Model Mediated University Course in Engineering
László Horváth
Institute of Applied Mathematics and Doctoral School of Applied Informatics and Applied Mathematics,
Óbuda University, Bécsi u. 96/b, Budapest, Hungary
Keywords: Education using Active Engineering Model, Object Models for Engineering Course, Contextually
Structured Virtual Teaching Material.
Abstract: Great changes of ideas, methods and systems place new challenges for researchers, practitioners, and
educators in engineering in these days. The most affecting change is for lifecycle engineering of cooperating
systems operated multidisciplinary products. Product information is represented and handled in dedicated
engineering system using complex model in which objects are glued by consistent system of contextual
connections. Crossing disciplinary borders even at a single contextual connection is unavoidable. Groups of
engineers develop and apply these models accessing modeling and other capabilities in accordance with
area of industry, disciplines, and human role. Appropriately configured and cloud-based modeling assures
integration of theory and practice in knowledge driven model system. The reported work is based on
analysis of the above situation at the Laboratory of Intelligent Engineering Systems. Formerly published
results were applied at this recent research to integrate engineering course in the above characterized
industrial engineering system using appropriately configured model. This paper outlines recent advanced
features of engineering modeling systems which support their application for the above purpose. This is
followed by novel concept of model mediated engineering course, methodology for university course
specific engineering model configuration, and possibility to realize course specific models in advanced
industrial modeling system environments. The objective of work is teaching and learning method which can
be applied at real industrial engineering modeling system in integration with research and industrial
engineering activities.
1 INTRODUCTION
Quick development of informatics, intelligent
computing, and computer technology is great
challenge for educators both at teaching
advancements and utilizing achievements in course
program. Working with contextual object
representation and system related theories,
methodologies and practice is great challenge for
researchers, practitioners and educators in
engineering modeling. Cooperating systems operate
engineering structure (ES) such as industrial
product, experimental arrangement, and concept
object. System based engineering modeling required
higher level abstraction than it was usual in classical
physical level of engineering modeling. While
physical level modeling defines and connects
physical components such as parts and assemblies,
system level modeling requires defining and connect
functional and logical level components of ES.
Arbitrarily complex model of ES is capable of self-
modification when any external and internal context
changes.
Practice awaits results to support connection of
higher education, research, and industrial processes
within a single purposeful engineering model. New
media is to be introduced for this purpose in the
form of advanced engineering model. Although this
paper provides results for application at education of
engineering, similar modeling can also be utilized at
other teaching areas such as archeology,
anthropology, etc.
The reported results were achieved at the
Laboratory of Intelligent Engineering Systems
where appropriate engineering modeling
environment is available. Work in this paper was
mainly based on formerly published own results in
organized driving chains for industrial product
model (Horváth, 2017), intellectual property
representation in multidisciplinary industrial
Horváth, L.
Model Mediated University Course in Engineering.
DOI: 10.5220/0006803704810488
In Proceedings of the 10th International Conference on Computer Supported Education (CSEDU 2018), pages 481-488
ISBN: 978-989-758-291-2
Copyright
c
 2019 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved
481

engineering model system (Horváth, 2016), product
behavior definition for requirements, functional,
logical, and physical (RFLP) structured engineering
model (Horváth, Rudas, 2015), and intellectual
resource driven virtual engineering environment for
higher education (Horváth, Rudas, 2016). Main
resources from other authors were in context-
sensitive synthesis of cyber-physical system model
(Canedo et. al.), model-based engineering using
systems engineering (SE) (Kleiner, Kramer, 2013),
connection of engineering education research with
learning sciences (Johri, Olds, 2011), and
development of expertise at engineering education
(Litzinger, et al, 2011).
The main objective of the reported work was to
integrate engineering course in appropriate industrial
engineering system using appropriately configured
model. This paper emphasizes the relevant new
features of engineering modeling systems preparing
introduction of novel concept for model mediated
engineering course. Rest of paper discusses
methodology for university course specific
engineering model configuration and possibility to
realize course specific engineering model in
advanced industrial modeling system. The proposed
solution is considered as milestone towards deep
information content based smart E-learning.
2 ENGINEERING MODEL AND
UNIVERSITY COURSE
Engineering model is about characterization,
connection, and behavior of engineering objects
(EOs). Recently, EOs are not only tangible features,
components, and units but also algorithms,
mathematical procedures and functions, physical
phenomena, analysis procedures, simulations,
engineering calculations, experience and expertise
representations, etc. (For more details see Figure 7).
Real time analyses and simulations evaluate
attempts to contribute models and prevent
inappropriate model objects. Content of an
engineering course can be included in appropriately
composed deep knowledge based active model to
replace passive course materials.
Current leading virtual engineering is result of
long development process for the past four decades.
