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£176.73

Information Science Reference Personalization and Collaboration in Adaptive E-Learning

Name: Personalization and Collaboration in Adaptive E-Learning
Brand: Information Science Reference
Price: 176.73 GBP
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Computing & Internet

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Description

As part of e-learning, adaptive systems are more specialized and focus on the adaptation of learning content and presentation of this content. An adaptive system focuses on how knowledge is learned and pays attention to the activities, cognitive structures, and context of the learning material. The adaptive term refers to the automatic adaptation of the system to the learner. The needs of the learner are borne by the system itself. The learner did not ask to change the parameters of the system to his own needs; it is rather the needs of the learner that will be supposed by the system. The system adapts according to this necessity. Personalization and Collaboration in Adaptive E-Learning is an essential reference book that aims to describe the specific steps in designing a scenario for a collaborative learning activity in the particular context of personalization in adaptive systems and the key decisions that need to be made by the teacher-learner. By applying theoretical and practical aspects of personalization in adaptive systems and applications within education, this collection features coverage on a broad range of topics that include adaptive teaching, personalized learning, and instructional design. This book is ideally designed for instructional designers, curriculum developers, educational software developers, IT specialists, educational administrators, professionals, professors, researchers, and students seeking current research on comparative studies and the pedagogical issues of personalized and collaborative learning.

Product Specifications

Brand: Information Science Reference
Format: Hardcover
ASIN: 1799814920
Category: Books > Subjects > Computing & Internet
Domain: Amazon UK
Release Date: 13 December 2019
Listed Since: 30 September 2019

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Information Science Reference Personalization and Collaboration in Adaptive E-Learning

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