论文标题
基于本体匹配和推荐系统的混合自适应教育电子学习项目
A Hybrid Adaptive Educational eLearning Project based on Ontologies Matching and Recommendation System
论文作者
论文摘要
在学习需求中的教学干预措施的实施受到了极大的关注，因为向所有学生提供相同的教育条件，在教学上是无效的。相反，更有效地考虑了适应学生真正个人技能的教学策略。朝这个方向上的一个重要创新是支持自动建模研究并调整教育需求和学生技能的教学内容的自适应教育系统（AES）。可以通过人工智能（AI）技术来增强这些教育方法的有效利用，以使网络的实质内容获取结构，并被搜索引擎所感知到已发表的信息。这项研究提出了一种新型的自适应教育学习系统（AEELS），该系统有能力从学习存储库中收集和分析数据，并根据学生的技能和经验将其适应教育课程。这是一种新型的混合机器学习系统，结合了一种半监督的分类方法，用于本体匹配和推荐机制，它使用了基于社区的基于社区和基于内容的过滤技术的混合方法，以便为每个学生提供个性化的教育环境。
The implementation of teaching interventions in learning needs has received considerable attention, as the provision of the same educational conditions to all students, is pedagogically ineffective. In contrast, more effectively considered the pedagogical strategies that adapt to the real individual skills of the students. An important innovation in this direction is the Adaptive Educational Systems (AES) that support automatic modeling study and adjust the teaching content on educational needs and students' skills. Effective utilization of these educational approaches can be enhanced with Artificial Intelligence (AI) technologies in order to the substantive content of the web acquires structure and the published information is perceived by the search engines. This study proposes a novel Adaptive Educational eLearning System (AEeLS) that has the capacity to gather and analyze data from learning repositories and to adapt these to the educational curriculum according to the student skills and experience. It is a novel hybrid machine learning system that combines a Semi-Supervised Classification method for ontology matching and a Recommendation Mechanism that uses a hybrid method from neighborhood-based collaborative and content-based filtering techniques, in order to provide a personalized educational environment for each student.
