International Journal of Application or Innovation in Engineering & Management (IJAIEM)
Web Site: www.ijaiem.org Email: editor@ijaiem.org, editorijaiem@gmail.com
Volume 2, Issue 3, March 2013
ISSN 2319 - 4847
Designing ontology-based academic course for
‘Theory of Computation’ to facilitate
personalized e-learning system
Sujeet Kumar1 and Md. Tanwir Uddin Haider2
1,2
National Institute of Technology, Patna
ABSTRACT
The increasing awareness of e-learning with aid of reusable ontology led to partial development of ontology for few subjects.
Ontology aids to organize the structure of information on the basis of commonly accepted vocabulary among the researchers,
these can be accessed via software agents applying semantic web concepts. This reusability saves the instructor’s time to make
use of already build ontology via integration and merging. The main goal of e-learning environment is to present content in
efficient manner for improving learner’s performance and their interest of learning. Many educational researchers had
acknowledged interconnection involving the learning style and the performance of learner, as compared to the perspective of
conventional classroom environment. This Paper makes use of widely accepted Peter Honey and Alan Mumford learning style
model to group learner (personalized) and on the basis of learner’s learning style the content of subject named Theory of
computation (TOC) is provided applying semantic inference rules. The ontology for TOC subject has been developed using
Protégé 4.2 alpha tool.
Keywords: Ontology, Semantic web, software agent, e-learning, inference rule.
1. INTRODUCTION
The Internet has doubled in size every year since 1969; current statistics of internet user across the world has crossed
the two billion. Internet revolution and advancement in semantic web approach led to adoption of web based learning
system. E-learning based on semantic approach serves in imparting educational goal with objective of utilizing the
student inherits characteristics. Semantic web integrates heterogeneous data, facilitates interoperability and provides
service for optimized querying, searching and navigation [1]. One important component of semantic web is ontology
that is study of existence [2]. Ontology defines a common vocabulary for researchers who need to share information in
a domain [3]. It includes machine-interpretable definitions of basic concepts in the domain and relations among them.
The W3C standard for Semantic Web includes OWL (Web Ontology Language) and RDF (Resource Description
Framework).
Several issues like “teacher bandwidth”, i.e. the number of learners a single instructor can successfully mentor, have
been primary bottleneck in conventional learning system [4]. Also in traditional approach the same course content is
delivered to all kind of learner neglecting individual’s learning style. In current scenario one’s knowledge is accredited
on the basis of evaluation result. Nevertheless performance upgrade is essential for academic and professional front.
Learning style reflects the unique preference of an individual towards receiving grasping the newly processed
information and later ability to recall and organize those data.
These problems can be addressed by e-learning environments, which is capable of supporting a one to one
communication [5]. Many educational researchers had acknowledged interconnection involving the learning style and
the performance of learner, as compared to the perspective of conventional classroom environment.
In this Paper ontology upper layer ontology has been proposed for Theory of Computation (TOC) course that is being
taught in undergraduate program in engineering field. This Paper draw upon Peter Honey and Alan Mumford
Questionnaire, which is based on Kolb’s learning style model, for grouping the learner style (personalize) and present
the personalized content based on inference rule. The ontology for TOC subject has been developed using Protégé 4.2
alpha tool.
2. RELATED WORK
Kolb’s [6] provided relatively flexible account of learning styles claims that concrete experience and abstract
conceptualization reflect right- and left-brain thinking respectively. The right brain is supposed to be initial receiver of
all information and it globally processes .The left brain is in charge of language and speech production, it processes the
information sequentially and those in which this part is dominant are highly structured logical and organized.
Volume 2, Issue 3, March 2013
Page 374
International Journal of Application or Innovation in Engineering & Management (IJAIEM)
Web Site: www.ijaiem.org Email: editor@ijaiem.org, editorijaiem@gmail.com
Volume 2, Issue 3, March 2013
ISSN 2319 - 4847
Kolb’s Learning Style Inventory (LSI) comprises of four categories: -The converging style (abstract, active), the
diverging style (concrete, reflective), the assimilating style (abstract, reflective) and the accommodating style (concrete,
active). The converging style relies primarily on abstract conceptualization and active experimentation, they are good at
problem solving, decision making and prefers dealing with technical problems rather than interpersonal issues. The
diverging style is imaginative and aware of meanings and values. The assimilating style likes to reason inductively and
to create. The accommodating style likes doing things, carrying out plans.
Felder-Silverman [7] proposed four dimensions of learning styles viz. active-reflective, sensing-intuitive, visual-verbal
and sequential-global based on information processing model of the learner. An individual can check their learning
style based on Felder and Soloman [8] which consists of forty-four questions each of having four alternative answers.
Honey & Mumford [9] proposed four learning dimensions named activists, reflector, theorist and pragmatists. The
activist group are open minded and enthusiastic, reflectors prefers to observe and takes time before reaching
conclusion, theorists are logical whereas pragmatists prefers to solve practical problems and ready to try new ideas.
