arrow
返回

AI-Based Personalized E-Learning Systems: Issues, Challenges, and Solutions

delete2022-01-01
delete50
delete
OA
AI
M
Mir Murtaza *
Y
Yamna Ahmed
J
Jawwad Ahmed Shamsi
F
Fahad Sherwani
M
Mariam Usman
DOI:10.1109/ACCESS.2022.3193938delete
delete原文链接
delete原文求助
delete分享
delete收藏
摘要

摘要

En 中文
A personalized e-learning system is effective in imparting enhanced learning to its users. As compared to a conventional e-learning system, which provides similar contents to each learner, a personalized learning system provides specific learning contents and assessments to the learners. Personalization is based on Artificial Intelligence (AI) based techniques in which appropriate contents for each learner are determined using the level of comprehension of the learner and the preferred modes of learning. This paper presents requirements and challenges for a personalized e-learning system. The paper is focused in elaborating four research questions, which are related to identifying key factors of personalized education, elaborating on state of the art research in the domain, utilizing benefits of AI in personalized education, and determining future research directions. The paper utilizes an in-depth survey of current research papers in answering these questions. It provides a comprehensive review of existing solutions in offering personalized e-learning solutions. It also elaborates on different learning models and learning theories, which are significant in providing personalized education. It proposes an efficient framework, which can offer personalized e-learning to each learner. The proposed framework includes five modules i.e Data Module, Adaptive Learning Module, Adaptable Learning Module, Recommender Module, Content and Assessment Delivery Module. Our work also identifies significant directions for future research. The paper is beneficial for academicians and researchers in understanding the requirements of such a system, comprehending its methodologies, and identifying challenges which are needed to be addressed.
Keyword:
Electronic learning
Education
Videos
Adaptation models
Object recognition
Artificial intelligence
Learning (artificial intelligence)
Recommender systems
Data mining
Adaptability
artificial intelligence
educational data mining
knowledge tracing
personalized e-learning
recommender systems

期刊

IEEE Access 封面图
IEEE Access
IF:
3.6
论文数:
9.8W
被引数:
29.4W

机构

暂无机构信息
引用论文

引用论文

err分享
err收藏
Induction Of Lymphokine-Activated Killer (LAK) Activity in Canine Lymphocytes with Low Dose Human Recombinant InterIeukin-2in vitro
err1994-01-01
err0
PREAI
errStuart C. Helfand; Steve A. Soergel; Jaime F. Modiano; Jacquelyn A. Hank; Paul M. Sondel
err分享
err收藏
Powerful CEOs and earnings quality
err2021-06-29
err0
PREAI
errShin-Rong Shiah-Hou
err分享
err收藏
THE DIGITAL GENERATION: A STUDY ON HOW UNDERGRADUATE STUDENTS FROM ROMANIA ARE CONSUMING DIGITAL MEDIA
err2020-03-01
err0
PREAI
errRamona-Alexandra Neghină; Dragoș-Georgian Ilie; Valentin-Andrei Mănescu; Mihaela-Rodica Ganciu; Gheorghe Militaru
err分享
err收藏
Community-Based Essential Newborn Care Practices and Associated Factors among Women of Enderta, Tigray, Ethiopia, 2018
err2020-01-21
err0
errOAAI
errGebrehiwot Gebremariam Weldeargeawi; Zenawi Negash; Alemayehu Bayray Kahsay; Yemane Gebremariam; Kidanemaryam Berhe Tekola
err分享
err收藏
Knowledge Tracing: A Survey知识追踪: 一项调查
err2023-02-09
err77
errOAAI
errAbdelrahman, Ghodai; Wang, Qing; Nunes, Bernardo
err分享
err收藏
err分享
err收藏
学者 查看更多内容