.png){kind=icon}
返回
Enhancing e-learning through AI advanced techniques for optimizing student performance
.png){kind=icon}
OA
AI
DOI：10.7717/peerj-cs.2576.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The integration of Artificial Intelligence (AI) into e-learning has transformed conventional educational approaches, improving the learning process and maximizing student achievement. This study offers a thorough examination of how AI can be utilized to enhance e-learning results by employing advanced predictive methods and performance optimization strategies. The main goals consist of creating an AI-based framework to monitor and analyze student interactions, evaluating the influence of online learning platforms on student understanding using advanced algorithms, and determining the most efficient methods for blended learning systems. AI algorithms, known for their cognitive ability and capacity to learn, adapt, and make decisions, are employed to analyze and forecast student performance, thereby improving educational quality and outcomes. The practical results obtained by implementing machine learning and deep learning models, such as convolutional neural networks (CNN) and recurrent neural networks (RNN), show substantial enhancements in forecasting different performance metrics. This research highlights the ability of AIto develop adaptable, effective, and successful e-learning environments, promoting enhanced academic achievement and customized learning experiences. The findings demonstrate that CNN outperformed other deep learning and machine learning algorithms in terms of accuracy during the prediction phase, showcasing the advanced capabilities of AI in educational contexts. Portions of this text were previously published as part of a preprint (https://doi.org/10.21203/rs.3.rs4724603/v1).
Keyword:
Machine learning
Deep learning
Education data
AI
Artificial Intelligence (AI)
eLearning
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
2.5
论文数:
3.4K
被引数:
6.9K
机构
引用论文
Diastereo- and enantioselective cyclopropanation of alkyenyl fluorides with benzyl diazoarylacetates
PREAI
分享收藏Machine-Learning Techniques for Predicting Phishing Attacks in Blockchain Networks: A Comparative Study.png)
Algorithms
OAAI
AlgorithmsIF0
OAAI分享收藏分享收藏Review on Convolutional Neural Networks (CNN) in vegetation remote sensing卷积神经网络 (CNN) 在植被遥感中的应用综述OAAI
OAAI分享收藏Innovating for elderly people: the development of geront’innovations in the French silver economy
PREAI
分享收藏
查看更多内容