Abstract
Abstract
A growing number of language learners use ubiquitous language learning applications to learn anytime and anywhere. Learners translate and learn isolated words inspired by their activities and surroundings. However, isolated words may have several meanings that change depending on the context. Since learners don’t have the opportunity to indicate the meaning they are looking for in an online learning environment, they risk learning translations that do not correspond to their intended meaning. Identifying the intended meaning of the learner is needed to provide them with an appropriate translation. However, isolated words are difficult to disambiguate due to a lack of text around them. To this end, informal ubiquitous learning environments can offer another type of context, one that is formed by the users’ past learning logs. In this work, we propose using the learners’ past vocabulary to disambiguate their intended meaning when they look up isolated words. Accordingly, we propose and evaluate three methods. The first method considers that the intended meaning of the learner is the one that is the most semantically similar to the learner’s past vocabulary. The second method builds on the first method but gives more weight to the vocabulary that the learner logged shortly before the target word. The third method addresses situations where the semantic similarities between the different meanings of the word and the past vocabulary have similar values. In those cases, the method considers that the intended meaning of the learner is the most common meaning in the target language. The three methods were evaluated using 148 logs of SCROLL, a ubiquitous informal language learning environment. The success rates of the three methods were 72.180%, 75.630%, and 83.050% respectively. This work shows that the past activity of language learners in informal ubiquitous language learning environments could be used to identify their intended meaning when learning a new word.
Publisher
Springer Science and Business Media LLC
Subject
Computer Science Applications,Education
Reference30 articles.
1. B. T. Atkins, K. Varantola, Monitoring dictionary use. International Journal of Lexicography. 10(1), 1–45 (1997).
2. M. Azab, A. Salama, K. Oflazer, H. Shima, J. Araki, T. Mitamura, An nlp-based reading tool for aiding non-native english readers (2013).
3. A. Boulton, S. De Cock, Dictionaries as aids for language learning. International Handbook of Modern Lexis and Lexicography, 1–17 (2017). https://doi.org/10.1007/978-3-642-45369-4_25-1.
4. P. De Brabanter, M. Kissine, Utterance Interpretation and Cognitive Models. vol. 20 (Brill, 2009). https://doi.org/10.1163/9789004253148.
5. V. Demouy, A. Jones, Q. Kan, A. Kukulska-Hulme, A. Eardley, Why and how do distance learners use mobile devices for language learning?. The EuroCALL Review. 24(1), 10–24 (2016).
Cited by
5 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献