Abstract
This paper reports and discusses on the initial stage of developing an educational tool to support Chinese undergraduate students in reflecting on their English language (L2) learning experience. By using a classification framework called A-S-E-R and Latent Semantic Analysis, we developed a digital tool to automatically classify reflective L2 learning skills into different elements and hierarchical levels. This paper begins by presenting the background and objectives of the study, followed by the details of method and results. Preliminary findings show that the tool performed satisfactorily on our testing data and the computer-generated reflection ratings were comparable to human ratings. Copyright © 2013 IEEE.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 2013 3rd International Conference on IT Convergence and Security, ICITCS 2013 |
| Place of Publication | Macao |
| Publisher | IEEE |
| Pages | 1-3 |
| ISBN (Print) | 9781479928453 |
| DOIs | |
| Publication status | Published - 2013 |
Citation
Cheng, G., & Chau, J. (2013). An approach to identify levels of reflection using latent semantic analysis. In Proceedings of the 2013 3rd International Conference on IT Convergence and Security, ICITCS 2013 (pp. 1-3). Macao: IEEE.Keywords
- Classification
- EPortfolio
- Reflective learning
- Text mining