Integrated telegram and web-based forum with automatic assessment of questions and answers for collaborative learning

• Main Authors: CHEONG, Michelle L. F., CHEN, Yun-Chen, DAI, Bing Tian
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2018
• Subjects: Q&A forum; Collaborative learning; Text mining; Natural language processing; Machine learning; Computer Sciences; Higher Education
• Online Access: https://ink.library.smu.edu.sg/sis_research/4267
• Institution: Singapore Management University

We designed, developed and implemented an integrated Telegramand Web-based Forum capable of automatic thoughtfulness assessment of questionsand answers, using text mining and Natural Language Processing (NLP)methodologies, for collaborative learning. We trained and applied the RandomForest algorithm to provide instant thoughtfulness score prediction for the newposts contributed by the students, and prompted the students to improve ontheir posts, thereby invoking deeper learning. In addition, the platform isdesigned to ensure that students remain engaged on the platform. Our initialimplementation for a university course on spreadsheets modeling using Excel,shows some promising results which strengthened our belief that through theprocess of asking good questions, and providing good answers, students’learning can be improved beyond the traditional classroom, and beyondinstructor-student relationship.