Integrated Telegram and Web-based Forum with Automatic Assessment of Questions and Answers for Collaborative Learning

被引:0
|
作者
Cheong, Michelle L. F. [1 ]
Chen, Jean Y-C [1 ]
Dai, Biug Tian [1 ]
机构
[1] Singapore Management Univ, Sch Informat Syst, Singapore, Singapore
来源
PROCEEDINGS OF 2018 IEEE INTERNATIONAL CONFERENCE ON TEACHING, ASSESSMENT, AND LEARNING FOR ENGINEERING (TALE) | 2018年
关键词
Q&A forum; collaborative learning; text mining; natural language processing; machine learning; ONLINE;
D O I
暂无
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
We designed, developed and implemented an integrated Telegram and Web-based Forum capable of automatic thoughtfulness assessment of questions and answers, using text mining and Natural Language Processing (NLP) methodologies, for collaborative learning. We trained and applied the Random Forest algorithm to provide instant thoughtfulness score prediction for the new posts contributed by the students, and prompted the students to improve on their posts, thereby invoking deeper learning. In addition, the platform is designed to ensure that students remain engaged on the platform. Our initial implementation for a university course on spreadsheets modeling using Excel, shows some promising results which strengthened our belief that through the process of asking good questions, and providing good answers, students' learning can be improved beyond the traditional classroom, and beyond instructor-student relationship.
引用
收藏
页码:9 / 16
页数:8
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