Adaptive learning is an educational method which uses computers as interactive teaching devices. Computers adapt the presentation of educational material according to students' learning needs, as indicated by their responses to questions and tasks. One of the aims of adaptive learning is to allow electronic education to incorporate the value of the interactivity afforded to a student by an actual human teacher or tutor. Adaptive learning has been partially driven by a realization that tailored learning cannot be achieved on a large-scale using traditional, non-adaptive approaches. Adaptive learning systems endeavor to transform the learner from passive receptor of information to collaborator in the educational process.
There are many ways in which adaptive learning can be used in and outside of the classroom. Intelligent Tutoring Systems (adaptive learning that is implemented in the classroom environment using information technology) operate on three basic principles designed to ease the integration of adaptive learning in a classroom environment:
- Systems need to be able to dynamically adapt to the skills and abilities of a student. Environments utilize cognitive modeling to provide feedback to the student while assessing student abilities and adapting the curriculum based upon past student performance. Inductive logic programming (ILP) is a way to bring together inductive learning and logic programming to an Adaptive Learning System. Systems using ILP are able to create hypotheses from examples demonstrated to it by the programmer or educator and then use those experiences to develop new knowledge to guide the student down paths to correct answers.
- Systems must have the ability to be flexible and allow for easy addition of new content. Since the cost of developing new Adaptive Learning Systems is often prohibitive to educational institutions, re-usability is essential. School districts have specific curriculum that the system needs to utilize to be effective for the district. Algorithms and cognitive models should be broad enough to teach mathematics, science, and language.
- Systems need to also adapt to the skill level of the educators. Many educators and domain experts are not skilled in programming or simply do not have enough time to demonstrate complex examples to the system: therefore, the system should be adaptable to the abilities of educators.
Adaptive learning systems can also be implemented on the Internet for use in distance learning and group collaboration applications. Initially, distance learning systems without adaptive learning were able to provide automated feedback to students who are presented questions from a preselected question bank. That approach, however, lacks the guidance which teachers in the classroom can provide. Therefore, current trends in distance learning call for the use of adaptive learning to implement intelligent dynamic behavior in the learning environment. During the time a student spends learning a new concept, he or she is tested on his or her abilities and databases track his or her progress against one of the models into which the system has been divided. The latest generation of distance learning systems take into account the students' answers and adapt themselves to the student's cognitive abilities using a concept called "cognitive scaffolding. " Cognitive scaffolding is the ability of an automated learning system to create a path of assessment from lowest to highest based on the demonstrated cognitive abilities.
Furthermore, adaptive learning can be incorporated to facilitate collaboration within distance learning environments like forums or resource sharing services. Some examples of how adaptive learning can help with collaboration include:
- Automated grouping of users with the same interests.
- Personalization of links to information sources based on the user's stated interests or the user's surfing habits.
Adaptive Learning
Adaptive learning uses computers as an integral part of educational development