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.[1] 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. [2]
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.[3]
History[edit]
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.[4] 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".[5]
Implementations[edit]
Learning management system[edit]
Many learning management systems have incorporated various adaptive learning features. A learning management system (LMS) is a software application for the administration, documentation, tracking, reporting and delivery of educational courses, training programs, or learning and development programs. Adaptive learning systems have previously been used, for instance, to help students develop their argumentative writing performance (Argument Mining).[8]
Distance learning[edit]
Adaptive learning systems[9] can be implemented on the Internet for use in distance learning and group collaboration.[10]
The field of distance learning is now incorporating aspects of adaptive learning. Initial 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. 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 they are tested on their abilities and databases track their progress using one of the models. 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 cognitive path of assessment from lowest to highest based on the demonstrated cognitive abilities.[11]
A current successful implementation of adaptive learning in web-based distance learning is the Maple engine of WebLearn by RMIT university.[12] WebLearn is advanced enough that it can provide assessment of questions posed to students even if those questions have no unique answer like those in the Mathematics field.
Adaptive learning can be incorporated to facilitate group collaboration within distance learning environments like forums or resource sharing services.[13] Some examples of how adaptive learning can help with collaboration include automated grouping of users with the same interests, and personalization of links to information sources based on the user's stated interests or the user's surfing habits.