Adaptive learning
Adaptive learning, also known as adaptive teaching, is an educational method which uses computer algorithms as well as artificial intelligence to orchestrate the interaction with the learner and deliver customized resources and learning activities to address the unique needs of each learner. In professional learning contexts, individuals may "test out" of some training to ensure they engage with novel instruction. Computers adapt the presentation of educational material according to students' learning needs, as indicated by their responses to questions, tasks and experiences. The technology encompasses aspects derived from various fields of study including computer science, AI, psychometrics, education, psychology, and brain science. Research conducted, particularly in educational settings within the United States, has demonstrated the efficacy of adaptive learning systems in promoting student learning. Among 37 recent studies that examined the effects of adaptive learning on learning outcomes, an overwhelming majority of 86% (32 studies) reported positive effects. 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. Adaptive learning systems' primary application is in education, but another popular application is business training. They have been designed as desktop computer applications, web applications, and are now being introduced into overall curricula. History Adaptive learning or intelligent tutoring has its origins in the artificial-intelligence movement and began gaining popularity in the 1970s. At that time, it was commonly accepted that computers would eventually achieve the human ability of adaptivity. In adaptive learning, the basic premise is that the tool or system will be able to adjust to the student/user's learning method, which results in a better and more effective learning experience for the user. 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 start of the work on adaptive and intelligent learning systems is usually traced back to the SCHOLAR system that offered adaptive learning for the topic of geography of South America. A number of other innovative systems appeared within five years. A good account of the early work on adaptive learning and intelligent tutoring systems can be found in the classic book "Intelligent Tutoring Systems". Technology and methodology Adaptive learning systems have traditionally been divided into separate components or 'models'. While different model groups have been presented, most systems include some or all of the following models (occasionally with different names): Expert model – The model with the information which is to be taught Student model – The model which tracks and learns about the student Instructional model – The model which actually conveys the information Instructional environment – The user interface for interacting with the system Expert model The expert model stores information about the material which is being taught. This can be as