In response to the global pandemic, there is an increased need for tools that can support independent learning. To scaffold learning English vocabulary words, a word counting module was implemented into an online translation (OT) system to generate personalized word lists tailored to the interest/specialization of each OT user. After inputting 50 articles in English and translating 25 Korean articles (into English) with content related to Artificial Intelligence, we generated two lists based on the inputted and translated text. The lists included the 100 most frequent words ranked from the highest to lowest frequency with individual word count. The lists had low word overlap with other widely used academic word lists and contained highly specific words (e.g., proper nouns, abbreviations, trending words, common area terminologies) aligned with the topic of interest (AI). By generating and referring to personalized word lists, English language learners will be able to select useful words to review with online flashcards (e.g., Quizlet) and dictionaries (e.g., WordReference, Linguee), and independently work towards developing their specialized vocabulary knowledge.
Jin Ha Woo