Wordhyve: A context-aware language learning app for vocabulary enhancement through images and learning contexts

Abstract

Vocabulary acquisition is an essential component for mastering any language as words are the building blocks of a language. In informal learning, foreign language learners often struggle to memorize new vocabularies, and therefore, new tools need to be developed to facilitate vocabulary acquisition. In computer-assisted learning environments, images are often used as annotations to represent words because images convey the essence of a word more effectively than verbal descriptions. Also, understanding the learning contexts in which learning happens is crucial for any computer-assisted learning environment. From this standpoint, in this research, a context-aware language learning app called Wordhyve is developed. Wordhyve, a native Android app, is built to support foreign language learners in memorizing foreign vocabularies using multimedia annotations, including images, texts, translation, voices, and contextual clues. Wordhyve allows language learners to capture and record lifelogs. Later on, the app uses those learning experiences as triggers to enhance foreign vocabularies. The analytics of the Wordhyve use those logs for the recommendation of incidental vocabularies and assist learners in memorizing those recommended vocabularies using various learning contexts. Wordhyve uses image analytics on the learner-captured images to recommend those incidental vocabularies.