An Intelligent Tutoring System for Japanese Language Particles with User Assessment and Feedback

Thesis Abstract: In recent years, an increasing number of Ateneo students are taking an interest in the Japanese language. For Ateneo students beginning their study of the language however, Japanese particles are difficult concepts because they cannot be translated to equivalent words in English. For a beginner learner, it is inevitable to view a second language with the lens of a first language as shown by the concept of transfer in second language acquisition. As a result, learners tend to misconstrue Japanese particles by attempting to understand them with respect to non-existent equivalents in English.

In this research, we would like to develop an intelligent tutoring system for Ateneo students taking introductory Japanese (FLC 1JSP) to aid them better understand Japanese particles. The system would assess the learner’s understanding of Japanese particles by practice and depending on which particle where most mistakes are made, the system would give instructional feedback. Feedback to be implemented in the system use visual prototypes that represent the meaning of the particle. We hope to see if visual representations better teach Japanese particles to students as opposed to text-detailed explanations such as those commonly found in textbooks.

Members:
Zachary T. Chung

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