An Intelligent Platform with Automatic Assessment and Engagement Features for Active Online Discussions

摘要

In a university context, discussion forums are mostly available in Learning and Management Systems (LMS) but are often ineffective in encouraging participation due to poorly designed user interface and the lack of motivating factors to participate. Our integrated platform with the Telegram mobile app and a web-based forum, is capable of automatic thoughtfulness assessment of questions and answers posted, using text mining and Natural Language Processing (NLP) methodologies. 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 thinking resulting in better quality contributions. In addition, the platform is designed with six features to ensure that students remain actively engaged on the platform. We report the performance of our platform based on our implementations for a university course in two runs, and compare with existing systems to show that by using our platform, students' participation and engagement are highly improved, and the quality of posts will increase. Most importantly, our students' performance in the course was shown to be positively correlated with their participation in the system.