Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

7-2019

Abstract

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.

Keywords

Discussion forum, Natural Language Processing, Student engagement

Discipline

Databases and Information Systems | Higher Education | Numerical Analysis and Scientific Computing

Research Areas

Data Science and Engineering

Publication

Advances and Trends in Artificial Intelligence: 32nd International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2019, Graz, Austria, July 9-11, Proceedings

Volume

11606

First Page

730

Last Page

743

ISBN

9783030229993

Identifier

10.1007/978-3-030-22999-3_62

Publisher

Springer

City or Country

Cham

Additional URL

https://doi.org/10.1007/978-3-030-22999-3_62

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