scholarly journals IMPROVING ADAPTIVE LEARNING IN A SMART LEARNING ENVIRONMENT

2021 ◽  
Vol 2 ◽  
pp. 93-99
Author(s):  
Gilberto Marzano ◽  
Anda Abuze ◽  
Yeliz Nur
Keyword(s):  
Learning Environment ◽  
Adaptive Learning ◽  
Low Cost ◽  
Educational Interventions ◽  
Digital Learning ◽  
Smart Learning Environment ◽  
Smart Learning ◽  
Unit Structure ◽  
Teaching Learning ◽  
Near Future

It has been broadly argued that, in the near future, the demand for skilled labor will increase whilst that for routine activities will decrease. In this regard, the need for making greater investments in education to re-skill workers and support continuous learning has been invoked as an essential requirement for preserving people’s employability.Digital technology is deemed increasingly necessary to sustain the educational endeavor, for the possibilities it offers to make more accessible and low-cost educational interventions. It allows for the creation of personalized learning paths and customized digital learning solutions, for courses to be available to a large attendance of learners, and for teaching-learning activities to be offered at significantly reduced cost.In this article, a learning unit structure designed to improve adaptive learning is proposed, and mechanisms for adaptive learning in a smart learning environment are discussed.The implemented teaching-learning solution is also illustrated. This is a preliminary application based on an approach that combines the teacher experience with learning analytics. 

scholarly journals Innovative Shift in Smart Learning Environment

2020 ◽  
pp. 36-44
Author(s):  
Hadya S. Hawedi ◽  
Abdulghader Abu Reemah A. Abdullah
Keyword(s):  
Learning Environment ◽  
Information And Communication Technologies ◽  
Learning Outcome ◽  
Learning System ◽  
Organizational Setting ◽  
Smart Learning Environment ◽  
Smart Learning ◽  
Learning Platform ◽  
Search Tool ◽  
Teaching Learning

Innovations in smart learning represent a domain of knowledge transfer platform to boost the effectiveness of the educational practices and learning outcome. The uniqueness of this form of electronic-assisted has been widely accepted as it provides its users with a powerful multi-search tool to access learning content that meet their intended needs. The transformative changes in the learning platform provide a flexible teaching/learning online outlet that has increasingly been adopted to improve learning outcome. In this study, the effectiveness of innovation in information and communication technologies (ICT) as a platform to rapidly transformed learning environment is discussed. Potential of smart learning environment is discussed and relevance of its flexibility in the learning environment and adaptable features for training workers in an organizational setting. This review extensively highlights the position of smart learning system in improving conventional learning and organizational practices that are limited in scope and their functioning environment.

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

2019 ◽  
Vol 6 (1) ◽  
Author(s):  
Hongchao Peng ◽  
Shanshan Ma ◽  
Jonathan Michael Spector
Keyword(s):  
Learning Environment ◽  
Adaptive Learning ◽  
Personal Development ◽  
Personalized Learning ◽  
Individual Performance ◽  
Individual Characteristics ◽  
Core Concept ◽  
Smart Learning Environment ◽  
Personal Learning ◽  
Smart Learning

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.

scholarly journals Teaching System of Smart Learning Environment for Aerobics Course

2018 ◽  
Vol 13 (05) ◽  
pp. 165 ◽  
Author(s):  
Yanan Yu ◽  
Aili Qi
Keyword(s):  
Learning Environment ◽  
University Education ◽  
Independent Learning ◽  
Fuzzy Cognitive Map ◽  
Digital Learning ◽  
Smart Learning Environment ◽  
Teaching System ◽  
Smart Learning ◽  
University Course ◽  
The University

In the past digital learning environment, we required the multimedia facilities excessively and ignored the individual needs of learners, and the teaching resources existed depending on the equipment. The emergence of smart learning environment can meet people's independent learning, customized learning, smart learning and other requirements. Meanwhile, the “intelligence" of smart learning environment conforms to the teaching features of aerobics and other body-shaping courses, which can cultivate the learners’ innovation abilities and further optimize the teaching effect. In this paper, on the basis of the theory construction of smart learning environment, we designed a teaching system of smart learning environment for the university course Aerobics based on the Fuzzy Cognitive Map (FCM), conducted the application practice of the smart learning environment in the teaching of the university course Aerobics by the controlled experiment method, analyzed the difference of teaching effect in and out of a smart learning environment, and finally drew a conclusion, in order to provide some theoretical and data support for the application of smart learning environment in the teaching of physical education (PE) majors and other university education.

scholarly journals Activity Monitoring in the Digital Learning Environment of a Modern University: Technological Tasks of Psychological Support

2021 ◽  
Vol 23 (1) ◽  
pp. 156-165
Author(s):  
E. V. Bredun ◽  
Т. A. Vaulina ◽  
V. A. Shamakov ◽  
E. A. Shcheglova
Keyword(s):  
Learning Environment ◽  
Activity Monitoring ◽  
Psychological Support ◽  
Digital Learning ◽  
Smart Learning Environment ◽  
Research Results ◽  
Digital Learning Environment ◽  
Smart Learning ◽  
Distant Learning ◽  
Digital Footprints

The paper reviews the existing approaches to using digital footprints in the digital learning environment. Monitoring digital footprints of university students can help to design smart learning environment and predict models of interaction between this environment and the user. The article covers the main analysis tools that can be applied to activity monitoring in LMS Moodle, including datasets as a convenient resource for distant learning. The authors studied authentication techniques that are based not on one’s knowledge but on the confirmation of one’s digital profile. The research results revealed some personal styles and patterns of cognitive behavior that reflect students’ work in the digital learning environment. The research results can be used to develop new psychological support of activity monitoring of the digital university environment, as well as to create new effective cognitive user-friendly interfaces.

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