Computers adapt the presentation of educational material according to students' learning needs, as indicated by their responses to questions, tasks and experiences.
Adaptive learning systems endeavor to transform the learner from passive receptor of information to collaborator in the educational process.
[4] Adaptive learning or intelligent tutoring has its origins in the artificial-intelligence movement and began gaining popularity in the 1970s.
Back in the 70's the main barrier was the cost and size of the computers, rendering the widespread application impractical.
Another hurdle in the adoption of early intelligent systems was that the user interfaces were not conducive to the learning process.
The simplest means of determining a student's skill level is the method employed in CAT (computerized adaptive testing).
A large pool of questions is amassed and rated according to difficulty, through expert analysis, experimentation, or a combination of the two.
Obviously, a certain margin for error has to be built in to allow for scenarios where the subject's answer is not indicative of their true skill level but simply coincidental.
A further extension of identifying weaknesses in terms of concepts is to program the student model to analyze incorrect answers.
Consider the following example: Clearly, a student who answers (b) is adding the exponents and failing to grasp the concept of like terms.
When the incorrect answers are being evaluated by the student model, some systems look to provide feedback to the actual questions in the form of 'hints'.
During the time a student spends learning a new concept they are tested on their abilities and databases track their progress using one of the models.
While these tools provide an adequate method for basic branching, they are often based on an underlying linear model whereby the learner is simply being redirected to a point somewhere along a predefined line.
These conditions may relate to what the learner is currently doing, prior decisions, behavioral tracking, interactive and external activities to name a few.
These higher end tools generally have no underlying navigation as they tend to utilize AI methods such as an inference engine.