1. Web Services for Supporting
the Interactions of Learners in
the Social Web
Traian Rebedea Mihai Dascalu Vlad Posea Stefan Trausan-Matu
Faculty of Automatic Control and Computers
University Politehnica of Bucharest

2. Contents
• Context & Goals
• Scenario
• PolyCAFe
– NLP Pipe and Advanced Discourse Techniques
– Tagged LSA & Visualization
– Utterance Evaluation and Collaboration
– Participant Assessment and SNA
• Social Network Assistant
– Recommendation and Social Search Algorithms
• Web Services and Widgets
• Validation Results
2

3. Context
• Education through dialogue
• Technology – breaking space frontiers
• Computer Supported Collaborative Learning
- Chat & Forum -
• Communities of Practice (CoP)
• Social Web + Semantic perspective
3

4. Goals
• Find knowledgeable peers
• Automatically assess participants time
• Support learners interacting in
– Chats PolyCAFe
– Forums
– Social networking platforms Social Network Assistant
4

5. Scenario
Topic of interest
Social Network Assistant
Peer students
Engage in conversation
Chats & Forums
PolyCAFe
Automatic feedback and support
5

6. PolyCAFe architecture
Feedback & Grading
Collaboration Polyphony SNA
Advanced NLP and discourse analysis
Surface Domain
NLP Pipe WordNet LSA
Analysis Ontology
6

7. NLP Pipe & Advanced NLP and
discourse analysis
1 • Stop-words elimination
2 • Spelling Correction
3 • Stemming
4 • Tokenizer
5 • Part of Speech Tagging
• Speech acts identification
• Co-references
• Lexical chains derived from WordNet
7

8. Tagged LSA
• Corpus of chats
• Term-Doc Matrix + Tf – Idf
• POS Tagging + Stemming
• Segmentation k
i 1
word 1,i , word 2,i
Sim ( word 1 , word 2 )
– Participants
k k
i 1
word 12,i i 1
2
word 2,i
– Fixed Window
• Similarity
Vector(utterance
) (1 log(no _ occurence wordi )) * vector(wordi )
(
i 1
Sim(utterance , utterance )
1 2 Sim Vector(utterance ),Vector(utterance )
1 2
8

9. Vector space visualization
Radial Model
Physical Model
9

10. Utterance evaluation & Collaboration
• Degree
Social • Betweenness
• Semantic similarity
Qualitative • Predefined topics
• Discourse
• NLP Pipe
Quantitative • Occurrences
• Social cohesion
• Quantitative collaboration
• Gain based collaboration Qualitative approach
10

11. Participant assessment and Social
Networks Analysis
• Multiple perspectives • Social Networks -
– Quantitative metrics
– Qualitative – Degree
• Surface analysis – Centrality
– Readability • Closeness
• Flesch Reading Ease • Graph
• Gunning’s Fog • Eigen Value
• Flesch Grade Level – User Ranking
– Page’s Essay Grading • Google Page Ranking
• Fluency
• Spelling
• Diction
• Utterance structure
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12. Social Network Assistant Architecture
• RDF Semantic
Repository
12

13. Recommendation and Social Search
Algorithms
• Tag co-occurrence
• Tag-resource affinities Tag Clustering
• Tag-user affinities
• FolkRank
– Based on Google Page Rank
– Tri-partite graph
– Tag based attention profile
13

14. Web Services and Widgets
• REST WS + W3C standard
• Wookie widgets container
• Possibly embedded in Web 2.0 & learning apps
(Elgg, Moodle)
• XML manipulation
• Multiple functionalities & generated graphs
14

15. Validation Results
• PolyCAFe formal validation
– Student average (28/32 questions): 3,66 - 5,0
– Tutor average (35 questions): 3,5 - 5,0
• Social Network Assistant
– 90% score >= 4 usefulness
– 70% social search more trustworthy than standard
search
• Timesaving for manual assessment ≈ 30%
• Integration in formal learning context
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