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We propose a “smart” language learning system for students to acquire domain-specific vocabulary while taking an online course. F-Lingo, a browser plugin, works on top of the FutureLearn MOOC platform to provide learners with opportunities to study the words, phrases, and concepts that are important to the course topic. F-Lingo comprises three components. The Material Gathering component crawls the web pages of the MOOC course the student has chosen, collecting the entire textual content (with some exceptions). The Vocabulary Extraction component identifies domain-specific words, phrases, and concepts, and hyperlinks in the MOOC page to draw the student’s attention to them. Clicking a link displays a dialog window in which lexico-grammatical features, and definitions, of the extracted items can be studied, including illustrations in example sentences retrieved from external resources such as Wikipedia and FLAX. The Progress Tracking component records the clicks that students make on hyperlinks and the time spent in the dialog windows. This allows us to build the student’s vocabulary learning profile under the assumption that the more time the student pays attention to an item, the more worthy the item to be included in a follow-up language activity. These statistical data provide evidence and reasoning in our current and ongoing work on automatically generating personalized language activities and vocabulary tests at the end of the MOOC course. F-Lingo has been made available in three Data Mining courses on the FutureLearn MOOC platform and has been used by 109 learners. This research is ongoing. Future work focuses on automatically generating personalized vocabulary tests and activities based on the student’s click statistics. |
