Traditional instructional methods often infuse “static knowledge” that learners can recall but may not apply correctly when needed. By contrast, Intelligent Tutoring Systems use simulations and other highly interactive learning environments that require people to apply their knowledge and skills.
Regardless of the fact that many instructional systems have been developed to support learning and training in the form of Computer-Aided Learning (CAL), Computer-Aided Instruction (CAI), Computer-Based Training (CBT) and Web-Based Training (WBT), the vast majority of such systems in the fields of education and industry, have failed to achieve the desired result.
This lack of success is due to the fact that traditional instructional methods, present instructional materials in a rigid tree structure to guide the learners from one content page to another depending on their answers. While they may be somewhat useful in helping learners, they are restrictive because they do not consider the diversity of students’ knowledge states and their particular needs. Such systems do not generate flexible instructional plans. Instead, they follow a pre-specified and fixed plan.
Moreover, they are not adaptive and are unable to dynamically provide the same kind of individualized attention that students would receive from human teachers. They fail to adapt to the specific way of acquiring knowledge a student has, and are unable to give the individualized attention that a human tutor provides.
A potential solution to this problem is the use of novel software known as “Intelligent Tutoring Systems” (ITS), with built-in artificial intelligence. These systems, which adapt themselves to the current knowledge stage of the learner and support different learning strategies on an individual basis, could be integrated with the Web for effective training and tutoring.
Intelligent tutoring systems (ITSs) are software programs that give support to the learning activity. These systems can be used in the conventional educational process, distant learning courses as well corporate training, either under the form of CDROMs or as applications that deliver knowledge over the Internet. They present new ways for education, which can change the role of the human tutor or teacher, and enhance it.
They present educational materials in a flexible and personalized way that is similar to one-to-one tutoring. In particular, ITSs have the ability to provide learners with tailored instructions and feedback. The basic underlying idea of ITSs is to realise that each student is unique.
They use simulations and other highly interactive learning environments that require people to apply their knowledge and skills. These active, situated learning environments help them retain and apply knowledge and skills more effectively in operational settings.
An intelligent tutoring system personalizes the instruction based on the background and the progress of each individual student. In this way, the learner is able to receive immediate feedback on his performance. Today, prototype and operational ITS systems provide practice-based instruction to support corporate training, high school and college education, military training etc.
The goal of intelligent tutoring systems is to provide the benefits of one-on-one instruction automatically and cost effectively. Intelligent tutoring systems enable participants to practice their skills by carrying out tasks within highly interactive learning environments.
An intelligent tutoring system (ITS), goes beyond training simulations by answering user questions and providing individualized guidance. Unlike other computer-based training technologies, intelligent tutoring systems assess each learner’s actions within these interactive environments and develop a model of their knowledge, skills, and expertise. Based on the learner model, ITSs tailor instructional strategies, in terms of both the content and style, and provide explanations, hints, examples, demonstrations, and practice problems as needed.
Research on prototype systems indicates that students and staff taught or trained by intelligent tutoring systems generally learn faster and translate the learning into improved performance better than classroom-trained participants.
Researchers in some universities developed an intelligent tutoring system called the LISP Tutor in the mid-1980s that taught computer programming skills to college students. In one controlled experiment, students who used this tutoring system scored 43 percent higher in the final exam, than a control group that received traditional instruction.
Learners taught using Sherlock an intelligent tutoring system performed significantly better than the control group and, after 20 hours of instruction, performed as well as technicians with four years of on-the-job experience.
Consequently, intelligent tutoring systems provide improved training outcomes when compared to classroom instruction. They provide training which is tailored and customized to the individual student, leading to effective learning. The knowledge incorporated into the ITS captures the expertise of best instructors and distributes it to all students and can serve as an effective tool to provide practice-based instruction to support corporate training, high school and college education, military training etc.