Main strategies of internet-based Japanese language teaching and the associated risks : a thesis presented in partial fulfilment of the requirements for the degree of Master of Arts in Japanese at Massey University

This study formulates two models of using Internet in classroom based Japanese language education. The models identified, the static model and the dynamic model, can be used in planning the strategy of introducing Internet as an educational medium in Japanese language classroom. Apart from elaborating the features of the models, and clarifying their relationships to recognized foreign/second language teaching approaches, we determine the risks, associated with Internet based Japanese language education and consider the ways to mitigate them. Our study is backed by 2 surveys, and by qualitative and quantitative analysis of Internet search engine data and of a database of teachers' beliefs data. This study may be of value to Japanese language teachers and learners, education administrators and to designers of CALL software

Towards Machine Speech-to-speech Translation

There has been a good deal of research on machine speech-to-speech translation (S2ST) in Japan, and this article presents these and our own recent research on automatic simultaneous speech translation. The S2ST system is basically composed of three modules: large vocabulary continuous automatic speech recognition (ASR), machine text-to-text translation (MT) and text-to-speech synthesis (TTS). All these modules need to be multilingual in nature and thus require multilingual speech and corpora for training models. S2ST performance is drastically improved by deep learning and large training corpora, but many issues still still remain such as simultaneity, paralinguistics, context and situation dependency, intention and cultural dependency. This article presents current on-going research and discusses issues with a view to next-generation speech-to-speech translation.En Japón se han llevado a cabo muchas actividades de investigación acerca de la traducción automática del habla. Este artículo pretende ofrecer una visión general de dichas actividades y presentar las que se han realizado más recientemente. El sistema S2ST está formado básicamente por tres módulos: el reconocimiento automático del habla continua y de amplios vocabularios (Automatic Speech Recognition, ASR), la traducción automática de textos (Machine translation, MT) y la conversión de texto a voz (Text-to-Speech Synthesis, TTS). Todos los módulos deben ser plurilingües, por lo cual se requieren discursos y corpus multilingües para los modelos de formación. El rendimiento del sistema S2ST mejora considerablemente por medio de un aprendizaje profundo y grandes corpus formativos. Sin embargo, todavía hace falta tratar diversos aspectos, com la simultaneidad, la paralingüística, la dependencia del contexto y de la situación, la intención y la dependencia cultural. Por todo ello, repasaremos las actividades de investigación actuales y discutiremos varias cuestiones relacionadas con la traducción automática del habla de última generación.Al Japó s'han dut a terme moltes activitats de recerca sobre la traducció automàtica de la parla. Aquest article n'ofereix una visió general i presenta les activitats que s'han efectuat més recentment. El sistema S2ST es compon bàsicament de tres mòduls: el reconeixement automàtic de la parla contínua i de vocabularis extensos (Automatic Speech Recognition, ASR), la traducció automàtica de textos (Machine translation, MT) i la conversió de text a veu (Text-to-Speech Synthesis, TTS). Tots els mòduls han de ser plurilingües, per la qual cosa es requereixen discursos i corpus multilingües per als models de formació. El rendiment del sistema S2ST millora considerablement per mitjà d'un aprenentatge profund i de grans corpus formatius. Tanmateix, encara cal tractar diversos aspectes, com la simultaneïtat, la paralingüística, la dependència del context i de la situació, la intenció i la dependència cultural. Així, farem un repàs a les activitats de recerca actuals i discutirem diverses qüestions relacionades amb la traducció automàtica de la parla d'última generació

Trialing project-based learning in a new EAP ESP course: A collaborative reflective practice of three college English teachers

