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Course Recommendations in Online Education Based on Collaborative Filtering Recommendation Algorithm

Jing Li, Zhou Ye, Wei Wang
2020 Complexity  
By improving the traditional recommendation algorithm based on collaborative filtering, the course recommendation results are more in line with users' interests, which greatly improves the accuracy and  ...  In this paper, a personalized online education platform based on a collaborative filtering algorithm is designed by applying the recommendation algorithm in the recommendation system to the online education  ...  Conflicts of Interest e authors declare that they have no conflicts of interest reported in this paper. Figure 1 : 1 Personalized the video site's content.  ... 
doi:10.1155/2020/6619249 fatcat:gnvblysc3vbrhial7qq6astg2i

Optimization Analysis and Implementation of Online Wisdom Teaching Mode in Cloud Classroom Based on Data Mining and Processing

Jing Gao, Xiao-Guang Yue, Lulu Hao, M. James C. Crabbe, Otilia Manta, Nelson Duarte
2021 International Journal of Emerging Technologies in Learning (iJET)  
It not only highlights the core position of personalized curriculum recommendation in the field of online education, but also makes the cloud classroom online teaching mode more intelligent and meets the  ...  Therefore, this paper proposes a cloud classroom online teach-ing system under the personalized recommendation system.  ...  The core idea is that users who have the same or similar interests in the past will have the same interest in the future. The recommended algorithm for the basic model is based on sample data.  ... 
doi:10.3991/ijet.v16i01.18233 fatcat:d3abfrssz5bzlkdz2ykw2su5ui

Analysis of Factors Affecting User Willingness to Use Virtual Online Education Platforms

Xiaogai Shen, Jianli Liu
2022 International Journal of Emerging Technologies in Learning (iJET)  
However, users differ in their willingness to use virtual online education platforms.  ...  This paper explores the factors affecting user willingness to use such platforms, laying a theoretical basis for promoting virtual online education.  ...  the online education products and have a thorough understanding of the actual requirements and behavior characteristics of the users, only in this way can they design products that can meet the expectations  ... 
doi:10.3991/ijet.v17i01.28713 doaj:0a5a193810804e068a77943850c07133 fatcat:ndulu6chlbabtobfjqgldq7l7a

A Survey of Online Course Recommendation Techniques

Jinliang Lu
2022 Open Journal of Applied Sciences  
The recommender system has been widely used in various Internet applications due to its high efficiency in filtering information, helping users to quickly find personalized resources from thousands of  ...  In addition, due to its great use value, many new researches have been proposed in the field of recommender systems in recent years, but there are not many works on online course recommendation at present  ...  For an efficient online course recommender system, the recommender system should be able to capture users' interests according to users' historical course selection records, extract users' personalized  ... 
doi:10.4236/ojapps.2022.121010 fatcat:ww7vgve2bvecjfjyzc2iqevcam

Application of Mobile Learning and Big Data on Improving Flipped Classroom and MOOCs

Weibo Huang, Jianghui Liu, Xiaowen Wang, Jinkang Li, Rong Zhang, Yanxia Liu
2016 DEStech Transactions on Computer Science and Engineering  
the mobile learning techniques are applied to flipped classroom and Massive Open Online Courses (MOOCs).  ...  Mobile learning platform can be used to achieve the development of massive open online courses by combining curriculum resources, technology management and mobile intelligence.  ...  The personalized resources recommendation model contains behavior record module, model analysis module and the recommendation algorithm module.  ... 
doi:10.12783/dtcse/icte2016/4765 fatcat:3uctiod225gz3acomyokvntzuy

What Should We Teach in Information Retrieval?

Ilya Markov, Maarten de Rijke
2019 SIGIR Forum  
In particular, we argue for more attention, in basic IR teaching materials, to scenarios such as recommender systems, and to topics such as query and interaction mining and understanding, online evaluation  ...  And their development is best thought of as a two-stage development process: offline development followed by continued online adaptation and development based on interactions with users.  ...  online course.  ... 
doi:10.1145/3308774.3308780 fatcat:ixkmjqqmsjeavictyumi7xkxsu

A MENTAL HEALTH EDUCATION STRATEGY BASED ON ONLINE VIDEOS

2020 REVISTA ARGENTINA DE CLINICA PSICOLOGICA  
The AMHE analyzes the sequence and frequency of the access to category pages in the search for online videos, determines the categories of the videos watched by college students, and extracts the keywords  ...  To protect the mental health of college students, this paper proposes two methods based on online videos, namely, the accurate mental health education (AMHE) method and the personalized mental health education  ...  In order to recommend personalized knowledge content for each learner in the elearning platform, the first thing to do is to have a certain understanding of each learner's personality preferences and learning  ... 
doi:10.24205/03276716.2020.7 fatcat:mqqp3wk7zjfk3mhzekbs2536u4

