Inproceedings,
OPUS One An Artificial Intelligence - Multi Agent based Intelligent Adaptive Learning Environment (IALE)
Learning in the Synergy of Multiple Disciplines, Proceedings of the EC-TEL 2009, volume 5794 of Lecture Notes in Computer Science, Berlin/Heidelberg, Springer, (October 2009)
Abstract
This paper proposes a concept for an Intelligent Adaptive Learning Environment (IALE) based on a holistic Multidimensional Instructional Design Model, applied on OLAT, an open source, Java LMS, developed at the University of Zurich, to support student and/or groups defined as "Learning Entities" (LE). Based primarily on an Artificial Intelligence - Tutoring Subsystem, used to identify, monitor and adapt the student's learning path, considering the students actual knowledge, learning habits and preferred learning style. The proposed concept has the peculiarity of eliminating any didactical boundaries or rigid, implied course structures (also known as unlimited didactical freedom). Relying on "real time" adapted profiles, it allows content authors to apply a dynamic course design, supporting tutored, collaborative sessions and activities, as suggested by modern pedagogy. The AI tutoring facility (eTutor), coupled with the LMS, is intended to support the "human tutor" with valuable LE performance - / activity data, available from the integrated "Behavior Recorder Controller" (BRC), allowing to confirm or manually modify actions suggested by the eTutor. The student has the option to select the level of tutoring interventions or switch to a "subject matter" exercise mode if he feels, and is allowed to do so. The concept presented combines a personalized level of surveillance, learning activity- and/or learning path adaptation suggestions to ensure the students learning motivation and learning success.
