Ontologies for Effective Use of Context in e-Learning Settings

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Ontologies for Effective Use of Context in e-Learning Settings

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Ontologies for Effective Use of Context in e-Learning Settings Dragan Ga evi 1, Jelena Jovanovi 2, Colin Knight3, Griff Richards3 1School of Computing and ... –

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Title: Ontologies for Effective Use of Context in e-Learning Settings

1
Ontologies for Effective Use of Context in
e-Learning Settings

Dragan Gaševic1, Jelena Jovanovic2,
Colin Knight3, Griff Richards3
1School of Computing and Information System,
Athabasca University
dgasevic_at_acm.org
2FON-School of Business Administration,
University of Belgrade
jeljov_at_gmail.com
3School of Interactive Arts and Technology, Simon
Fraser University
cjk, griff_at_sfu.ca

2
What we do not have today and we need
Individualized personalized learning supported
by ICT Adaptive and contextualized learning
experience supported by ICT Effective and
efficient information, community, and expert
retrieval, based on context and
semantics Conceptual modeling of different
knowledge domains
(Roadmap for Technology Enhanced Professional
Learning, 2007)
3
What we do not have today and we need
Individualized personalized learning supported
by ICT Adaptive and contextualized learning
experience supported by ICT Effective and
efficient information, community, and expert
retrieval, based on context and
semantics Conceptual modeling of different
knowledge domains
(Roadmap for Technology Enhanced Professional
Learning, 2007)
4
Existing Solutions

Learning metadata specifications and standards
IEEE LOM standard
IMS Learning Design specification
Problems with existing solutions
Prescriptive in nature
Metadata of limited quantity, complexity and
semantics
No room for metadata validation and revision
Ambiguous provenance of metadata
One-way (meta)data flow

5
Existing Solutions

Alternative solutions offered by the research
community
Ecological approach Pragmatic Web (G.
McCalla, USASK, Canada)
Use of concepts from controlled vocabularies,
taxonomies, and ontologies as metadata values
How to get closer to the users?

6
Our Solution

Changing the concept and the target users of
metadata
metadata derived from the actual usage of LOs
metadata aimed at computer programs that can make
sense of them for end users
An ontology based framework for capturing and
representation of contextualized semantic rich
metadata

7
Learning Object Context

Context awareness (meta)data
Learning activity a learning object (LO) was used
in
Prerequisites, learning objectives, available
time,
Domain topics/concepts covered,
LOs components of special interest,
Pedagogical role played by the LO,
Learners evaluations of the LO,
Learners characteristics
Aimed at capturing diverse kinds of learning
situations typical for modern e-Learning
environments

Learning Object Context
8
Learning Object Context Ontologies (LOCO)
Framework

Formalizes the notion of Learning Object Context
Integrates different kinds of learning related
ontologies
Flexible and easily extensible

9
The LOCO Framework

Aimed at facilitating
Reuse/repurposing of LOs and learning design
Context-aware retrieval of learning resources
Context aware recommendation of learning
content/activities/peer students

Won us The Best Paper Award at the 6th IEEE
Intl Conference on Advanced Learning
Technologies (ICALT2006)
10
Learner-centric scenarios
Providing learner with a custom view of the LOs
repository, compliant with the requirements of
the current learning context
11
Learner-centric scenarios
Leveraging context (meta)data of learners
on-line communication and collaboration
12
Teacher-centric scenarios

Provision of fine grained and semantically rich
feedback for educators, e.g., information about
domain topics difficult for learners
unusual performance of a learner or a group of
learners
The idea is to help educators
rethink the quality of
the learning content and
learning design of the online courses they teach
make more informed decisions regarding how to
improve their online courses

13
An Application Example TANGRAM

Ancient Chinese moving piece puzzle
An adaptive learning environment for the domain
of Intelligent Information Systems
Two basic functionalities
On-the-fly assembly of personalized learning
content out of existing content units
Quick access to a particular type of content
about a topic of interest
e.g. access to examples of RDF documents or
definitions of the Semantic Web.

14
An Application Example TANGRAM

TANGRAM leverages the LOCO framework
Decomposes LOs in accordance with a content
structure ontology
enables direct access to and reuse of content
units of diverse granularity levels
Annotates content units with concepts of an
ontology of instructional roles
Annotates content units with concepts of the
domain ontology
Keeps track of its users through the concepts and
properties of its user model ontology

15
An Application Example TANGRAM
16
An Application Example TANGRAM

Weaknesses to be addressed
Relies on a rudimentary form of learning design
ontology
Lacks support for active and collaborative
learning

To learn more about TANGRAM visit
http//iis.fon.bg.ac.yu/TANGRAM/home.html
17
An Application Example LOCO-Analyst

Aims at helping educators rethink the content and
design of their courses
Provides educators with feedback about
the learning activities of their students
the usage of the deployed learning content
the peculiarities of the interactions in the
online learning community.
Not tied to any specific e-Learning environment
feedback provision functionalities developed on
top of the LOCO framework

18
An Application Example LOCO-Analyst

Based on Semantic Web technologies
Ontologies enable
unambiguous representation and
integration of learning context data
abstraction of relevant concepts from the usage
tracking data
Semantic annotation facilitates establishing
semantic connections among learning artifacts
Simple rules are used for feedback generation

19
An Application Example LOCO-Analyst
20
An Application Example LOCO-Analyst

Evaluated as a useful tool for improving content
and design of online courses
Special appreciation for
Qualitative (over quantitative) feedback
Integrated view on the learning process as a
whole
Expressed an interest in using LOCO-Analyst in
ongoing course delivery

To learn more about LOCO-Analyst visit
http//iis.fon.bg.ac.yu/LOCO-Analyst/
Please, ask for a demo today ?.
21
LOCO-Analyst Current Work
Reducing the overhead in domain ontology
creation/evolution by leveraging students
collaborative tagging
22
Conclusion