EVOV: A video recommendation system to support sustainable vocabulary learning

Learning vocabulary is both critical and boring for many EFL (English as foreign language) learners and one major difficulty is the lack of suitable context for learning new words. Although videos can provide a rich context for learning vocabulary, it often takes more time than textual media to learn. This paper presents the EVOV system which is to exploit the role of video in vocabulary learning with the human-interaction mechanism and recommendation engine. This system models vocabulary learning as an evolutionary process. It involves watching videos, reviewing vocabulary, learner modeling and individualized recommendations. This paper introduces the core modules of EVOV and demonstrates how it supported vocabulary learning through video in an efficient and sustainable way.