"Towards Collaborative and Intelligent Learning Environments Based on E" by Yuehua Wang, Shulan Lu et al.
 

Author(s)/Creator(s)

Yuehua Wang
Shulan Lu
Derek Harter

Publication Title

IEEE Access

Document Type

Article

Abstract/Description

The current pandemic has significantly impacted educational practices, modifying many aspects of how and when we learn. In particular, remote learning and the use of digital platforms have greatly increased in importance. Online teaching and e-learning provide many benefits for information retention and schedule flexibility in our on-demand world while breaking down barriers caused by geographic location, physical facilities, transportation issues, or physical impediments. However, educators and researchers have noticed that students face a learning and performance decline as a result of this sudden shift to online teaching and e-learning from classrooms around the world. In this paper, we focus on reviewing eye-tracking techniques and systems, data collection and management methods, datasets, and multi-modal learning data analytics for promoting pervasive and proactive learning in educational environments. We then describe and discuss the crucial challenges and open issues of current learning environments and data learning methods. The review and discussion show the potential of transforming traditional ways of teaching and learning in the classroom, and the feasibility of adaptively driving learning processes using eye-tracking, data science, multimodal learning analytics, and artificial intelligence. These findings call for further attention and research on collaborative and intelligent learning systems, plug-and-play devices and software modules, data science, and learning analytics methods for promoting the evolution of face-to-face learning and e-learning environments and enhancing student collaboration, engagement, and success.

Department

Psychology and Special Education

Department

Computer Science and Information Systems

First Page

137991

Last Page

138002

DOI

10.1109/ACCESS.2021.3117780

Volume

9

ISSN

2169-3536

Date

10-14-2021

Plum Print visual indicator of research metrics
PlumX Metrics
  • Citations
    • Citation Indexes: 13
  • Usage
    • Downloads: 7
  • Captures
    • Readers: 167
see details

Share

COinS
 
 

To view the content in your browser, please download Adobe Reader or, alternately,
you may Download the file to your hard drive.

NOTE: The latest versions of Adobe Reader do not support viewing PDF files within Firefox on Mac OS and if you are using a modern (Intel) Mac, there is no official plugin for viewing PDF files within the browser window.