Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
11-2021
Abstract
The last two decades have witnessed an explosive growth in technology adoption in education. Proliferation of digital learning resources through Massive Open Online Courses (MOOCs) and social media platforms coupled with significantly lowered cost of learning has brought and is continuing to take education to every doorstep globally. In recent years, the use of asynchronous online discussion forums has become pervasive in tertiary education institutions. Online discussion forums are widely used for facilitating interactions both during the lesson time and beyond. Numerous prior studies have reported benefits of using online discussion forums including enhanced quality of learning, improved level of thinking beyond the classroom, collaborative knowledge building, and enhanced participation by shy or intimidated students. By monitoring and analyzing students’ activities in online discussion forums, instructors can intervene and manage students’ learning. For the instructor to employ appropriate intervention measures, both quantitative and qualitative analyses of students’ participation are important. To mitigate the challenge of the sheer volume of conversation threads in online discussion forums, we present a text mining approach to profiling student learning based on Q&A interactions. Firstly, we perform text classification to categorize conversations into two categories: non-programming-related and programming-related. Secondly, from the programming-related conversation threads, our method categorizes students into four participation proficiency types based on their Q&A activities. Next, our method determines whether a student adopts more explicit or implicit expression behavior in Q&A activities. We evaluate our approach on the second-year computing course, Web Application Development II. Finally, we share the lessons learned in this teaching process.
Keywords
Profiling student learning, Online discussion forum, Q&A interactions, Slack
Discipline
Computer Sciences | Educational Assessment, Evaluation, and Research | Higher Education
Research Areas
Data Science and Engineering
Publication
Proceedings of the International Conference on Computers in Education (ICCE), Thailand, November 22-26
First Page
251
Last Page
260
Publisher
ICCE
City or Country
Thailand
Citation
ONG, De Lin; SHIM, Kyong Jin; and GOTTIPATI Swapna.
Profiling Student Learning from Q&A Interactions in Online Discussion Forums. (2021). Proceedings of the International Conference on Computers in Education (ICCE), Thailand, November 22-26. 251-260.
Available at: https://ink.library.smu.edu.sg/sis_research/6897
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Included in
Computer Sciences Commons, Educational Assessment, Evaluation, and Research Commons, Higher Education Commons