A Survey Paper on E-Learning Recommender System

Reema Sikka, Amita Dhankhar, Chaavi Rana
2012 International Journal of Computer Applications  
This paper suggests the use of web mining techniques to build such an agent that could recommend online learning activities or shortcuts in a course web site based on learners' access history to improve  ...  course material navigation as well as assist the online learning process.  ...  Moreover, we are interested in recommending beneficial learning activities to enhance online learning, as well as recommending shortcuts or jumps to some resources to help users better navigate the course  ... 
doi:10.5120/7218-0024 fatcat:t2jpvplno5auhokn746j5ae7au

Subjective Areas of Improvement: A Personalized Recommendation

Suganya G, Premalatha M, Piyush Dubey, Aryan Raj Drolia, Srihari S
2020 Procedia Computer Science  
The proposed system will also recommend the list of online courses and materials that the users can make use of to strengthen themselves.  ...  The proposed system will also recommend the list of online courses and materials that the users can make use of to strengthen themselves.  ...  In short, online personalized recommendation helps the student to improve their performance without the need for any kind of human mentor. .  ... 
doi:10.1016/j.procs.2020.05.037 fatcat:nybb7vc4vvhlrihflykek6ti5i

Shaping online learning communities and the way adaptiveness adds to the picture

Penelope Markellou, Maria Rigou, Athanasios Tsakalidis, Spiros Sirmakessis
2005 International Journal of Knowledge and Learning  
With learning being a process closely connected to sociability, learning on the web is in many cases accompanied and promoted by the creation and maintenance of online communities.  ...  Even though today's web-based learning environments have drastically evolved and now incorporate techniques from other domains and application areas (such as web mining, AI, user modelling, and profiling  ...  'personal' pages, but this has proven to be of limited use, since it depends on the users' knowing in advance the content of their interest.  ... 
doi:10.1504/ijkl.2005.006252 fatcat:nwjquw3q6nb4hjgbstzbqkedpu

Collaborative filtering for expansion of learner's background knowledge in online language learning: does "top-down" processing improve vocabulary proficiency?

Masanori Yamada, Satoshi Kitamura, Hideya Matsukawa, Tadashi Misono, Noriko Kitani, Yuhei Yamauchi
2014 Educational technology research and development  
The online learning environment recommends English news articles using information obtained from other users with similar interests.  ...  In recent years, collaborative filtering, a recommendation algorithm that incorporates a user's data such as interest, has received worldwide attention as an advanced learning support system.  ...  As Manouselis et al. (2010) indicated, in order to understand ''interest'' in educational settings, discussion should focus on what kinds of ''variables'' influence learners' interests for a recommendation  ... 
doi:10.1007/s11423-014-9344-7 fatcat:gija5knl2ve6rcadkpqcwp4kfa

A Learning and Management System on Account of Software and Hardware

Chun-ying TANG, Fu-rui YANG, Zi-qian GUO, Yu-jie DONG, Hong-wei ZHAO
2018 DEStech Transactions on Computer Science and Engineering  
describe and study a system, which is taking Jilin University as an example, based on the system feasibility and necessity of campus applications, this paper analyzes and investigates the problems existing in  ...  After about 400 teachers and students using over 2 months, because of its good user experience and characteristics of learning, we gain lots of praise, now we are planning to promote it gradually.  ...  This work was supported in part by the Jilin province development and Reform Commission Special industrial innovation 2016C035 and State Key Laboratory of applied optics.  ... 
doi:10.12783/dtcse/aiie2017/18230 fatcat:irt5l2t2d5hmngpwrx4647xecq

A Study of English Informative Teaching Strategies Based on Deep Learning

Yaojun Guo, Naeem Jan
2021 Journal of Mathematics  
The experimental research results prove that the online e-learning service platform cannot only effectively meet the diverse and personalized English learning needs of university students, but also improve  ...  The model incorporates deep learning models based on word embedding and text convolutional networks, which can uncover the hidden interest features of academics for English.  ...  teachers. e personalization of education requires teachers to develop targeted development strategies by understanding students' psychological characteristics and interests. is conflict is also solved  ... 
doi:10.1155/2021/5364892 fatcat:sihlhwrlanhubaw35lhuhnq5ra

The Construction of Accurate Recommendation Model of Learning Resources of Knowledge Graph under Deep Learning

Xia Yang, Leping Tan, Rahman Ali
2022 Scientific Programming  
The knowledge graph has been fully applied in this process. The application of deep learning in the recommendation systems has further enhanced their performance.  ...  During the last two decades, a large number of different types of recommendation systems were adopted that present the users with contents of their choice, such as videos, products, and educational content  ...  Acknowledgments is study was supported by the Hunan Provincial Natural Science Foundation Project: Construction of Accurate Learning Resource Recommendation Model Based on Knowledge Graphs (no. 2019JJ70062  ... 
doi:10.1155/2022/1010122 fatcat:4tfv7v3bwvbtpmdgbniq5zh5nu

An English Reading and Learning System Based on Web

Xiaoying He, Muhammad Usman
2021 Scientific Programming  
, and user satisfaction.  ...  English reading materials are integrated using a feature model, and the adaptive recommendation system is built using the ID3 method.  ...  Click "reset" to clear everything in the text box so that users can fill in personal information.  ... 
doi:10.1155/2021/7281269 fatcat:uernlrbvovazjfggls32cmsrg4
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