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https://hdl.handle.net/10356/103685
Title: | Personalized question recommendation for English grammar learning | Authors: | Fang, Lanting Tuan, Luu Anh Hui, Siu Cheung Wu, Lenan |
Keywords: | Content-based Recommendation DRNTU::Engineering::Computer science and engineering Grammar Question Recommendation |
Issue Date: | 2017 | Source: | Fang, L., Tuan, L. A., Hui, S. C., & Wu, L. (2018). Personalized question recommendation for English grammar learning. Expert Systems, 35(2), e12244-. doi:10.1111/exsy.12244 | Series/Report no.: | Expert Systems | Abstract: | Learning English grammar is a very challenging task for many students especially for nonnative English speakers. To learn English well, it is important to understand the concepts of the English grammar with lots of practise on exercise questions. Previous recommendation systems for learning English mainly focused on recommending reading materials and vocabulary. Different from reading material and vocabulary recommendations, grammar question recommendation should recommend questions that have similar grammatical structure and usage to the question of interest. The content similarity calculation methods used in existing recommendation methods cannot represent the similarity between grammar questions effectively. In this paper, we propose a content‐based approach for personalized grammar question recommendation, which recommends similar grammatical structure and usage questions for further practising. Specifically, we propose a novel structure named parse‐key tree to capture the grammatical structure and usage of grammar questions. We then propose 3 measures to compute the similarity between the question query and database questions for grammar question recommendation. Additionally, we incorporated the proposed recommendation method into a Web‐based English grammar learning system and presented its performance evaluation in this paper. The experimental results have shown that the proposed approach outperforms other classical and state‐of‐the‐art methods in recommending relevant grammar questions. | URI: | https://hdl.handle.net/10356/103685 http://hdl.handle.net/10220/48599 |
ISSN: | 0266-4720 | DOI: | 10.1111/exsy.12244 | Schools: | School of Computer Science and Engineering | Rights: | © 2017 John Wiley & Sons, Ltd. All rights reserved. This paper was published in Expert Systems and is made available with permission of John Wiley & Sons, Ltd. | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | SCSE Journal Articles |
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Personalized question recommendation for English grammar learning.pdf | 857.93 kB | Adobe PDF | View/Open |
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