Two set of questionnaires i.e. 80 item versions and 40 item versions has been proposed. The first type comprised of is
20 questions per style and is supposed to be suitable for longer session of interaction and feedback with learner.
Whereas 40 item version has 10 questions for each style and it is suitable for short term learning session, as few
suggestions has been designed for action as compared to aforesaid questionnaire.
Md. Tanwir Uddin Haider, Aditya K Sinha and Banshi Dhar Chaudhary [10] have proposed about the interconnection
between academic deficiency and learning style of learner in traditional education system. The results were based on
result and statistics of experiment conducted for end-semester exams and online quizzes. This work makes use of
Felder-Silverman learning dimensions.
The design and prototype implementation of an adaptive e-textbook for Theory of computation course by using
ActiveMaths has been proposed by Eric Andr`es, Rudolf Fleischer and MinEr Liang [11]. ActiveMaths provides
mathematical environment for technology enhanced learning on the web. The performance of the learner is checked
with variour feedback like homework, quizzes, background knowledge and feedback.
Ling Jiang, Chengling Zhao and Haimei Wei [12] have proposed ontology for computer network based on Topic Maps.
TM4L software has been used to browse and create educational topics.
Ontology for Software Engineering has been proposed by Yajing Zhao, Jing Dong and Tu Peng. This paper work
enumerates some benefits of ontology to critical issues related to various domain of approach in Software engineering
domain.
José R. Hilera, Luis and Fernández-Sanz [13] have proposed domain ontology based on IEEE glossary of software
engineering. In this paper CMMI level domain has been categorized into concepts (class).
An architecture of e-learning system based on Dunn and Dunn learning style has been proposed by Christian wolf.
Multimedia learning and adaptive hypermedia environment has been taken into consideration for presenting the
content matter.
Zhang jinghua [14] has proposed personalized learning for programming course. The SWRL rule has been used for
standard representation and automatic reasoning
3. METHODOLOGY
In this Paper, ontology for Theory of Computation (TOC) course that is being taught in undergraduate program in
engineering field has been proposed. In this work the content for Theory of computation course is being provided
automatically applying inference rules of semantic web, on the basis of Learner’s learning style. To test the style of
learning Peter Honey and Alan Mumford Questionnaire, which is based on Kolb’s learning style model has been used.
The proposed approach will help to identify the learning domain of learner’s which will help the instructor to build the
more suitable instruction process. It will also help to enhance the performance of individual learner by making
interesting, motivating, interactive, and feedback session and aids for on demand learning approach which would
motivate learners to pursue higher education.
4. ONTOLOGY DESIGN
In this Paper, work has been focused on the limited content matter of the subject focusing on the types of Automata,
Types of grammar, formal languages and their properties. This layout has been derived by considering the sequence
from book titled “Introduction to Automata theory, Languages and Computation” [15]. The ontology has been
developed using Protégé 4.2 alpha.
Figure 1 show the snapshot of ontology for Theory of computation developed on the protégé interface. Thing is inbuilt
super class provided by the protégé tool. Topics like Automata, Formal languages and Grammar , which are major
domain of this subject has been partitioned into classes and further branching based on relevance has been developed
on the basis of content taken from “Introduction to Automata Theory, Languages and Computation”. For instance
Finite automata, linear bounded automata, pushdown automata and Turing machine are four types of automata.
Volume 2, Issue 3, March 2013
Page 375
International Journal of Application or Innovation in Engineering & Management (IJAIEM)
Web Site: www.ijaiem.org Email: editor@ijaiem.org, editorijaiem@gmail.com
Volume 2, Issue 3, March 2013
ISSN 2319 - 4847
Figure 1: Screenshot of TOC ontology on protégé interface
Figure 2 shows the Ontograph view of TOC ontology. Ontograph is ontology visualization plug-in for protégé. This
interface displays the concept (class) and their hierarchy in various forms like spiral, grid horizontal and vertical tree
structure. This view helps to give a graphical aspect of the proposed ontology without showing their underlying
relations name (like is subclass of). This view aid to give clear ideas and is very handy when there are numerous topics
involved for larger application. This view is horizontal tree structure of the proposed ontology for Theory of
computation course.
Figure 2: Ontograph view of TOC ontology
Figure 3 shows the Owl Viz view of TOC ontology. Owl viz is also a plugin environment compatible with protégé. It is
an owl visualization tool which displays the class hierarchy graphically and helps to navigate them. This view helps to
Volume 2, Issue 3, March 2013
Page 376
International Journal of Application or Innovation in Engineering & Management (IJAIEM)
Web Site: www.ijaiem.org Email: editor@ijaiem.org, editorijaiem@gmail.com
Volume 2, Issue 3, March 2013
ISSN 2319 - 4847
generate the graphical structure of ontology content along with is-a relation for class and subsequent sub class in the
hierarchy.
Figure 3: Owl Viz view of TOC ontology
Figure 4 shows snapshot of partial OWL code generated in protégé tool. The upper layer ontology designed is
represented in OWL, which is accepted as the standard by W3C. The generated code is machine understandable and its
structure of tags resembles with XML, as Owl is based upon XML and RDF concepts. Inference rules could be used to
deduce the desired result for indexing and searching.
