video lecture
illustrating the application of differential equations.
Originally the e-math test should have included a
hypergraph navigation module for supporting non-
linear access to the learning objects, but for the
limited time period of the test and the limited
number of topics and corresponding learning objects
and activities, the hypergraph would not be able to
show its full potential. Interactive hypergraphs are
used to visualize and navigate large tree structures
and networks and they could be useful for non-linear
navigation of topics, learning objects and their
activities, but it should again be recalled that we
should not only understand their design and use
from the technical perspective (of the interface and
its implementation), but also from the didactic
perspective of the topical structure and the ways in
which it might constrain learning.
6 CONCLUSIONS
In designing the e-math prototype it soon became
clear that student learning would need to be
supported by recommended sequences of activities
(adapted to learning styles or not) since any non-
guided exploratory use of the system, e.g. jumping
between unrelated documents, would be confusing
and counterproductive for the learning objectives of
the course. This however once again (as in the case
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331

of the “learning cycle” for learning about circuit
theory) points to the dilemmas and constraints
imposed on the use and reuse of learning objects: if
conceptual understanding of topics in e.g.
engineering education require extended coherent
sequences of learning activities, then the desired
(“LEGO”-like, cf. Wiley 2001) modularity and
flexibility of the components of instruction (Merrill
2001), does not necessarily entail that they can be
reused “out of context” and repurposed within other
scenarios and other organizations (cf. the ideal
expressed by the LOM standard). Perhaps advances
in semantic web technologies such as the use of
ontologies, automated indexing, software agents and
social tagging of content can render learning objects
of the future more “intelligent” with regard to how
content can be combined and recombined (McGreal
2004, Gašević et.al. 2007), but even with this kind of
technical vision we cannot escape the necessity of
considering the didactic perspective on learning and
the constraints imposed on learning.
ACKNOWLEDGEMENTS
The e-math project is supported by the Danish
Ministry of Science, Technology and Innovation.
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