Main stages of this process are summarized in
Figure 1. Development computer procedure
assistance of analysis, explanation, and
interpretation of documented information gradually
took the evaluation of documents from human. Next
stage of development was introduction of model
which described EOs. Annotations were still
required to explain content for application.
Integrated information model was milestone towards
structured computer representation of EOs.
Capability was restricted to mechanical, electrical,
electronic, computer or software engineering.
Development of object model was done towards
more integration and active knowledge driven
adaptive operation (Brière-Côté, A., Rivest, L.,
Desrochers, A., 2010). Beyond appropriate
knowledge items, adaptive operation of model
required consistent context structure. This allowed
propagation of modifications along chains of
contextually connected EOs.
Figure 1: Main stages of engineering model development.
Several published works below strengthen real
need for education program development towards
virtual engineering. Paper (Johri, Olds, 2011)
includes statement that engineering education
research needs more support from learning sciences
in theoretical and empirical work on engineering
learning. Widening contexts in modeling for
engineering assists development in this direction.
New product lifecycle management (PLM) course
concept is shown in (Eigner, M., Langlotz, M.,
Reinhardt, P., 2009). This work was supported by
model of product engineering project. Real
processes were considered in industrial context.
Students cooperated using process-based case
studies. Paper (Wolf, T., 2010) reports a work to
assess amount of learning observed in lectures and
laboratories. A graduate course on computer
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networks was investigated. It was concluded that
amount of learning during lectures and laboratories
was almost the same.
Human controls modeling procedures to generate
model of contextual EOs. In this way, human
contribution to model is indirect and depends on
capabilities provided by modeling procedures
(Figure 2). At the same time, model object
generation is also affected by outside contexts.
These contexts represent higher level decisions, law,
standards, knowledge carriers, etc. Engineers who
work on the same model complex can access
modeling capabilities and model objects in group
work depending on area of activity, disciplines
involved, and personal role. Engineers use cross-
discipline environment (Beier, G., et. al., 2013).
Outside contexts are connected using information
communication management capabilities.
Simulation of object behaviors is provided to
prevent definition of inappropriate EOs. Finally,
integrated storing, simulation, and evaluation of
closely connected models exclude accommodation
of model which is not appropriate for cooperation
with the related models.
Concept of disciple specific information unit of
engineering course (Figure 3) assisted development
of course representation in engineering model. Each
discipline is contextual with given set of modeling
capabilities. Topic must be contextual with well-
defined set of EOs. Choice of EOs can be extended
by user definition available in modeling systems. EO
behaves as feature. Feature modifies relevant
features using dedicated contextual connections of
parameters in the model.
Representation of information about principles
and methods is one of main challenges in definition
course as ES model. Efficient teaching and learning
processes are highly based on good examples.
Example can be easily generated as instance of
generic model. Assessment is created by purposeful
contexts utilizing real time checks, analyses, and
simulations. Real time response of model is novel
capability and shifts assessment into a higher level.
3 MODEL MEDIATED
ENGINEERING COURSE
Author of this paper think that current modeling
systems are in possession of capabilities to represent
all things which are needed to replace conventional
courses for model-based ones. Model mediated
engineering course is based on course configured
engineering model (CCEM). CCEM consists of
course specific purposeful contextual object model
and representation of course process (Figure 4).
Lecturer, student, and research, industrial, legal or
other partner communicates with modeling
environment through course specific access control.
Clarification of partner's role is very important.
Human interactions are opposed to living responses
of active engineering model.
Figure 2: Outlie of engineering model and its creation.
Figure 3: Information unit in engineering course.
Although active knowledge is represented in the
CCEM, human knowledge that does not contradict
represented active threshold knowledge is still very
important. Threshold knowledge is not allowed to
change during normal course processes. It can be
modified only by persons with special role. This
requires correct preparation from the side of lecturer
Model Mediated University Course in Engineering
483

and correct definition from the side of student. At
the same time, change of knowledge within the
allowable range is important to make what-if tests
during lecture and laboratory classes. Whereas
passive media cannot react, active model guarantees
quality of education.
Figure 4: Engineering course in virtual environment.
During course program for lecture, seminar, or
laboratory participants communicate with model to
explain its content, define object in the context of
existing ones, and carry out tests, analyses, and
simulations to experience the behavior of modeled
engineering objects. Course activities in engineering
model environment are done under control of
predefined course process (Figure 5). This can be
modified or omitted by lecturer in accordance with
the local measures for teaching and learning
processes.
The most important affairs between model and
participants are summarized and related in Figure 5.
Suppose that an actual concept is explained at a
given stage of course process. Concept is related to
one or more objects in engineering model.
