Intelligent Tutoring System - Design and Development Methods

Design and Development Methods

Apart from the discrepancy amongst ITS architectures each emphasizing different elements, the development of an ITS is much the same as any instructional design process. Corbett et al. (1997) summarized ITS design and development comprising of four iterative stages: (1) needs assessment, (2) cognitive task analysis, (3) initial tutor implementation and (4) evaluation.

The first stage known as needs assessment, is common to any instructional design process, especially software development. This involves a learner analysis, consultation with subject matter experts and/or the instructor(s). This first step is part of the development of the expert/knowledge and student domain. The goal is to specify learning goals and to outline a general plan for the curriculum; it is imperative not to computerize traditional concepts but develop a new curriculum structure by defining the task in general and understanding learners' possible behaviours dealing with the task and to a lesser degree the tutor’s behavior. In doing so, three crucial dimensions need to be dealt with: (1) the probability a student is able to solve problems; (2) the time it takes to reach this performance level and (3) the probability the student will actively use this knowledge in the future. Another important aspect that requires analysis is cost effectiveness of the interface. Moreover, teachers and student entry characteristics such as prior knowledge must be assessed since both groups are going to be system users.

The second stage, cognitive task analysis, is a detailed approach to expert systems programming with the goal of developing a valid computational model of the required problem solving knowledge. There are three chief methods for developing a domain model: (1) interviewing domain experts, (2) conducting “think aloud” protocol studies with domain experts and (3) conducting “think aloud” studies with novices. Although the first method is most commonly used, experts are usually incapable of reporting cognitive components, therefore the preferred method to obtain cognitive model evidence is the “think aloud” study in which the expert is asked to report aloud what s/he is thinking when solving typical problems.

The third stage, initial tutor implementation, involves setting up a problem solving environment to enable and support an authentic learning process. This stage is followed by a series of evaluation activities as the final stage which is again similar to any software development project.

The fourth stage, evaluation includes (1) pilot studies to confirm basic usability and educational impact; (2) formative evaluations of the system under development, including (3) parametric studies that examine the effectiveness of system features and finally, (4) summative evaluations of the final tutor’s effect: learning rate and asymptotic achievement levels.

Eight principles of ITS design and development

Anderson et al. (1987) outlined eight principles for intelligent tutor design and later elaborated on those principles highlighting an all-embracing principle which they believed governed intelligent tutor design, they referred to this principle as:

Principle 0: An intelligent tutor system should enable the student to work to the successful conclusion of problem solving.

1. Represent student competence as a production set.
2. Communicate the goal structure underlying the problem solving.
3. Provide instruction in the problem solving context.
4. Promote an abstract understanding of the problem-solving knowledge.
5. Minimize working memory load.
6. Provide immediate feedback on errors.
7. Adjust the grain size of instruction with learning.
8. Facilitate successive approximations to the target skill.