An intelligent platform with automatic assessment and engagement features for active online discussions

• Main Authors: CHEONG, Michelle L. F., CHEN, Yun-Chen, DAI, Bing Tian
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2019
• Subjects: Discussion forum; Natural Language Processing; Student engagement; Databases and Information Systems; Higher Education; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/5106; https://ink.library.smu.edu.sg/context/sis_research/article/6109/viewcontent/Cheong2019_IntelligentPlatformAutoAss_Engagement_av.pdf
• Institution: Singapore Management University

In a universitycontext, discussion forums are mostly available in Learning and ManagementSystems (LMS) but are often ineffective in encouraging participation due topoorly designed user interface and the lack of motivating factors toparticipate. Our integrated platform with the Telegram mobile app and aweb-based forum, is capable of automatic thoughtfulness assessment of questionsand answers posted, using text mining and Natural Language Processing (NLP)methodologies. We trained and applied the Random Forest algorithm to provideinstant thoughtfulness score prediction for the new posts contributed by thestudents, and prompted the students to improve on their posts, thereby invokingdeeper thinking resulting in better quality contributions. In addition, theplatform is designed with six features to ensure that students remain actively engagedon the platform. We report the performance of our platform based on ourimplementations for a university course in two runs, and compare with existingsystems to show that by using our platform, students’ participation and engagementare highly improved, and the quality of posts will increase.