Transcript Diapozitiv 1

METOD – MetaTool
for Educational
Platform Design
Mateja Verlič
University of Maribor
Faculty of Electrical Engineering and Computer Science
Contents
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About project
METOD paradigm
Adaptive learning in METOD
Data collection
Supporting technologies
MetaTool
 Meta-information
 User
interface
About project
Leonardo da Vinci programme
 Motivation:
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 Lack
of adaptiveness of current Learning
management systems
 Static platforms
 Ease of knowledge transfer
 Lack of support for special groups of people
(elderly, vision and hearing impaired...)
METOD paradigm 1/2
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Enabling educators to:
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Educators:
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Develop computerized educational platforms
Supporting individual educational and training approaches
Experiment with various platforms and innovative educational
methods with ease
Supporting and accelerating creativity
Teachers
Non-professional educators (parents, family members)
Self-adaptation
METOD paradigm 2/2
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Long term aim: improve the skills and
competence of people by the integration of new
computer supported educational platforms
Paradigm is:
 Collection
of theoretical and practical findings
 Providing repository of:
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various training environments
description of trainees' characteristics
possible pedagogical goals
different pedagogical and communication strategies
Adaptive learning in METOD 1/
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Considering:
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Various styles of learning – learning through:
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Different student types and skill levels:
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seeing,
listening,
moving,
doing and
touching
Basic
Intermediate
Advanced
Different learning paths
Adaptive learning in METOD
 Preferred
learing styles
 Learning theories
 Learning and teaching methods, approaches,
processes
 Life-span learning
Data collection
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Direct feedback:
 Surveys
 Questionnaires
 Polls
 Grades
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Indirect feedback
 Observing
use of LMS resources
 Observing use of tools
Supporting technologies
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Analysis and evaluation of collected data
User classification and student types
Prediction of user’s behavior
Suggested learning path
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Predefined paths
Effective path by other users
Suggested links of alternative learning styles and levels
Intelligent behavior
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Data-mining
Machine learning - Multimetod approach
MetaTool
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Meta-tool = Tool of tools
Output of MetaTool = input to LMS
Customizable multi-user type support
Input of MetaTool:
 Topics
 Materials
 Meta-information
 Collected
data from LMS
MetaTool meta-information
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Why meta?
 Information
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about using materials
Not part of the material
 User
types
 Learning styles
 Suggested learning path
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Teacher defined
Machine generated
Possibility of peer review
MetaTool user interface
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Basic user interface:
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Parents
Other family members
Learners
Wizard-based creation of
courses
Advanced user interface:
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Skilled professional
teachers
User interface
Defining topics
Assigning materials to topics
Output of MetaTool
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SCORM package
 Standard
for exchange of e-learning units between
LMSs
 Compatibility support
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Only static structure
 Additional integration of meta-information
 Enabling dynamic content
 Add-on module for LMS needed
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Static web pages
Moodle package
Add-on for LMS
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Data collection module
Machine learning module
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On-line machine learning
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Off-line machine learning
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Statistics
Minor adjustment of the learning path
Better analysis
More processing resources available
Can be peer reviewed
Inference module
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Application of extracted knowledge
Advantages of METOD
Adaptiveness on different levels
 Integration of learning theories and
intelligent systems
 Accessibility
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 Support
for people with special needs
Support for life-long learning
 MetaTool - not limited to single LMS
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Disadvantages of METOD
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Adaptiveness
 User
does not get the same learning path
every time
Can be confusing for adult users
 Can be overridden (predefined static view of the
content)
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LMS module needed for intelligent support
 Additional effort for teacher
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Current status of METOD
Currently in active development phase
 First user-feedbacks
 Expected deployment at the end of the
year
 Not yet publicly available
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Summary
Advantages > disadvanatges
 Why?
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 Less
effort needed for learner
 Alternative materials and learning paths
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More interresting?
 Improving
the quality of learning process
 Next logical step in LMS development
Thank you!
Questions?