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Personalization refers to a broad range of practices that involve making adjustments to learning activities and resources based on a number of parameters pertaining to individuals and groups of learners. The terms learning and instruction are both included to reflect the fact that some aspects of personalization occur in informal and unstructured environments not easily associated with instruction, which refers to those learning environments specifically designed and structured to support learning with regard to various goals and objectives. Related terms include differentiated learning and individualized instruction, although each of these has somewhat more specific meanings and usage. Differentiated learning and differentiated instruction refer to the practice of grouping students according to their ability levels and needs. The practice dates back to the days of one-room schoolhouses and relies on assessments to determine appropriate groupings. The basic notion was and is that learners could be grouped by their current abilities so that appropriate activities and resources for those learners could be used. Assuming that the groupings were appropriate and exhaustive, all learners could then receive appropriate support for learning.

Individualized learning and individualized instruction focus on specific individuals rather than groups. The basic notion is that each individual has specific needs and characteristics that should be accommodated in planning and implementing instruction. Formal individualized instruction has focused on learners with disabilities, with the requirement in many school systems in the United States to develop and follow individualized education plans (IEPs) for each student with a disability. IEPs were first required by the Education for All Handicapped Children Act of 1975, which was reauthorized in 1990 as the Individuals with Disabilities Education Act and reauthorized in 2004 as the Individuals with Disabilities Education Improvement Act. More informal individualized instruction involves one-to-one tutoring and at-home schooling, practices that are not necessarily associated with those with learning impediments.

The interest in personalized learning, broadly conceived to include differentiated and individualized learning and instruction, is based on the notion that instruction for larger groups is not as effective as one-to-one tutoring, as noted by Benjamin Bloom in a famous 1984 article. Many educators advocate personalized learning and instruction in some form, but there has been relatively little systematic and sustained progress on a large scale. In the 1990s, intelligent tutoring systems provided a technology-based response to Bloom’s challenge that was successful in highly restricted contexts, such as operating a device, writing programming code, and solving simple arithmetic problems. In general, these systems did not achieve the two-sigma improvement, or two standard deviations above those who only received conventional instruction, found by Bloom in one-to-one tutoring situations. But they often achieved significant improvements over non-individualized instruction. This entry first discusses the rationale for personalization and the dimensions of personalization. The entry then provides examples of personalized learning environments and discusses implications of personalization for learning and instruction.

Rationale for Personalization

The rationale for personalizing learning and instructional experiences is twofold, involving both effectiveness and efficiency. The notion of efficiency involves the resources needed to achieve a particular result. In the case of learning, the relevant resources involve learners as well as those supporting the learning (instructors, instructional systems, learning resources, learning spaces, and so on). For the people involved, a critical factor in efficiency studies is the time required. In the context of learning, one focus is clearly the learner’s time to achieve a desired outcome. For personalizing learning, the belief is that by identifying specific learner needs and requirements, the learner will be able to achieve a desired outcome in an optimally short time. By focusing on specific learner problems, a personalized learning system can address those problem areas and help the learner make progress efficiently. By identifying what a learner already knows and is able to do well, a personalized learning system can skip over learning activities that might bore the learner and not contribute to improved performance or understanding. Human tutors achieve these sorts of efficiencies by adjusting to individual learner needs and situations.

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