Using an Automatic Approach to Classify Reflective Language Learning Skills of ESL Students

This paper reports and discusses on a project about designing a digital tool to support Chinese undergraduate students in reflecting on their English language (L2) learning experience. The tool namely ACTIVE was developed primarily based on a classification framework called A-S-E-R and Latent Semantic Analysis. It can automatically classify reflective L2 learning skills into four elements with each divided into four hierarchical levels. This paper begins by presenting the background of the study, followed by the details of methods of automatic classification and performance evaluation. The results of the project indicate that the computer-generated ratings for students' reflection are comparable to human ratings.

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