Currently in many Chinese universities, the traditional College English course is facing the risk of being ‘marginalized’, replaced or even removed, and many hours previously allocated to the course are now being taken by EAP or ESP. At X University in northern China, a curriculum reform as such is taking place, as a result of which a new course has been created called ‘xue ke’ English. Despite the fact that ‘xue ke’ means subject literally, the course designer has made it clear that subject content is not the target, nor is the course the same as EAP or ESP. This curriculum initiative, while possibly having been justified with a rationale of some kind (e.g. to meet with changing social and/or academic needs of students and/or institutions), this is posing a great challenge for, as well as considerable pressure on, a number of College English teachers who have taught this single course for almost their entire teaching career. In such a context, three teachers formed a peer support group in Semester One this year, to work collaboratively co-tackling the challenge, and they chose Project-Based Learning (PBL) for the new course. This presentation will report on the implementation of this project, including the overall designing, operational procedure, and the teachers’ reflections. Based on discussion, pre-agreement was reached on the purpose and manner of collaboration as offering peer support for more effective teaching and learning and fulfilling and pleasant professional development. A WeChat group was set up as the chief platform for messaging, idea-sharing, and resource-exchanging. Physical meetings were supplementary, with sound agenda but flexible time, and venues. Mosoteach cloud class (lan mo yun ban ke) was established as a tool for virtual learning, employed both in and after class. Discussions were held at the beginning of the semester which determined only brief outlines for PBL implementation and allowed space for everyone to autonomously explore in their own way. Constant further discussions followed, which generated a great deal of opportunities for peer learning and lesson plan modifications. A reflective journal, in a greater or lesser detailed manner, was also kept by each teacher to record the journey of the collaboration. At the end of the semester, it was commonly recognized that, although challenges existed, the collaboration was overall a success and they were all willing to continue with it and endeavor to refine it to be a more professional and productive approach

A Comparative Study on Japanese and Indonesian Elementary School

Pendidikan dasar secara umum terbagi dalam dua lembaga pendidikan yakni sekolah dasar dan sekolah menengah pertama. Proses pendidikan yang berlangsung di sekolah dasar merupakan landasan yang sangat penting untuk proses pendidikan di lembaga selanjutnya. Tujuan yang sangat penting dari proses pendidikan di sekolah dasar adalah pengembangan otot, emosi, sosialisasi, pengenalan lingkungan,dan aspek kebahasaan. Kemudian, mulai kelas empat di sekolah dasar ,para siswa mendalami ilmu pengtahuan secara intensif. Sekolah dsar di Jepang menekankan pada pendidikan mental sehingga anak bisa lebih ulet, tabah, toleran, dan optimis dalam hidup bermasyarakat. Pendidikan moral, olah raga, ketrampilan, dan pendidikan kesejahteraan keluarga sangat penting dalampengembangan kepribadian siswa. Pelajaran matematika dan ilmu pengetahuan banyak diajarkan dengan pendekatan kontekstual di sekolah dasar di Indonesia dan Jepang. Kedua Negara juga mulai memberikan pelajaran Bahasa Inggris kepada siswa sekolah dasar untuk mengenalkan secara dini bahasa dab kebudayan bangsa lain serta mempersiapkan mereka dalam persaingan global. Melakukan studi banding terhadap kondisi pendidikan Negara lain membuat kita memperoleh informasi yang benar terhadap pencapaian kita dan Negara lain di bidang pendidikan serta membuat langkah-langkah perbaikan berdasarkan data yang terpercaya bukan kabar burung yang tidak jelas

Own-language use in language teaching and learning: state of the art

Until recently, the assumption of the language-teaching literature has been that new languages are best taught and learned monolingually, without the use of the students’ own language(s). In recent years, however, this monolingual assumption has been increasingly questioned, and a re-evaluation of teaching that relates the language being taught to the students’ own language has begun. This article surveys the developing English language literature on the role of students’ own language(s) in the language classroom. After clarifying key terms, the paper charts the continuing widespread use of students’ own languages in classrooms around the world and the contemporary academic and societal trends which have led to a revival of support for this. It then explores key arguments which underpin this revival, and reviews a range of empirical studies which examine the extent and functions of own-language use within language classrooms. Next, the article examines the support for own-language use that a range of theoretical frameworks provide, including psycholinguistic and cognitive approaches, general learning theory and sociocultural approaches. Having explored the notion of ‘optimal’ in-class own-language use, the article then reviews research into teachers’ and students’ attitudes towards own-language use. It concludes by examining how a bilingual approach to language teaching and learning might be implemented in practice

Towards a Universal Wordnet by Learning from Combined Evidenc

Lexical databases are invaluable sources of knowledge about words and their meanings, with numerous applications in areas like NLP, IR, and AI. We propose a methodology for the automatic construction of a large-scale multilingual lexical database where words of many languages are hierarchically organized in terms of their meanings and their semantic relations to other words. This resource is bootstrapped from WordNet, a well-known English-language resource. Our approach extends WordNet with around 1.5 million meaning links for 800,000 words in over 200 languages, drawing on evidence extracted from a variety of resources including existing (monolingual) wordnets, (mostly bilingual) translation dictionaries, and parallel corpora. Graph-based scoring functions and statistical learning techniques are used to iteratively integrate this information and build an output graph. Experiments show that this wordnet has a high level of precision and coverage, and that it can be useful in applied tasks such as cross-lingual text classification