Adaptable and Reusable Query Patterns for Trace-Based Learner Modelling

This paper defines a framework to describe Learner Modelling (LM) process based on interactions traces. This framework includes an RDF-Based representation of knowledge models that can be used by a LM designer. The first model enables the LM designer to describe observations about learner's interactions with a TEL-system. The second model enables the LM designer to describe the structure of learner's profile. This framework supports also the description of reusable and adaptable SPARQL-based query patterns. These patterns enable the LM designer to calculate and infer learner profile elements for different TEL systems. We define the notion of query pattern and illustrate its application in the context of two TEL systems.

[1]  Pierre Dillenbourg,et al.  A Framework for Learner Modelling , 1992, Interact. Learn. Environ..

[2]  Jean-Marc Labat,et al.  Indicators for Deducting the Learners' Learning Styles: Case of the Navigation Typology Indicator , 2009, 2009 Ninth IEEE International Conference on Advanced Learning Technologies.

[3]  Peter Dolog,et al.  Integrating Adaptive Hypermedia Techniques and Open RDF-based Environments , 2003, WWW.

[4]  Alain Mille,et al.  Analyzing Behaviorial Data for Refining Cognitive Models of Operator , 2006, 17th International Workshop on Database and Expert Systems Applications (DEXA'06).

[5]  Alain Mille,et al.  A Trace-Based Learner Modelling Framework for Technology-Enhanced Learning Systems , 2010, 2010 10th IEEE International Conference on Advanced Learning Technologies.

[6]  Yannick Prié,et al.  A Trace-Based System for Technology-Enhanced Learning Systems Personalisation , 2009, 2009 Ninth IEEE International Conference on Advanced Learning Technologies.

[7]  Jack Mostow,et al.  Why, What, and How to Log? Lessons from LISTEN , 2009, EDM.

[8]  Raymund Sison,et al.  Student Modeling and Machine Learning , 1998 .

[9]  Jim E. Greer,et al.  Towards Best Practices for Semantic Web Student Modelling , 2005, AIED.

[10]  Nadine Mandran,et al.  Experimentation and Results for Calibrating Automatic Diagnosis Belief Linked to Problem Solving Modalities: A Case Study in Electricity , 2010, EC-TEL.

[11]  Stéphanie Jean-Daubias,et al.  AMBRE-add: An ITS to Teach Solving Arithmetic Word Problems , 2008 .

[12]  Elvira Popescu Learning Styles and Behavioral Differences in Web-Based Learning Settings , 2009, 2009 Ninth IEEE International Conference on Advanced Learning Technologies.

[13]  Ryan Shaun Joazeiro de Baker,et al.  Adapting to When Students Game an Intelligent Tutoring System , 2006, Intelligent Tutoring Systems.

[14]  Cédric d'Ham,et al.  Scaffolding the students' activity of experimental design with a dedicated software: copex-chimie , 2009 .