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CfP: NLP in support of Learning - Workshop @ AIED 2009
CALL FOR PROPOSALS: Natural Language Processing in support of Learning -- Workshop @ AIED 2009. July 6 or 7, 2009, Brighton, UK, in conjunction with AIED 2009 Conference
Contact: nlpsl@upmf-grenoble.fr

1. IMPORTANT DATES
   Submission Deadline: April 16, 2009
   Notification of Acceptance: Mid-May 
   Camera-ready papers due date: End of May 
   NLPsL Workshop: A half-day on 6 or 7 July, 2009
   AIED Conference: July 8-10, 2009

2. AIMS (more information on the workshop website)
In AI-ED research, providing feedback for learning entails measuring differences among learners; between learners and their desired characteristics (e.g., knowledge, competences, motivation, self-regulation processes); or between learners and their looked-for resources (e.g. web-links, articles, courses) has often been performed by computing and analysing 'distances' using several techniques like factorial analysis, instance-based learning, clustering, and so on. Corpora on which these measures are made are all writing-based, that is, are multiple forms of pieces of evidence such as texts read (written by teachers), spoken utterances, essays, summaries, forum or chat messages. Some of these metrics are based on shallow syntactical and morphological aspects of the interaction and production artefacts (e.g., text length). Others are focused more on semantic and pragmatic aspects. These measures are used for providing various kinds of feedback for supporting learning and connections between learners. For instance, relations between learners' utterances, knowledge, concept acquisition, emotional states, essay scores, and even learners themselves have all been investigated with the help of computing semantic distances. 

The purpose of this workshop is to focus on the latter two – semantics and pragmatics – by trying to identify what questions and problems are solved, but also to raise and discuss how well the metrics developed assist in the provision of support and the construction of feedback for learning. What are the most efficient ones? To what extent do they match distances inferred by teachers' assessments? This workshop addresses the problem of how support can be provided and feedback be generated for helping students learn. 

Several Natural Language Processing techniques like Latent Semantic Analysis (LSA) or the use of semantic and pragmatic analysis of conversations have been successfully deployed in various educational applications to enrich learning and teaching with information technology. However, few research approaches considered also in detail the problem of providing feedback.

3. TOPICS
The topics of this workshop relate on the AI-ED applications of these techniques and the methodological issues they have raised (e.g., their selection and validation). Topics should cover the following distance-based semantic processing techniques in AI-ED research, but are not restricted to: 

Automated essay scoring & grading, Summarization & writing assistance, such as: 
    * Feedback generation, Tutoring & Tutor support, Question answering
    * Learner modelling, Enriching user profiles, Peer finding & community formation
    * Positioning & Placement of learners  
    * Selection & Sequencing of content
    * Protocol analysis, Knowledge gap analysis, Task analysis 

Methodological issues of distance-based semantic processing techniques, such as: 
    * Corpus composition & preparation (sanitising, filtering, selection, seeding, domain modelling, etc.) 
    * Optimisation of analysis and queries 
    * Statistical properties 
    * Combining these techniques with other ones 
    * Evaluation and Validation concerns 

Cognitive Modelling using distance-based semantic processing techniques, such as: 
    * Knowledge acquisition 
    * Language acquisition and development 
    * Measure of semantic relatedness 
    * Cognitive architectures 
    * Activity modelling 
    * Cognitive corpora 

Analysis, assessment and feedback generation of content and inter-animation in Computer-Supported Collaborative Learning through chats, such as: 
    * Content analysis of chat conversations 
    * Discourse analysis and visualization in chat conversations 
    * Identification of discussion and argumentation threads in conversations 
    * Identification of inter-animation, transactivity and interactions in chats 
    * Assessment of learners' participation in conversations 
    * Feedback generation for chats in educational settings

4. COMMITTEES
- Organisational Committee
This workshop is jointly organized and supported by members of the LTfLL (Language Technologies for LifeLong Learning) EC-funded Research Project 
    * Philippe Dessus (University of Grenoble, France)
    * Stefan Trausan-Matu (UPB, Roumania)
    * Peter van Rosmalen (OUNL, The Netherlands)
    * Fridolin Wild (Vienna University of Economics and Business Administration, Austria)

- Program Committee
    * Jean-Yves Antoine (University of Tours, France)
    * Gaston Burek (Tuebingen University, Germany)
    * Philippe Dessus (University of Grenoble, France)
    * Arthur C. Graesser (University of Memphis, USA)
    * Xiangen Hu (University of Memphis, USA)
    * Mathieu Lafourcade (University Montpellier, France)
    * Benoît Lemaire (University of Grenoble, France)
    * David Meyer (Vienna University of Economics and Business Administration, Austria)
    * Phil McCarthy (University of Memphis, USA)
    * Danielle S. McNamara (University of Memphis, USA)
    * Paola Monachesi (Utrecht University, The Netherlands)
    * Traian Rebedea (UPB, Roumania)
    * Stefan Trausan-Matu (UPB, Roumania)
    * Jan van Bruggen (OUNL, The Netherlands)
    * Peter van Rosmalen (OUNL, The Netherlands)
    * Fridolin Wild (Vienna University of Economics and Business Administration, Austria)
    * Virginie Zampa (University of Grenoble, France)

5. SUBMISSION TYPES (More information on the workshop website)
Submitted papers should describe substantial and unpublished work. English is the official language for both papers and talks. Submissions are expected to comply with the AIED paper format. The submitted papers should be 6-8 pages in length and in PDF format.
posted by Jérôme Zeiliger on 02/24/09 09:04:54
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