Towards a Semantic Modeling of Learners for Social Networks

1
Towards a Semantic Modeling of Learners for
Social Networks

• Asma Ounnas, ILaria Liccardi, Hugh Davis, David
  Millard, and Su White
• Learning Technology Group
• University of Southampton, UK
• Presented by Rosta Farzan
• Personalized Adaptive Web Systems Lab

2
Introduction

• Social networks is important in distant learning
• Physically different location and different life
• Need friends who share same interests,
  preferences, and learning experiences
• Learner model
• Building social networks of learners
• This work
• An extension of Friend of a Friend (FOAF)
  ontology to build learner model for social
  networks

3
Outline

• Existing learner models
• Learners feature taxonomy
• Comparison of the learners model
• Extension of FOAF as a learner model
• Conclusion Future Work

4
PAPI

• IEE LTSC
• Data interchange specification
• Describes learner information for communication
  among cooperating systems
• Personal information
• General information e.g. name, address,
• 6 Categories
• Relations information
• Learners relationships with others e.g.
  classmate
• Security information
• Access rights
• Preference information
• Public information about the learners
  preferences e.g. learning style, language,
• Performance information
• Records of learners measure performance e.g.
  grades
• Portfolio information
• Learners projects and works

5
IMS LIP

• Similar to learner's CV
• Focus on Learners history and learning
  experience
• Lifelong model
• Transfer between institution
• 11 categories
• Identification name, e-mail,
• Goal Learning, Career,
• Qualification, Certification, License
• From recognized authorities
• Activity learning activities in any state of
  completion
• Interest hobbies and recreational
• Relationship between core data elements
• Competency skills and experiences
• Accessibility language capabilities, learning
  preferences, disabilities
• Transcript official academic achievements
• Affiliation organization
• Security Key password

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eduPerson

• By Internet2 and Educause
• Facilitate communication between higher education
  institution
• Similar to employee information system
• Detailed description
• 43 elements in 2 categories
• General attributes
• Information about the learner, the organization,
  and references
• New attributes
• To facilitate collaboration between the
  institution
• E.g. Affiliation, ID for authentication,

7
Dolog LP

• By Dolog et al
• Uses RDF and learners ontologies
• For personalization services
• 5 categories
• Identification
• Name, telephone, address, email,
• Other user features
• Preferences, Goal, and Interests
• Study performance
• Performance, portfolio, and certification
• Human resource planning
• Organization
• Calendar
• Appointments and events

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FOAF

• RDF vocabulary
• Properties and classes to describe
• People, documents, and organizations
• For building communities and social groupings
• 5 categories
• Basic information
• Name, email, images, homepage
• Personal information
• Weblogs, interests, publications
• Online accounts
• Projects and groups
• Projects, organizations
• Documents and images
• E.g. personal profile document, logo

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Learners Features Taxonomy
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Comparison of the Learner Models
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Comparison of the Learner Models

• PAPI, LMS LIP, and Dolog PL
• Best for adaptive e-learning
• eduPerson
• Collecting data and transferring between
  institution
• FOAF
• Automatic personalization
• Describes learners relations with others by
  pointing to learner knows

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Comparison of the Learner Models
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Extending FOAF

• Advantages of FOAF
• RDF
• 1.5 millions FOAF documents
• FOAF vocabularies evolves
• FOAF files are easy to create
• Facilitates locating people with similar interest
• Security and privacy issues are taken care

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Extending FOAF

• Required feature for using FOAF as a learner
  model
• Personal Data
• Spoken and written language, gender, learning
  styles, preferred modules
• Relations
• Taking courses, taking module,
• Evaluating strength of the relationships between
  learners
• Algorithm for building social networks of learners