Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
12-2019
Abstract
Traditionally teaching is usually one directional where the instructor imparts knowledge and there is minimal interaction between learners and instructor. With the focus on learner-centred pedagogy, it can be a challenge to provide timely and relevant guidance to individual learners according to their levels of understanding. One of the options available is to collect reflections from learners after each lesson to extract relevant and high-value feedback so that doubts or questions can be addressed in a timely manner. In this paper, we derived an approach to automate the identification of doubts from the informal reflections through features analysis and machine learning. Using reflections as a feedback mechanism and aligning it to the weekly course content can pave way to a promising approach for learner-centered teaching and personalized learning.
Keywords
Doubt identification, Learner-centred pedagogy, informal reflections
Discipline
Computer Sciences | Educational Assessment, Evaluation, and Research | Higher Education
Research Areas
Data Science and Engineering
Publication
ICCE 2019: Proceedings of the 27th International Conference on Computers in Education, Kenting, Taiwan, December 2-6
First Page
1
Last Page
10
ISBN
9789869721431
Publisher
Asia-Pacific Society for Computers in Education
City or Country
Taiwan
Citation
LO, Siaw Ling; TAN, Kar Way; and OUH, Eng Lieh.
Do my students understand? Automated identification of doubts from informal reflections. (2019). ICCE 2019: Proceedings of the 27th International Conference on Computers in Education, Kenting, Taiwan, December 2-6. 1-10.
Available at: https://ink.library.smu.edu.sg/sis_research/4669
Copyright Owner and License
Authors
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