学习成果与前提知识推荐系统的开发

Maria Koshkareva, Maksim Khlopotov, Anastasiia Chernysheva
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引用次数: 1

摘要

本文描述了基于课程信息的学习成果和前提知识推荐系统的开发过程。推荐系统被设计为在education Program Maker服务中实现,用于处理教育过程元素。该推荐系统旨在帮助大学工作人员创建学术课程,从而使大学的文书工作更容易、更快速地数字化。使用通用句子编码器和学习内容数据计算学习结果建议。前提知识推荐是与有关课程和概念领域的信息计算。为在服务中实现已开发的算法进行了修改,并为显示推荐的表单创建了接口原型。使用命中率指标对模型进行评估;结果表明,最终模型优于基线。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Development of Learning Outcomes and Prerequisite Knowledge Recommendation System
This paper describes the development process of learning outcomes and prerequisite knowledge recommendation system based on the information about an academic course. The recommendation system is designed to be implemented in the service Educational Program Maker for working with education process elements. The recommendation system aims to help university staff members during academic course creation and, as a result, make the paperwork digitizing in universities easier and faster. Learning outcomes recommendations are computed with the Universal Sentence Encoder and learning content data. Prerequisite knowledge recommendations are calculated with information regarding curricula and concept domains. Developed algorithms were modified for implementation in the service, and interface prototypes for forms with displayed recommendations were created. Models were evaluated with the hit rate metric; the results showed that final models outperform baselines.
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