Personalized adaptive learning: an emerging pedagogical approach enabled by a smart learning environment
By Hongchao Peng, Shanshan Ma, J. Spector. Smart Learning Environments, 2019
362 citations recorded by the source corpus.
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.
Subfields: Computer Science Applications, Information Systems
View Paper: https://www.semanticscholar.org/paper/2c81750bb589caf343bf8d96ac24a202cac0cdb5
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In Computer Science Applications
In Information Systems
Citations in the corpus
- A systematic literature review of personalized learning terms (2020, background): “For example, Chatti et al. (2010) and Peng, Ma and Spector (2019) are the ones who put the two most common terms used for personalized learning together and started to use “ personalized adaptive learning, ” which might be a good lead for future focus on what components are being used for each…”
- Learning design to support student-AI collaboration: perspectives of leading teachers for AI in education (2022, background): “These, in turn, provide more tailored and relevant learning opportunities and experiences that support students as they progress through the learning material (Peng et al., 2019; Cho et al., 2019).”
- Leading teachers' perspective on teacher-AI collaboration in education (2023, neutral): “…(i.e., detecting when students struggle with some tasks or concepts) to develop a student learning profile and teachers can use this data to suggest personalized learning methods to meet with the different needs and interest of students (Peng et al., 2019; Holstein et al., 2019a, b; UNESCO, 2019).”