Innovation in Language Learning

Edition 16

Accepted Abstracts

Development of a Recommendation Panel for Wordhyve Language Learning App

Mohammad Nehal Hasnine, Research Center for Computing and Multimedia Studies, Hosei University (Japan)

Junji Wu, Communication Engineering Department, Waseda University (Japan)

Masatoshi Ishikawa, Faculty of Business Administration Tokyo Seitoku University (Japan)

Hiroshi Ueda, 1Research Center for Computing and Multimedia Studies, Hosei University (Japan)


To language learners, vocabulary is an inseparable component of a foreign language as, without significant vocabularies, it is rather difficult to read, write, and communicate. Wordhyve is a ubiquitous language learning app that assists foreign language learners in enhancing foreign vocabulary using various authentic informal learning contexts [1]. Wordhyve allows the users to capture and record information linked with each learning activity as the learning log using its ubiquitous functions. Later, the analytics of the Wordhyve app analyzes the logs for generating incidental vocabularies for broadening vocabulary learning opportunities. In this paper, a new feature for the app, namely Wordhyve Recommendation Panel, is developed to recommend incidental vocabularies and smartly-generated learning contexts. In the app, incidental vocabularies and smartly-generated learning contexts are generated by detecting the objects found and analyzing the scenes of an image that a learner uploaded to memorize an intentional vocabulary. The recommendation panel lets the learner choose which incidental vocabularies to put aside for study next and which of the smartly-generated learning contexts to use for memorizing a word. The image analytics of Wordhyve relies on object detection and automatic image captioning technologies. The strategy used to build Wordhyve’s analytical functions is to use an intentional learning log as the trigger to generate multiple incidental vocabularies that a learner could learn in the long run.

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