Intelligent Tutoring System: A Proposed Approach to Javanese Language Learning in Indonesia

Intelligent Tutoring System: A Proposed Approach to Javanese Language Learning in Indonesia

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The Javanese language is becoming endangered, although it is one of compulsory subjects at schools. Students become unmotivated when they learn the language at school because of boring and irrelevant teaching and learning materials. Furthermore, their closest mentors such as teachers, parents and relatives can not provide motivating conditions to learn the Javanese language. In order to preserve the Javanese language through education at schools, Intelligent Tutoring System (ITS) is proposed for Javanese language learning. The student can learn the usage of Javanese language at a proper level of politeness through a natural dialog with Artificial Javanese Intelligent Tutor (AJI-Tutor).


Javanese language - one of 672 traditional languages in Indonesia is a native language of more than 75 million people [1]. However, most of its native speakers can not use the language in a proper manner. Recent research on Javanese language proficiency of students found that the Javanese youngsters can not apply correct Krama vocabularies in formal dialog based on context since the language is rarely use at home and in social organizations [2]. Therefore, the Javanese language should be used in daily activities to protect the language from becoming an endangered language.

Language preservation can be viewed from various perspectives, one of them is education. Regional languages, including Javanese language, have been established compulsory in the school curricula. However, Javanese language learning today is deplorable. Students tend to prefer to learn Bahasa Indonesia and English rather than the Javanese since those languages are more relevant in the era of globalisation.

An appropriate solution should be applied to so...

... middle of paper ...

...5. Rosic, M., Glavinic, V., and Stankov, S., Intelligent tutoring interoperability for the new web. Telecommunication Systems, 32, 2-3, 193-207(2006).
6. Schoelles, M. and Hamburger, H., The NLP role in animated conversation for CALL, Fifth conference on Applied Natural Language Processing, Washington DC, 127-134 (1997).
7. Plantamura, V.L., Gentile, E., and Angelini, A., Intelligent interaction for linguistic learning, Affective Computing and Intelligent Interaction, Beijing, China, 947-955 (2005).
8. Joshi, A.R. and Sasikumar, M., A constructivist approach to teaching sentences in indian languages, ICAC3, Mumbai, India, 14-19 (2009).
9. Greasser, A.C., Lu, S., Jackson, G.T., Mitchell, H.H., Ventura, M., Olney, A., and Louwerse, M.M., AutoTutor: a tutor with dialogue in natural language. Behavior Research Methods, Instruments, & Computers, 36, 2, 180-192(2004).

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