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Improving collaborative learning by personalization in Virtual Learning Environments using agents and competency-based ontology

机译:使用代理和基于能力的本体在虚拟学习环境中通过个性化改善协作学习

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With the spread of distance education courses or blended, an increasingly common problem is the lack of a personalized accompaniment to the student and the delay in responding by mediators and other colleagues the doubts and requests from students in Virtual Learning Environments (VLEs), usually posted on forums or manifested via e-mail. The approach taken to solving this problem presented in this paper is based on multi-agent systems and a competency-based ontology of the learner model. Through such technologies, the student's doubts are identified and these are directed to community members who have the profile with best suited skills and competencies to resolve it, decreasing the response time of doubts from students. A Petri Net has been developed in order to represent interactions among agents. The system was tested in a Numerical Analysis class that makes use of the VLE Moodle. The results of the tests were used to prove the validity of the system and the viability of the solution. Survey questionnaires were passed in the classroom in order to obtain and evaluate the students' impressions about the resource available to them in the VLE.
机译:随着远程教育课程的普及或融合,一个越来越普遍的问题是缺乏针对学生的个性化伴奏,以及调解员和其他同事对学生在虚拟学习环境(VLE)中提出的疑问和要求的回应有所延迟,通常是在论坛上或通过电子邮件显示。本文提出的解决此问题的方法基于多智能体系统和学习者模型的基于能力的本体。通过此类技术,学生的疑惑得以识别,并将其定向到社区成员,这些社区成员具有最适合解决问题的技能和能力的档案,从而减少了学生对疑惑的响应时间。为了表示代理之间的交互,已经开发了Petri网。该系统在使用VLE Moodle的数值分析类中进行了测试。测试结果被用来证明系统的有效性和解决方案的可行性。在教室中通过了调查问卷,以获取并评估学生对VLE中可用资源的印象。

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