Fuzzy Set Theory and Fuzzy Logic for Activities Automation in Engineering Education

Fuzzy Set Theory and Fuzzy Logic
for Activities Automation in
Engineering Education
M. Ivanova
Technical University of Sofia
College of Energy and Electronics
XXVIII International Scientific Conference Electronics - ET2019
September 12 - 14, 2019, Sozopol, Bulgaria

The aim
An analysis regarding the applications of Fuzzy
set theory and Fuzzy logic in engineering
education for (semi) automating a wide variety
of engineering tasks is performed.
The possibilities for reaching suitable and well-
defined approaches when the situation is
characterized with unclearness and complexity
are outlined.

Theories of Fuzzy sets and Fuzzy logic
• Used for analyzing real world systems by creating
their fuzzy models
• The processes typical for building a fuzzy system
are:
– fuzzification – allowing the possibility for description of
its ambiguity and complexity through fuzzy sets, fuzzy
membership functions, linguistic variables;
– Fuzzy inference engine – applying different fuzzy
methods, techniques and algorithms leading to
conclusions; utilization of fuzzy rules in the form
if/and/or/then that facilitate reaching the conclusion;
– defuzzification – usage of different methods to convert
fuzzy conclusions in crisp values.

Fuzzy Theory and Fuzzy Logic
Applications in Engineering Education
• Activities before teaching/learning processes
For engineering curriculum design which has to include a
given number of courses that are classified in four groups:
fundamental, domain, specialty and complementary
(O. Bologa, R.E. Breaz, S.G. Racz, “A Fuzzy-based decision support tool for
engineering curriculum design”, 2015)

Fuzzy Theory and Fuzzy Logic Applications
in Engineering Education
For selection and ranking the courses
for undergraduate engineering
students
F. Ersöz, C. Hakan Kinci, T. Ersöz, “A model proposal
for course selection with the fuzzy MOORA
approach”, 2018
For identification of the important
factors for successful eLearning
design
Y. Kazancoglua and M. Aksoya, “A fuzzy logic-based
QFD to identify key factors of e-learning design”,
2011
For identification of suitable
engineering institutions
P. Mahendran, “A Fuzzy AHP Approach for selection
of measuring instrument for engineering college
selection”, 2014
For selection of effective eLearning
provider
Y. Kazancoglua and M. Aksoya, “A fuzzy logic-based
quality function deployment for selection of e-
Learning provider”, 2011
Activities before teaching/learning processes

Activities typical for educational process
To evaluate forth year students’
performance during their participation
in engineering courses according to
their skills, knowledge and attitudes
N. Aruna Kumari, D. N. Rao, M. Sudhir Reddy,
“Indexing student performance with fuzzy logics
evaluation in engineering education”, 2017
To improve collaborative eLearning
where students have possibility to
publish their explanations about a
given topic
F. A. D’Asaro, V. Perticone, M. E. Tabacchi, “A fuzzy
methodology to alleviate information overload in
eLearning”, 2013
For realization of peer-assessment
eLearning environment to reduce the
teachers work in evaluation of the
students’ assignments
P. Luukka and M. Collan, “Using a linguistic
scorecard for peer-assessment through an on-line
system, Multiple criteria multiple peer-assessment
with linguistic inputs”, 2013

To identify suitable research topics for each
student at project preparation according to
his self-assessed skills and declared interests
M. Fuad Abdul Latip et al., “Implementation
of fuzzy logic-based final year project
student-supervisor matching system”, 2017
For development of adapted eLearning
system that evaluates the learners’
knowledge and recommends suitable
learning resources
M. Al Duhayyim and P. Newbury, “Concept-
based and fuzzy adaptive e-learning”, 2018
For quantitative/qualitative evaluation of
lecturing teams’ performance (each team
includes a professor and an assistant
professor)
M. Lambovska, “Control on teams: A model
and empirical evidence from Bulgaria”, 2018

Activities after graduation
- For evaluation of employers’ satisfaction regarding the
performance of engineering graduates
Y. Md Yusoff, M. Zaidi Omar, A. Zaharim, “Evaluation of graduates’ performance
using fuzzy approach”, 2013

Conceptual Model for Fuzzy Theory and Fuzzy Logic
Utilization in Engineering Education
Activities before teaching/learning processes
Activities after graduation
Curriculum design Course
selection and
ranking
Selection of engineering institution
eLearning provider selection
Students’
performance
evaluation
Project
preparation
Learning
styles
evaluation
Facilitation of
personalized, peer-,
collaborative eLearning
Learners’
classification
Materials
recommendation
Teachers’
performance
evaluation
Educational
services
evaluation
Evaluation of engineering graduates
eLearning design
Learning paths
evaluation
Learning styles
prediction
Learning
performance
prediction
Decision making

The model presents the typical usage of Fuzzy theory
and logic that could be classified in the following
groups:
(1) selection and ranking of objects, characteristics and
attributes;
(2) evaluation of events, processes, services,
competences and skills, behavior, features,
performance;
(3) recommendation of learning materials;
(4) students classification in groups,
(5) decision making in teaching and learning;
(6) prediction of behavior, performance, characteristics

The created model contributes to the following issues:
• The developed model could be used as knowledge source for
educators and researchers presenting the current state of
Fuzzy theory applications in engineering education and
eLearning
• It could be used as starting point for further exploration and
detailed analysis of a concrete topic and application
• The model could be utilized as guidance showing the most
common fields for automation of educational-related activities
that require a well-defined and precise solution
• It could be seen as a driver for ideas concerning building
intelligent and innovative solutions in different educational
scenarios and context based on Fuzzy theories

Conclusion
• The problems typical for engineering education and
situations that are characterized with complexity,
dynamics and blurriness and that are successfully solved
through the application of Fuzzy set theory and Fuzzy
logic are outlined
• A conceptual model is proposed and it will be used in the
future work focused on design and implementation of
automated solution for improvement the quality of self-
learning in formal and informal educational settings
ACKNOWLEDGMENT
The author would like to thank the Research and Development Sector at the
Technical University of Sofia for the financial support.

Thank you for your attention!
The used picture is taken from: https://d1vpzb8ccuu79x.cloudfront.net/wp-
content/uploads/keolis-1.jpg

Fuzzy Set Theory and Fuzzy Logic for Activities Automation in Engineering Education

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