Engineering model is object model. Object consists
of its class, place in taxonomy, parameters,
contextual connection between parameters, and
procedures to handle parameters. Object orientation
is one of the cornerstones of information technology.
According to experience at the Laboratory of
Intelligent Engineering Systems, object orientation
of engineering model can be well utilized at
teaching. In this way, object parameters and their
contextual connections are revealed and explained.
Active model facilitates built in and user defined
tests, analyses, and simulations using appropriately
configured objects, parameters, and contexts.
Figure 5: Engineering model at course.
Capabilities can be applied at generation of
arbitrary defined ES with the restriction by existing
active knowledge and role-based access. Model must
have consistent context structure. Trivial and other
effective contexts are enforced by modeling
procedures including contexts of selected capability,
engineering object, and interacting human.
Among wide range of capabilities for description
and representation engineering objects, their
parameters, and contextual connections shape
related modeling capabilities are shown in Figure 6.
Mathematical representation of arbitrary shape can
be composed using engineer understandable
features. On this physical level of model definition
shape feature is contextual with geometry, topology,
and attributes. Shape feature behavior means for
example that the shape is either on mechanical or on
electrical component of ES. Features build shape of
ES component. Inter shape features define relative
placing and movements of ES components.
Behaviors of EC components and their groups can
be analyzed in case of certain mechanical, heat,
magnetic or other loads using numerical
mathematics. Knowledge features are applied using
driving contextual connections with target object
parameters.
On functional and logical levels of ES model
functional and logical components are connected by
ports into structures. These models are virtually
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executable when behavior representations are
available in components.
System based product development forced
industrial companies to apply engineering system
which included modeling capabilities for research
including scientific configurations, contexts,
analyses, experiments, simulations, and procedures.
Research specific functions are available such as
design of experiments, definition of optimizing and
other algorithms, and methods from computation
intelligence. Engineering model allows placing
research results in wide context for evaluation and
verification. Research capabilities highly increase
relevance of engineering modeling systems to
doctoral research for PhD degree. Laboratory of
Intelligent Engineering Systems prepares
engineering modeling environment for research
jointly with the Doctoral School of Applied
Informatics and Applied Mathematics at the Óbuda
University.
4 UNIVERSITY COURSE
SPECIFIC ENGINEERING
MODEL
CCEM is an engineering model which is active at
course related activities during lectures, seminars,
laboratories, classroom tests, and individual work.
Course specific engineering model defines and
organizes objects according to content of course
program. This supposes that objects in subject
material of engineering education can be included in
engineering object (EO) representations.
Figure 7 is an attempt to summarize EO
categories which are well proven in advanced
engineering modeling systems and can be applied at
course specific modeling. EOs are included in model
of ES for ES components, for knowledge applied at
definition and modification of components, and for
tools which are used regarding the above two
groups. Figure 7 tells us that conventional teaching
content includes elements which can be processed
into EOs in engineering model. Grouping
engineering objects in Figure 7 serves only analysis
of engineering model for the application at
university course. Well proven modeling
methodology is available to include any EO on
Figure 7 in engineering model where it is active
through its contextual connections.
Figure 6: Shape related modeling capabilities.
Representation of ES component part consists of
geometry for curves and surfaces, topology for
structure of geometry in boundary, and form features
for definition of shape boundary using series of
engineer understandable modifications. The result is
solid body representation which has contexts from
curves and surfaces. Engineering connection
connects solid bodies using definitions of placing
constraints, degrees of freedom, and connecting
means. Material engineering object may be very
complex including formulas and other means to
calculate properties at different conditions. Physical
parts and their connected units are visible. When ES
definition starts on the level of systems and
multidisciplinary modeling is required, port
connected functional components drive port
connected logical components. At the same time,
definition of physical level components needs
contexts from the logical level components.
Functional and logical components are in ES wide
structures.
The second group of EOs (Figure 7) is
knowledge. Significance of knowledge in
engineering model was increased during the past
Model Mediated University Course in Engineering
485

decade because reusable knowledge representations
drive generation of model objects at frequent
modifications of EOs and contexts during lifecycle
of ES. In this scenario, principles are recognized
behind relationships and phenomena, methods for
definition engineering objects, and behaviors of
modeled EO components and structures, and
experience and expertise serve as knowledge
contexts of relevant EOs.
Figure 7: Engineering objects.
The third group of EOs (Figure 7) includes tools
which are applied at handling the other two groups.
Tools are algorithms for optimizing and other
purposes, object parameter related procedures,
modeling and other processes, numerical and other
mathematical functions and procedures, dedicated
analyses for various EO parameters, structures of
contextual simulations, and engineering calculations.
