A Learner Model for Learning-by-Example Context

• Published in: Eighth ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD 2007): 30 July - 01 August 2007 / Qingdao, China Vol. 3; pp. 778 - 785
• Main Authors: Yuan Fan Zhang, Capus, L., Tourigny, N.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01.07.2007
• Subjects: Artificial intelligence; Context modeling; Distributed computing; Intelligent networks; Intelligent systems; Learning; Navigation; Problem-solving; Software engineering
• ISBN: 9780769529097; 0769529097
• DOI: 10.1109/SNPD.2007.515

Nowadays learning environments put more and more accent on the intelligence of the system. The intelligence of a learning environment is largely attributed to its ability of adapting to a specific learner during the learning process. The adaptation depends on individual learner's knowledge of the subject to be learned, and other relevant characteristics of the learner. The knowledge and the relevant information about the learner are maintained in the learner model. A learner model can be defined as structured information about the learning process; and this structure contains some values of the learner's characteristics. This paper proposes a new learner model, which is based on the consideration of what is appropriate to the learning-by-example context. The model records five categories of information about the learner: personal data, learner's characteristics, learning state, learner's interactions with the system, and learner's knowledge. This model is being integrated in Sphinx, an educational environment based on learning by means of examples.