Advanced Tutoring Approach for e-Courses
Today, we live in a society characterized by multiple reference points and knowledge continuously subject to reviews and discussions. Teaching is called to train a new type of person, which is the manager of own space, time and identity.
In this theoretical framework, an LMS can support complex learning scenarios, but, in my perspective, the key to e-learning success is in the automation of some aspects of the design process, execution and assessment, and in the ability to provide an intelligent Tutoring function (Cognitive Tutoring), able to support the Teacher/Tutor in his actions, guide Students to complete their courses on the base of their existent knowledge, performance, course progress and learning style.
In particular, an intelligent tutoring action, including an intelligent, AI based behavior recording and knowledge detection, can manage multiple actors with different roles, that a Human Tutor may have difficulties to supervise.
Some references:
- Aleven, V., McLaren, B.M., Sewall, J., & Koedinger, K.R. (2009). A New Paradigm for Intelligent Tutoring Systems: Example-Tracing Tutors. International Journal of Artificial Intelligence in Education, 19(2), 105-154.
LINK: http://iaied.org/pub/1149/
- Pedrazzoli A., dall’Acqua L. (2010), “An Artificial Intelligence Multi-Agent based Adaptive Learning Environment using reusable learning objects“, 1st issue of Volume III, International Journal of Excellence in e-Learning, Dubai
LINK: http://journals.hbmeu.ae/Pages/Articles.aspx?AID=165&IID=36
- Brusilovsky, P. (2007) Adaptive navigation support. In: P. Brusilovsky, A. Kobsa and W. Neidl (eds.): The Adaptive Web: Methods and Strategies of Web Personalization. Lecture Notes in Computer Science, Vol. 4321, Berlin Heidelberg New York: Springer-Verlag, pp. 263-290.
LINK: http://www.sis.pitt.edu/~peterb/papers/8_Brusilovsky.pdf