Significance of mathematics was increased with
need for more sophisticated ES models. Paper
(Machado, J. A. T., et. al., 2016) introduces method
to include approximate-analytical mathematical
method in engineering solutions. Annotations
communicate passive information between
participants. They contain document entities in
engineering model and are attached to any EO
representation.
Figure 8 illustrates objects and their contextual
connections in the proposed model. Suppose that we
analyze objects O
1
and O
2
. Each has three
parameters. Contextual connection C2 is defined
between parameters of O
1
and O
2
, while C1 and C3
are defined between parameters of O
1
and O
2
and
other objects. Proper operation of engineering model
requires consistent structure of these contextual
connections. Methods are researched for analysis of
consistency (Horváth, L., 2017). Notice at any lack
of contextual connection is inevitable.
Figure 9 serves better understand of key
procedures around EO. Suppose that an EO
represents some actual subject matter for teaching
and learning. Course model includes parameters for
characterization of EO and related definition
procedures which are to be explained. This must be
correct representation of content collected among
others from conventional passive notes,
presentations, and other teaching materials. When
model is adequately defined, its exploration shows
the required content. Full parametrized generic
engineering model is required for this purpose.
Parameters for characterization of the contextual EO
representations and the applied definition procedures
are to be explained.
Figure 8: Objects and connections.
Access to course purposed engineering model
using role-based authorization (Figure 9) has key
importance. Participants access model by course
specifically configured control of authorization.
Change and definition of objects, their parameters,
and contexts are possible in accordance with actual
mode. Mode may authorize for modification only
during a session, including new model version in the
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system, or development of the course specific
engineering model.
5 IMPLEMENTATION ISSUES
Development and maintenance of the above model is
challenging task and needs expertise in engineering,
teaching, and modeling. The main benefits are the
availability high amount inherently active
knowledge in the modeling system and that
considering of this knowledge is enforced by
modeling procedures. Despite advanced modeling
capabilities and built in knowledge, quality of model
and success of model-based course still highly
depends on participant qualities.
Figure 9: Scenario around an actual engineering object.
Implementation of course model supposes
availability of comprehensive, reliable, and proven
engineering modeling system which is in possession
of correct active knowledge, allows for local
knowledge in model, and supports system level
multidisciplinary generic representation of ESs.
Work in a user group which is configured within
very complex and increasingly smart engineering
modeling system is still a challenge even for
professionals. The question may be emerged in
reader that how teachers and students can cope with
the difficulties of working in such environments.
Anyway, students must be prepared for this type of
work in the future.
Figure 10: Main steps of model design.
Essential work of implementation is design of
the demanded course specific engineering model.
Main steps of design are sketched in Figure 10. First
task is to decide and characterize the purposes of
modeling activities. Following a student-oriented
schema, purposes are explanations of teaching
content, guiding student at learning and individual
work, consult student, individual work of student for
classroom tests and assignments, and examinations.
The next step is definition of topics in course
program and relevant active knowledge and
contexts. Threshold knowledge is defined as
knowledge which will be enforced by the modeling
procedures. Original threshold knowledge can be
extended by user definitions in modeling system.
Following this, the demanded engineering objects
and their contexts are defined. Knowledge items are
considered as engineering objects in accordance
with Figure 7. The rest tasks are definition of model
construction and application process and placing the
planned models in an actual engineering model
system.
The Laboratory of Intelligent Engineering
Systems has been experimenting with real-world
courses in modeling environment for ten years. This
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487

activity prepares experiments with CCEM courses.
A new and most recent engineering modeling
environment is under preparation at this laboratory.
Challenge may be lack of the required modeling
expertise. Moreover, system and multidisciplinary
engineering organized teaching subjects may be
strange for teaching personnel.
Fantastic advancement is that current modeling
procedures do not allow generation of obviously
erroneous model entities. At the same time, this
requires highly prepared teaching personnel.
Anyway, this is expected at university level.
Appropriately formed working team on the Internet
can help with remotely working members having the
necessary expertise.
6 CONCLUSIONS
Moving engineering activities to virtual systems is a
long history. Comprehensive projects with fully
integrated engineering would be impossible without
smart engineering modeling. This also means that
involving latest engineering technology is
unavoidable in higher education programs.
This paper shows a pioneer concept and
methodology to realize subject matter for university
course in the form of purposeful engineering model.
Working with this model student will experience
engineering work where knowledge will be active,
and representations will “live” as it can be expected
in the contemporary info-communication world.
Author thinks that the only solution is application of
industrial professional engineering modeling system
in a laboratory which is available at all types of
teaching and learning.
Teaching engineers must follow advances which
are towards wide application of virtual environments
to integrate active knowledge. This paper is a
contribution to these efforts.
ACKNOWLEDGEMENTS
The author gratefully acknowledges the financial
support by the Óbuda University.
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