Object-oriented context description for movie based context-aware language learning

Hazriani, Tsuneo Nakanishi, Kenji Hisazumi, Akira Fukuda

Research output: Contribution to journalArticle

Abstract

Context-aware ubiquitous learning is a promising way to learn languages; however, it requires developers and operators of much effort to construct, deploy, and use the specialized system. As its alternative, this paper proposes movie based context-aware language learning (MBCALL) that enables learners to learn languages through quizzes generated along virtual contexts occurring in the movie to be replayed. Since full automatic context capturing from the movie is impossible, the authors define an object-oriented context model (OOCM) and also a textual context description language subject to the OOCM to describe the movie context easily by human work. The OOCM introduces the case grammar concept of natural language processing. This enables quiz generation based on types of the words for objects, actions, and modes found in the movie. Evaluation with a small movie by three subjects shows that the OOCM can guide them to enrich information included in the movie context; therefore, we can generate more types of quizzes based on the movie context.

Original languageEnglish
Pages (from-to)350-357
Number of pages8
JournalInternational Journal of Advanced Computer Science and Applications
Volume9
Issue number4
DOIs
Publication statusPublished - 2018

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

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