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.
Highlights
A growing number of language learners are using informal language learning applications to learn new vocabulary anytime and anywhere
This paper shows the potential that informal ubiquitous vocabulary learning environments have to provide language learners with personalized translations based on their learning activity
We proposed methods to identify the learners’ intended meaning when they look up a polysemous word or homograph
Summary
A growing number of language learners are using informal language learning applications to learn new vocabulary anytime and anywhere. Dictionaries and online translators are learners’ preferred language learning tools (Demouy et al, 2016) with Google Translate being the most used translation tool (Ducar & Schocket, 2018). Learners encounter issues with translation when they encounter words that can have several meanings depending on the context. These are known as polysemous words and homographs. Other studies have shown that language learners’ preferred language learning tools are dictionaries and online translation tools (Demouy et al 2016). The most widely used translation tool is Google Translate (Ducar & Schocket, 2018) Using these tools, learners choose the vocabulary they are about to learn. Learners choose to learn words inspired by their surroundings, interests and goals (Sharples et al, 2005)
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