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

Hazriani, Tsuneo Nakanishi, Kenji Hisazumi, Akira Fukuda

研究成果: ジャーナルへの寄稿学術誌査読


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.

ジャーナルInternational Journal of Advanced Computer Science and Applications
出版ステータス出版済み - 2018

!!!All Science Journal Classification (ASJC) codes

  • コンピュータ サイエンス(全般)


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