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September 18, 2019Smart Learning Environments420 citationsOpen Access

Personalized adaptive learning: an emerging pedagogical approach enabled by a smart learning environment

HPHongchao PengSMShanshan MaJSJ. Michael Spector

Key Points

  • This research aims to define and explore the concept of personalized adaptive learning in educational settings.
  • Analyzed two pillars of personalized adaptive learning: personalized learning and adaptive learning.
  • Constructed a framework for personalized adaptive learning based on four core elements: individual characteristics, performance, development, and adaptive adjustment.
  • Developed a recommendation model for personalized learning paths using smart technology.
  • Personalized adaptive learning applies real-time monitoring to tailor teaching strategies for individual learners.
  • Four key aspects enhance personalized learning: learner profiles, competency-based progression, personal learning, and flexible environments.
  • A generative paths recommendation model was established to create effective personal learning pathways.

Abstract

Abstract Smart devices and intelligent technologies are enabling a smart learning environment to effectively promote the development of personalized learning and adaptive learning, in line with the trend of accelerating the integration of both. In this regard, we introduce a new teaching method enabled by a smart learning environment, which is a form of personalized adaptive learning. In order to clearly explain this approach, we have deeply analyzed its two pillars: personalized learning and adaptive learning. The core elements of personalized adaptive learning and its core concept are explored as well. The elements are four: individual characteristics, individual performance, personal development, and adaptive adjustment. And the core concept is referred to a technology-empowered effective pedagogy which can adaptively adjust teaching strategies timely based on real-time monitoring (enabled by smart technology) learners’ differences and changes in individual characteristics, individual performance, and personal development. On this basis, A framework of personalized adaptive learning is also constructed. Besides, we further explored a recommendation model of the personalized learning path. To be specific, personalized adaptive learning could be constructed from the following four aspects, namely, learner profiles, competency-based progression, personal learning, and flexible learning environments. Last, we explored a form of learning profiles model and a generative paths recommendation pattern of personal learning. This paper provides a clear understanding of personalized adaptive learning and serves as an endeavor to contribute to future studies and practices.

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Cite This Study

Peng et al. (2019) studied this question.

synapsesocial.com/papers/69dcd22b2e182f147e133497https://doi.org/10.1186/s40561-019-0089-y
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