The document discusses a hybrid learning scenario used at Bucharest "Politehnica" University that combines classroom lectures, individual study, and computer-supported collaborative learning (CSCL) using online chat sessions. It presents the VMT chat environment and XML encoding used to analyze the chats. The theoretical model is based on Bakhtin's dialogism and views learning as polyphonic with interanimated voices. The PolyCAFe system was developed to analyze chats for collaboration and automatically generate feedback using natural language processing and social network analysis. It identifies important utterances and determines how well participants collaborate. The system aims to help understand knowledge building in chats and provide support for hybrid learning environments.

1. Stefan Trausan-Matu
Universitatea “Politehnica” Bucuresti,
Institutul de Cercetari în Inteligenta Artificiala al
Academiei Române

2. Outlook
The Hybrid Learning Scenario
The Polyphonic Model of Discourse
The PolyCAFe Analysis System
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3. The Hybrid Learning Scenario
Classroom lectures
Individual study of learning materials
Computer-Supported Collaborative Learning (CSCL)
in small groups using online instant messenger chats
(Stahl 2006)
Un-moderated (due to the large number of students)
For discussing topics assigned by tutors in relation to
the lectures.
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4. The Scenario has been used for
More than 800 Computer Science students at
Bucharest “Politehnica” University, Romania since
2005, at the courses:
Human-Computer Interaction (undergraduate) debate
and design
Algorithm Design (undergraduate) problem solving
Natural Language Processing (master) debate and
design
Collaborative and Adaptive Systems (master) design a
presentation
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5. The VMT (Stahl 2009) chat environment
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6. The VMT Referencing facility
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7. The XML Encoding
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8. Example of a CSCL Assignment
Students had to debate in chat sessions in groups
ranging from 3 to 8
In the first part of the conversation, each student had
to defend a technology by presenting its features and
advantages and criticize the others by invoking their
flaws and drawbacks
In the final part of the chat, they had to discuss on
how they could integrate all these technologies in a
single online collaboration platform
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9. Tutors reported that the analysis:
is extremely time consuming, it takes about twice
the actual duration of the online chat
They needed to walkthrough more than once the
conversations in order to evaluate it
It proved to be very difficult to follow the threading
of discussions – there were very long chains and it
was very hard to remember what said each student,
and to asses their contributions
It was very difficult to identify important
utterances/contributions because only afterwards
this judgment may be done, after seeing the effect of
these utterances on the subsequent ones.
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10. Our Theoretical Model is based
on Mikhail Bakhtin’s
Dialogism - basis for the CSCL paradigm
(Koschman, 1999) “… Any true understanding is
dialogic in nature” (Voloshinov-Bakhtin, 1973)
Polyphony and Inter-animation of voices
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11. The polyphonic analysis
of CSCL chats
May be used for understanding the mechanisms of
knowledge building in collaborative chats
(Trausan-Matu, 2006), in particular and in hybrid
learning, in general
Is a problem similar to that of an inexperienced
listener who does not comprehend a lot when
hearing a complex classical music piece, for
example, a fugue written by Johann Sebastian
Bach.
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12. Confucius
“was a devotee of music and noted a close kinship
between humaneness (jen) and music presumably
because the former, like the latter, aims at the harmony
of relationships”
“it is impossible to understand man without
understanding the power of words (language)” (Hwa
Yol Jung, 1993)
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14. Polyphony
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15. LTfLL - EU FP7 Project
(2008-2011)
Language Technologies for Lifelong Learning
Netherlands, France, United Kingdom, Germany, Ausria,
Romania, Bulgaria
The PolyCAFe system (Polyphony-based Collaboration
Analysis and Feedback generation)
The system has just been validated with students and tutors
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16. The Architecture of PolyCAFe
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17. NLP pipe
spelling correction, stemmer, tokenizer, Named Entity
Recognizer, POS tagger and parser, and NP-chunker.
Stanford NLP software (http://nlp.stanford.edu/software)
Spellchecker : Jazzy
http://www.ibm.com/developerworks/java/library/j-jazzy/
Alternative NLP pipes are under development,
GATE (http://gate.ac.uk)
LingPipe (http://aliasi.com/lingpipe/).
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18. Social network analysis
Consider explicit and implicit referencing as arcs
between participants, which are the nodes
A kind of page-rank algorithm – an utterance is
important if it is referred by important utterances; The
strength of a voice (of an utterance) depends on the
strength of the utterances that refer to it
Determines if a person is central/peripheral
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19. Polyphony, Inter-animation and
Collaboration analysis
Assign an importance value for each utterance
considering several indicators of inter-animation
(collaboration)
Detection of chains of inter-animation patterns
(Trausan-Matu, 2007) in the chat
Consider several criteria such as the presence in the chat
of questions, agreement, disagreement
Presence of others’ voices
Social Networks metrics
Machine learning approach (genetic algorithms and
neural networks) for tuning the
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25. Conclusions
PolyCAfe was validated under the LTfLL project
(Rebedea and all, 2010)
The system will be freely available on the web
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26. Conclusions (cont.)
Polyphony and inter-animation provide a basis for an
unifying theoretical background for different types of
learning: face-to-face, to a distance, using electronic
means, and even individually. In each of these types
several voices should be present (actually, virtually or
as an echo in Bakhtin’s sense)
Polyphony and inter-animation of the voices of the
professor, of the learner, of the authors of read
documents, of chat colleagues …
Confucius Harmony?
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27. Thank You!
Questions?
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