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Adaptive Intelligent Learning Environments

  • Eelco HerderEmail author
  • Sergey Sosnovsky
  • Vania Dimitrova
Chapter

Abstract

Adaptive intelligent learning environments (AILE) seek to optimize the learning process for every individual learner. To this end, they create and maintain models of domain knowledge, instructional activities and the learners themselves. AILE is an active area of research that can be traced back to the 1970s. Over these years, a multitude of technologies and approaches have been proposed, implemented and empirically validated. A range of important pedagogical effects of AILEs have been documented in the literature—from increased speed of learning and better knowledge retention, to improvements in knowledge transfer and learner motivation. Two core research communities that drive further development of the field are Intelligent Tutoring Systems (ITS) and Adaptive Educational Hypermedia (AEH). This chapter outlines the evolution of AILEs over the years, describes their main principles and architectural components. Several classical systems exemplifying core AILE technologies are presented and emerging trends setting up the research agenda for the field are discussed at the end of the chapter.

Keywords

Learner Model Informal Learning Intelligent Tutor System Instructional Feedback Community Base Learning 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Eelco Herder
    • 1
    Email author
  • Sergey Sosnovsky
    • 2
  • Vania Dimitrova
    • 3
  1. 1.L3S Research CenterHannoverGermany
  2. 2.Department of Information and Computing SciencesUtrecht UniversityUtrechtThe Netherlands
  3. 3.School of ComputingUniversity of LeedsLeedsUK

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