Opatija, Croatia, 2012.
Boban Vesin, Aleksandra Klašnja-Milićević
Higher School of Professional Business Studies
Novi Sad, Serbia
e-mail: {vesinboban, aklasnja}@yahoo.com
Mirjana Ivanović, Zoran Budimac
Department for Mathematics and Informatics
Faculty of Science, Novi Sad, Serbia
e-mail: {mira, zjb}@dmi.uns.ac.rs
Protus 2.0: Ontology-based semantic
recommendation in programming
tutoring system
Presentor: Boban Vesin
Contents
• Introduction
• Personalization of content
• Used technologies
• Protus 2.0 architecture
• Ontologies in Protus 2.0
• Implemented rules
• Learner’s interface
• Conclusion
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Introduction
•
•
•
•
Semantic Web technologies
Educational environments
Ontologies
Ontologies provide a vocabulary of
terms whose semantics are formally
specified
• Ontologies need additional rules to
make further inferences
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Into Personalisation Technologies Arcitecture Ontologies Rules Interface Conlusion
Introduction
• The major goal of learning systems is to support a
given pedagogical strategy
• Ontologies can be associated with reasoning
mechanisms and rules to enforce a given adaptation
strategy in learning system
• Protus - PRogramming TUtoring System
• Adaptation of the teaching material and navigation in
a course based on the principles of Learning styles
recognition for a particular learner
• The main objective of the presentation is to present
new version of Protus that completely relis on
Semantic web technologies
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Into Personalisation Technologies Arcitecture Ontologies Rules Interface Conlusion
Personalization of content
• Customization of content to match
characteristics specified by the learner
model
• Protus 2.0 provides two general
categories of personalization based on
recommender systems
– Content adaptation
– Learner interface adaptation
• Adaptation based on the learning style
of the learner
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Into Personalisation Technologies Arcitecture Ontologies Rules Interface Conlusion
Learning styles identification
• Index of Learning Styles (ILS)
• ILS assesses variations in individual learning
style preferences across four dimensions or
domains:
– Information Processing: Active and Reflective
learners,
– Information Perception: Sensing and Intuitive
learners,
– Information Reception: Visual and Verbal learners,
– Information Understanding: Sequential and Global
learners.
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Into Personalisation Technologies Arcitecture Ontologies Rules Interface Conlusion
Characteristics of learners
Active
Reflective
Work in groups
Work alone
Preference to try out new material immediately
Preference to take time to think about a problem
(Ask, discuss, and explain)
Practical (Experimentalists)
Fundamental (Theoreticians)
Sensing
Intuitive
More interested in overviews and a broad
More patient with details
knowledge (bored with details)
By standard methods
Innovations
Senses, facts and experimentation
Perception, principles and theories
Visual
Verbal
Preference to perceive materials as pictures,
Preference to perceive materials as text
diagrams and flow chart
Global
Sequential
Prefer to get the big picture first
Prefer to process information sequentially
Assimilate and understand information in a linear Absorb information in unconnected chunks and
and incremental step, but lack a grasp of the big achieve understanding in large holistic jumps
picture
without knowing the details
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Into Personalisation Technologies Arcitecture Ontologies Rules Interface Conlusion
Used technologies
• OWL - Ontology Web Language
• Protégé - ontology editor
– SWRLTab
• SWRL - Semantic Web Rule Language
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Into Personalisation Technologies Arcitecture Ontologies Rules Interface Conlusion
Protus
• Different courses and domains
• Highly modular architecture
• Five central components:
– the application module
– the adaptation module
– the learner model
– session monitor
– domain module
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Overall architecture of Protus
Server side of system
Learner model
ontology
Session monitor
Teaching strategy
ontology
Domain
module
Adaptation module
Learner’s interface
(interface ontology)
Task
ontology
Domain
ontology
Learner model
Application
module
Teacher’s interface
Communication ontology define conection between components
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Into Personalisation Technologies Arcitecture Ontologies Rules Interface Conlusion
An excerpt of domain ontology
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An excerpt of resource topology