Figure 4: Snapshot of owl code in protégé interface
Volume 2, Issue 3, March 2013
Page 377
International Journal of Application or Innovation in Engineering & Management (IJAIEM)
Web Site: www.ijaiem.org Email: editor@ijaiem.org, editorijaiem@gmail.com
Volume 2, Issue 3, March 2013
ISSN 2319 - 4847
5. SCOPE & LIMITATION
Scope of the Paper is limited to e-learning domain. Upper layer ontology has been proposed for important topics of the
subject like the types of Automata, types of grammar, formal languages and their properties. Many other issues like
aberration from detected style, changes in style based on ages e.g. have not been taken into account.
6. CONCLUSION
With economical and easy access of web resources via internet, both government and many educational institutions
worldwide are giving emphasis on e-learning to attain the goal of global knowledge. This work is an effort to design
personalized e-learning system for Theory of computation (TOC) by making use of learning style concepts and
semantic web technology. The proposed approach will help to identify the learning domain of learner’s which will help
the instructor to build the more suitable instruction process. It will also help to enhance the performance of individual
learner by making TOC course more interesting, motivating, interactive, and feedback session which aids on demand
learning approach to motivate learners to pursue higher education.
1. FUTURE WORK
The proposed work is in its early stage of development. The scope of further improvement on ontology optimization
could be everlasting area. Further works includes making inference rules based on the learning style of learners. Rules
could be used to interlink upper layer ontology and corresponding data source on the fly. A more improved version of
work would comprise of all the dimensions of Honey and Alan Mumford’s learning style. Further the work could be
taken into practical implementation based on feedback of student’s evaluation. More work need to be done in context of
inference based on performance of learner, navigation, ontology standardization and collaboration of all these would
lead an era of personalized e-learning system.
REFERENCES
[1] Yanyan Li, Mingkai Dong, ”Towards a Knowledge Portal for E-Learning based on Semantic Web”, Eighth IEEE
International Conference on Advanced Learning Technologies, pp. 910-912, 2008.
[2] Yajing Zhao, Jing Dong and Tu Peng, "Ontology Classification for Semantic-Web-Based Software Engineering”,
IEEE TRANSACTIONS ON SERVICES COMPUTING, VOL. 2, NO. 4, pp.303-317, OCTOBER DECEMBER
2009.
[3] Natalya F. Noy and Deborah L. McGuinness,” Ontology Development 101: A Guide to Creating Your First
Ontology”.
[4] Dimitris Kotzinos, Sofia Pediaditaki, Apostolos Apostolidis, Nikolaos Athanasis, Vassilis Christophides, “Online
Curriculum on the Semantic Web:The CSD-UoC Portal for Peer-to-Peer E-learning”, The International World
Wide Web Conference Committee (IW3C2), WWW 2005, Chiba, Japan, pp. 307-314, May 10-14, 2005.
[5] Christian wolf, " iWeaver: Towards 'Learning Style'-based e-Learning in Computer Science Education",
Australian computer society, ACE2003, VOl. 20.
[6] Alice Y. Kolb, David A. Kolb, "Experience Based Learning Systems”, May 15, 2005.
[7] Felder, Richard M.(1996), “Matters of style”, ASEE Prism, 6(4),18-23.
[8] Soloman,
Barbara
A.,
Felder,
Richard M.: “Index of Learning Styles Questionnaire”,
http://www.engr.ncsu.edu/learningstyles/ilsweb.html.
[9] Peter Honey and Alan Mumford, ”The learning style questionnaire”, July 2006.
[10] Md. Tanwir Uddin Haider, Aditya K Sinha and Banshi Dhar Chaudhary, “An Investigation of relationship
between learning styles and performance of learners”, Vol. 2(7), 2813-2819, 2010.
[11] Eric Andr`es, Rudolf Fleischer and MinEr Liang,, "An Adaptive Theory of Computation Online Course in
ActiveMath", ICCSE 2010, IEEE, 2010.
[12] Ling Jiang, Chengling Zhao,Haimei Wei, "The Development of Ontology-Based Course for Computer Networks"
,International Conference on Computer Science and Software Engineering, pp. 487-490, 2008
[13] José R. Hilera, Luis and Fernández-Sanz,"Developing Domain-ontologies to Improve Software Engineering
Knowledge", Fifth International Conference on Software Engineering Advances, pp. 380-383, 2010.
[14] Zhang jinghua,"A Semantic Web Based Personalized Learning Service for Programming Course in E-learning",
International Conference on Mechatronic Science, Electric Engineering and Computer Jilin, China, pp.1563-1566,
August 19-22, 2011.
[15] J.E.Hopcroft, Rajeev Motawani and J.D. Ullman, “Introduction to Automata Theory, Languages and
Computation”, (Pearson Education Asia) 2nd Edition.
[16] Protégé-2000 (http://protege.stanford.edu)
[17] Web Ontology Language OWL, http://www.w3.org/2004/OWL, 2009.
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