{"title":"Application of educational data mining to create intelligent multi-agent personalised learning system","authors":"I. Krikun","doi":"10.1109/AIEEE.2017.8270534","DOIUrl":null,"url":null,"abstract":"In the paper, methodology to personalise learning according to the needs of individual students using educational data mining (EDM) to create intelligent multi-agent learning system is presented. First, systematic review on application of EDM to create intelligent learning systems is performed in Clarivate Analytics Web of Science database. Systematic review had shown that, currently, there is an increasing interest in EDM. After that, methods to personalise learning applying intelligent technologies to create optimised learning units for individual students are presented in the paper. Created students' profiles and personalised learning units should be further corrected applying EDM methods and tools. The model of intelligent multi-agent learning system based on application of intelligent technologies such as ontologies, recommender system, intelligent software agents and EDM is also presented in the paper. The principal success factors of the proposed methodology are pedagogically sound vocabularies of learning components, expert evaluation of the learning components in terms of its suitability to particular students, as well as application of ontologies, recommender system, intelligent software agents and EDM.","PeriodicalId":224275,"journal":{"name":"2017 5th IEEE Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 5th IEEE Workshop on Advances in Information, Electronic and Electrical Engineering (AIEEE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AIEEE.2017.8270534","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In the paper, methodology to personalise learning according to the needs of individual students using educational data mining (EDM) to create intelligent multi-agent learning system is presented. First, systematic review on application of EDM to create intelligent learning systems is performed in Clarivate Analytics Web of Science database. Systematic review had shown that, currently, there is an increasing interest in EDM. After that, methods to personalise learning applying intelligent technologies to create optimised learning units for individual students are presented in the paper. Created students' profiles and personalised learning units should be further corrected applying EDM methods and tools. The model of intelligent multi-agent learning system based on application of intelligent technologies such as ontologies, recommender system, intelligent software agents and EDM is also presented in the paper. The principal success factors of the proposed methodology are pedagogically sound vocabularies of learning components, expert evaluation of the learning components in terms of its suitability to particular students, as well as application of ontologies, recommender system, intelligent software agents and EDM.
本文提出了利用教育数据挖掘技术(EDM)创建智能多智能体学习系统,根据学生个体的需求实现个性化学习的方法。首先,在Clarivate Analytics Web of Science数据库中对EDM在智能学习系统中的应用进行了系统回顾。系统的回顾表明,目前人们对EDM的兴趣越来越大。然后,本文介绍了应用智能技术为个体学生创建优化学习单元的个性化学习方法。创建的学生档案和个性化学习单元应该进一步使用EDM方法和工具进行纠正。提出了基于本体、推荐系统、智能软件代理和EDM等智能技术的智能多智能体学习系统模型。所提出的方法的主要成功因素是教学上健全的学习组件词汇,根据其适合特定学生的学习组件的专家评估,以及本体,推荐系统,智能软件代理和EDM的应用。