ResourceType
ResourceType
CompliteCode
subTypeOf
FullProgram
subTypeOf
ResourceType
subTypeOf
subTypeOf
ResourceType
Task
ResultTask
subTypeOf
ResourceType
ResourceType
ErrorsTask
ExaminationalMaterial
ResourceType
subTypeOf
ConsistOf
CorrectCodeTask
ResourceType
ResourceType
DomainResource
Exam
ResourceType
Excercise
subTypeOf
subTypeOf
subTypeOf
ResourceType
AdditionalMaterial
subTypeOf
ResourceType
ResourceType
CourseMaterial
Example
subTypeOf
subTypeOf
subTypeOf
subTypeOf
subTypeOf
subTypeOf
ResourceType
ResourceType
ResourceType
ResourceType
ResourceType
ResourceType
Introduction
BasicInfo
Goals
Theory
SintaxRule
ProjectAssignments
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Learner model ontology
Class
Class
hasRole
Sequential/Global
Class
Teacher
isCategoryOf
Performance
Class
Class
haslPerformance
User
hasRole
Class
Class
Class
haslInfo
PersonalInfo
Learner
isCategoryOf
Active/reflective
LearningStyleCategory
isCategoryOf
Class
hasCategory
Visual/Verbal
Class
haslLearningStyle
LearningStyle
isCategoryOf
Class
Sensing/Intuitive
Class
Active/reflective
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Ontology for learner observation
Class
Learner
Class
Performance
hasInteraction
Class
hasGrade
hasResult
Session
partOf
External
Class
Float
Interaction
began
conceptUsed
ended
hasType
External
Class
Concept
TimeAndDate
Class
InteractionType
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Teaching Strategy ontology
Class
hasLearningStyle
Class
LearningStyle
generates
Class
Learner
Condition
generates
has Performance
Class
Class
Decision
Performance
basedOn
determines
Class
Class
basedOn
Personalization
BehaviourPattern
basedOn
Class
isTypeOf
Class
Resouce
consistsOf
Class
NavigationSequence
Class
isTypeOf
AdaptationType
CurrentGoal
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Implemented rules
• In Protus:
– the interface elements for sequential
navigation are hidden/shown
– Different presentation methods
– Adding of links to related or more complex
content
• Three groups of rules:
– learner-system interaction rules
– off-line rules
– recommendation rules
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Examle of implemented rules
• The form of the rules:
antecedent -> consequent
• Following rule updates learner model:
Learner(?x)  Interaction(?y) 
hasInteraction(?x,?y)  Concept(?c) 
conceptUsed(?y,?c)  Performance(?p)
 hasResult(?y,?p)  hasGrade(?p,?m)
 swrlb:greaterThan(?m, 1) 
isLearned(?c, true) 
hasPerformance(?x,?p)
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User Interface of Protus
• Web pages for students
– online tutorial with numerous resources
– testing knowledge
– communication with teachers and other
students
• Learning styles identification
• Initial assessment is based on the
ILS Questionnaire
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ILS Questionnaire
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Result of ILS questionnaire
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Information Processing:
User interface for Activists
User interface for Reflectors
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Information Perception
• Recommendation of Additional material
option for Sensing learners
• Recommendation of Syntax rules option
to Intuitive learner
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Into Personalisation Technologies Arcitecture Ontologies Rules Interface Conlusion
Information Reception:
• Example of lesson for Visual learners
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Information Reception:
• Example of lesson for Verbal learners
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Into Personalisation Technologies Arcitecture Ontologies Rules Interface Conlusion
Information Understanding
• Elements for Global Learners
• Navigation for Sequential learners
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User interface of Protus 2.0
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Into Personalisation Technologies Arcitecture Ontologies Rules Interface Conlusion
Conclusion
• We presented how Semantic Web
technologies and in particular ontologies
can be used for building Java tutoring
system
• Architecture for such adaptive and
personalized tutoring system that
completely relies on Semantic Web
technologies was presented
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Opatija, Croatia, 2012.
Boban Vesin, Aleksandra Klašnja-Milićević
Higher School of Professional Business Studies
Novi Sad, Serbia
e-mail: {vesinboban, aklasnja}@yahoo.com
Mirjana Ivanović, Zoran Budimac
Department for Mathematics and Informatics
Faculty of Science, Novi Sad, Serbia
e-mail: {mira, zjb}@dmi.uns.ac.rs
Protus 2.0: Ontology-based semantic
recommendation in programming
tutoring system
Presentor: Boban Vesin