Developing CALL for heritage languages: The 7 Keys of the Dragon

[EN] In this article we present an interactive extensible software, The 7 Keys of the Dragon, for the teaching/learning of Albanian and Russian to students that attend primary and secondary education in Greece with the respective languages as their heritage languages. We address the key challenges we encountered during the conceptualization phase of the project development and the specific design choices we implemented in order to accommodate them. Drawing on recent research on the role of Computer-Assisted Language Learning (CALL) applications for young bilingual populations, we aimed at creating a user friendly environment with a clear pedagogical orientation. Furthermore, given that games in language learning are associated with intrinsic motivation and meaningful exposure to the target language, we have integrated a fairy-tale background narrative, a game-inspired reward system, and two cartoon-like assistant characters to stimulate the user’s involvement in the learning tasks. Five chapters for each target language were created, each comprising a text, a variety of scaffolding material and quizzes. The software is designed to provide real-time automatic correction of quizzes and allow for easy expansion with additional quizzes and texts. A separate application for teachers facilitates essay correction and commenting on the students’ language learning progress and achievements.We are grateful to Amalia Rodou-Gorou and Tania Zouravliova for creating the language materials, to Nestoras Pelesoglou for the graphic design, and to Prof. dr. Ioannis Spantidakis for providing guidance in the pedagogical design of the e-learning environment. This research was supported by the programme “Education of Immigrant and Repatriate Students” (Action 5, Deliverable 5.2.3) funded by the European Social Fund, National Strategic Reference Framework (NSRF) 2007-2014 and the Ministry of Education, Lifelong Learning and Religious Affairs of the Hellenic Republic. The usual disclaimers apply.Revithiadou, A.; Kourtis-Kazoullis, V.; Soukalopoulou, M.; Konstantoudakis, K.; Zarras, C. (2015). Developing CALL for heritage languages: The 7 Keys of the Dragon. The EuroCALL Review. 23(2):38-57. doi:10.4995/eurocall.2015.4667.SWORD385723

Computational morphology and Bantu language learning:an implementation for Runyakitara

Computationele morfologie speelt een belangrijke rol in hedendaags computer ondersteund taalleren (CALL), in het bijzonder in het uitbreiden van de woordenschat, de verwerving van de morfologie, lexicale toegang en het verbeteren van de leesvaardigheid. Echter, tot nu toe zijn alleen talen onderzocht die goed gedocumenteerd en wijdverbreid zijn en die veelvuldig onderwezen worden, zoals het Engels, Frans, Duits, Spaans en Japans. Deze dissertatie richt zich op computationele morfologie, toegepast op taalverwerving, in het bijzonder in relatie tot de Runyakitara-tak van de Bantutalen. Zoals andere Batutalen bezit het Runyakitara een opvallend complexe morfologie: een uitdaging voor taalleerders. Traditionele wijzen van taaltraining, met goed opgeleide docenten, is onhaalbaar vanwege een gebrek aan hoogopgeleide docenten in het Runyakitara en de hoge kosten die dit met zich meebrengt. In dit proefschrift hebben een analysesysteem voor de Runyakitara talen ontworpen en geïmplementeerd. Vervolgens hebben we dit systeem op een nieuwe wijze in computerondersteund taalleren ingezet, via oefeningen met inflectie en syntaxis van het Runyakitara.

Locative enclitics in Ruruuli-Lunyala, Runyankore-Rukiga and Luganda: Form and functions

In this article, we describe the form and functions of locative enclitics in Ruruuli-Lunyala, Runyankore-Rukiga and Luganda. We demonstrate that although locative enclitics play the role of locative references, there are other non-locative functions which have not yet been reported in these three languages. The article pursues two objectives: (1) To describe the form of locative enclitics in the three languages; and (2) to describe the locative and non-locative functions of enclitics. Data for Luganda and Runyankore-Rukiga were collected using interviews and focus group discussions. For Ruruuli-Lunyala, examples were drawn from a spoken corpus of Ruruuli-Lunyala, a Ruruuli-Lunyala dictionary and elicitations from two native speakers. The findings show that locative enclitics in Ruruuli-Lunyala, Runyankore-Rukiga and Luganda play the role of locative reference in addition to non-locative functions. The non-locative functions attested in the three languages include partitive, politeness, comparative, adverbial, tense and aspect. Some encliticised words have become lexicalised, while others are used in idiomatic expressions

Computer-Assisted Language Learning (CALL) in support of (re-)learning native languages:The case of Runyakitara.

This study presents the results from a computer-assisted language learning (CALL) system of Runyakitara (RU_CALL). The major objective was to provide an electronic language learning environment that can enable learners with mother tongue deficiencies to enhance their knowledge of grammar and acquire writing skills in Runyakitara. The system currently focuses on nouns and employs natural language processing in order to generate a large base of exercise material without extensive tuning by teachers. Language learners used the system over 10 sessions and their improvements were charted. Besides this empirical evaluation, we also sought the opinions of Runyakitara experts about the system (as a judgmental evaluation). Results from the evaluation study indicate that RU_CALL has the ability to assess users’ knowledge of Runyakitara and to enhance grammar and writing skills in the language. This computational resource can be utilized by other interested learners of Runyakitara, and the idea can be extended to other indigenous languages with emigrant populations who wish to maintain their language skills

Building natural language processing tools for Runyakitara

Abstract This paper describes an endeavour to build natural language processing (NLP) tools for Runyakitara, a group of four closely related Bantu languages spoken in western Uganda. In contrast with major world languages such as English, for which corpora are comparatively abundant and NLP tools are well developed, computational linguistic resources for Runyakitara are in short supply. First therefore, we need to collect corpora for these languages, before we can proceed to the design of a spell-checker, grammar-checker and applications for computer-assisted language learning (CALL). We explain how we are collecting primary data for a new Runya Corpus of speech and writing, we outline the design of a morphological analyser, and discuss how we can use these new resources to build NLP tools. We are initially working with Runyankore–Rukiga, a closely-related pair of Runyakitara languages, and we frame our project in the context of NLP for low-resource languages, as well as CALL for the preservation of endangered languages. We put our project forward as a test case for the revitalization of endangered languages through education and technology.</jats:p