Intelligent tutoring system
Draft 1
Editor: Nicolas Balacheff, Laboratoire d’informatique de Grenoble
Contributors: Jacqueline Bourdeau, Télé-université, Montréal (Québec); Monique Grandbastien, LORIA, université Henri Poincaré Nancy1
Contents
Definition
An Intelligent tutoring system (ITS) is a computer-based instructional systems with models of instructional content that specify what to teach, and teaching strategies that specify how to teach.
Comments on the history
The term “intelligent tutoring systems” was coined by David Sleeman and John Seely Brown acknowledging the evolution of the previously called Computer Assisted Instruction (CAI) into Intelligent Computer Assisted Instruction (ICAI), an expression that ITS replaced then (Sleeman and Brown 1982 p.1).
Related terms
Computer Assisted Instruction (CAI), Intelligent Computer Assisted Instruction (ICAI), generative CAI, student model, learner model, knowledge model
Translation issues
French: tuteur intelligent ; however, the best translation of “tutor” would have been “précepteur”, the word “tuteur” has in French a connotation close to authoritative instruction.
Disciplinary issues
ITS represents an important milestone in the structuration of research on AI and learning, which initially ambitioned covering all types of computer-supported teaching and learning. “ ITS has clearly abandoned on the CAI’s early objective, namely that of providing total courses, and has concentrated on building systems which provide supportive environments for limited topics” (Sleeman and Brown 1982, p.8). A characteristic of ITS research is the emphasis on individualization and the requirement for the system to have its own problem solving expertise, both and their interaction requiring specific tutoring knowledge: “Computer-assisted instruction evolves toward intelligent tutoring systems (ITSs) by passing three tests on intelligence. First, the subject matter, or domain, must be “known” to the computer system well enough for this embedded expert to draw inferences or solve problems in the domain. Second, the system must be able to deduce learners’ approximation of that knowledge. Third the tutorial strategy or pedagogy must be intelligent in that the “instructor in the box” can implement strategies to reduce the difference between expert and student performance.” (Burns and Capps, p.1). This is translated into the classical three modules architecture of ITSs: the domain model, the tutor model and the learner model. Following John Self (1999, p.350), basic architecture of ITSs was already established in the mid-seventies. However, “beside this classic component view of ITSs, these systems offer a number of services. The implementation of some of these services usually transcends the individual components” (Nkambou et al. 2010, p.5).
Key references
Burns and Capps (1988) Foundation of intelligent tutoring systems: an introduction. In: Polson M. C., Richardson J. J. (eds.) Intelligent tutoring systems (pp.1-19).Hillsdale, NJ: Laurence Erlbaum.
Nkambou R., Bourdeau J., Mizoguchi R. (eds.) (2010) Advances in Intelligent tutoring systems. Springer verlag.
Self J. (1999) The defining characteristics of intelligent tutoring systems research: ITSs care, precisely. International Journal of Artificial Intelligence in Education, 10, 350-364
Sleeman D., Brown J. S. (eds) (1982) Intelligent tutoring systems. London: Academic Press.
