MET:Educational Benefits and Limitations
This page originally authored by Shelby Budd and Tracey Best (2007).
This page has been revised by Steffanie Reid (2008).
Educational Limitations of Intelligent Tutoring Systems
The examples of educational limitations listed are not inclusive to all limitations but are factors that are considered when taking into account the improvement of systems.
Subject Areas When building the models within the design of the ITS, subject areas such as mathematics, science and logic are more suited to an ITS model. The problem solving levels within the design can move through various levels of complexity. Subjects such as history, literature, geography and social sciences have more subjective answers, making the ITS design more complicated. New research will bring more range of subject areas to ITS as the system’s design expands and improves.
Pedagogical Constraints
The ITS is also limited in its pedagogical expertise. Unlike a human tutor, the pedagogical component for ITS needs enhanced capabilities. ITS needs further development to adopt a variety of pedagogy embedded in the system. ITS uses a single method of teaching and to date, cannot adapt it’s teaching according to the learners responses in the system.
Gaming the System
Another limitation to ITS is that students systematically use the "help" and "trial and error" property of the system to advance through various levels of problem solving. Students complete the tasks without actually engaging in critical thinking, otherwise described as "gaming the system." Models now exist to detect which students using ITS are gaming the system and in turn are showing lower academic grades. The long term goals of ITS are to not only assess knowledge and cognitive abilities but also behavioural characteristics that give a more detailed synopsis of the learner and to make more effective ITS environmnets (Baker, Corbett & Koedinger, n.d.).
New research is leading to a multi-level hint strategy, where students no longer immediately receive the answer to the question, but instead receive progressively bigger tips until they determine the correct course of action. It is hoped that this strategy will lead to improved student confidence in the material and less "gaming the system". (Anohina, 2007) (Added by Steffanie Reid (2008))
Educational Benefits of Intelligent Tutoring Systems
Tutoring Advantage
In a traditional educational setting, providing a tutor for each student may be ideal, but certainly is not plausible in terms of physical space and financial constraints. ITS can provide students with experiences similar to those provided by a tutor, but at a fraction of the cost. (edited by Steffanie Reid, 2008)
Variety of Uses
ITS are suitable in a variety of learning environments. The Navy has employed tutoring systems to provide tactical training and radar operational skills. ITS have also been successful for in flight simulations, army fire training, secondary mathematics and physics courses and in the health care profession for nurses' training. ITS are also being employed in "soft skill" situations to teach employees about selling, negotiating and working collaboratively (Ong & Ramachandran, 2000; Leddo & Kolodziej, 1997).
Cost Efficiency
The only cost involved in ITS concerns the purchase of the "hardware" and "software" required to operate the ITS. This is significantly less expensive than funding a traditional classroom, specifically an instructor's wages. The cost efficiency of this technology has led to its widespread use in many different classrooms and occupations. (edited by Steffanie Reid, 2008)
Effects on Learning
Aleksandar Davidovic (2001) found the following effects of learning in relation to using ITS:
Motivation
ITS students were motivated to complete assignments and showed greater satisfaction with learning than students who participated in regular classroom sessions.
Academic Improvement
Students who participated in learning with an ITS also showed an increase in marks. In one study, students showed a 43% higher final exam score in computer programming when using ITS, than their counterparts in a traditional learning environment (Ong & Ramachandran, 2000). In addition to improved marks, Ross and Casey (1994) found that students involved in ITS programs developed greater "problem solving capabilities" (p.722).
Learning Speed
Compared to their counterparts in a face to face setting, ITS students increased their cognition of concepts and moved through the assignments faster.
References
(section added by Steffanie Reid (2008)
Anohina, A, (2007). Advances in Intelligent Tutoring Systems: Problem-solving Modes and Model of Hints. International Journal of Computers, Communications & Control, v.II, No.1, pp. 48-55
Baker, R.S., Corbett, A.T. & Koedinger, K.R., Detecting Student Misuse of Intelligent Tutoring Systems. Retrieved February 15, 2007, from http://www.psychology.nottingham.ac.uk/staff/lpzrsb/BCK2004MLFinal.pdf
Davidovic, A. (2001). Learning benefits of structural example-based adaptive tutoring systems. Phd. University of South Australia, School of Computer and Information Science. Retrieved February 19, 2007, from http:\\www.ariic.libary.unsw.edu.au/unisa.
Leddo, J. & Kolodziej, J. (1997). Distributed interactive intelligent tutoring simulation. ERIC Document Access Code ED416319.
Ong, J. & Ramachandran, S. (2000). Intelligent tutoring systems: the what and the how. Retrieved February 14, 2007, from http://www.learningcircuits.org/2000/feb2000/ong.htm.
Ross, S. & Casey, J. (1994). Using interactive software to develop students' problem solving skills: evaluation of the "intelligent physics tutor." ERIC Document Access Code ED373754.