Herbert Lange
Computer Science and Engineering, University of Gothenburg and Chalmers University of Technology, Sweden
Peter Ljunglöf
Computer Science and Engineering, University of Gothenburg and Chalmers University of Technology, Sweden
Ladda ner artikel
Ingår i: Proceedings of the 7th Workshop on NLP for Computer Assisted Language Learning (NLP4CALL 2018) at SLTC, Stockholm, 7th November 2018
Linköping Electronic Conference Proceedings 152:5, s. 41-46
NEALT Proceedings Series 36:5, p. 41-46
Publicerad: 2018-11-02
ISBN: 978-91-7685-173-9
ISSN: 1650-3686 (tryckt), 1650-3740 (online)
We present a language learning application that relies on grammars to model the learning outcome. Based on this concept we can provide a powerful framework for language learning exercises with an intuitive user interface and a high reliability. Currently the application aims to augment existing language classes and support students by improving the learner attitude and the general learning outcome. Extensions beyond that scope are promising and likely to be added in the future.
Trude Heift. 2001. Intelligent Language Tutoring Systems for Grammar Practice. Zeitschrift für Interkulturellen Fremdsprachenunterricht, 6(2).
Aravind K. Joshi and Yves Schabes. 1997. Treeadjoining grammars. In Grzegorz Rozenberg and Arto Salomaa, editors, Handbook of Formal Languages. Vol 3: Beyond Words, chapter 2, pages 69–123. Springer-Verlag.
Tobias Kuhn. 2014. A Survey and Classification of Controlled Natural Languages. Computational Linguistics, 40(1):121–170.
Herbert Lange and Peter Ljungl¨of. 2018a. MULLE: A Grammar-based Latin Language Learning Tool to Supplement the Classroom Setting. In Proceedings of the 5th Workshop on Natural Language Processing Techniques for Educational Applications (NLPTEA ’18), pages 108–112, Melbourn. Australia. Association for Computational Linguistics.
Herbert Lange and Peter Ljunglöf. 2018b. Putting Control into Language Learning. In SIGCNL 2018, Maynooth, Ireland.
Peter Ljunglöf. 2011. Editing Syntax Trees on the Surface. In Nodalida’11: 18th Nordic Conference of Computational Linguistics, Riga, Latvia.
J.M. O’Toole and R.A.R. King. 2011. The deceptive mean: Conceptual scoring of cloze entries differentially advantages more able readers. Language Testing, 28(1):127–144.
Laura Perez-Beltrachini, Claire Gardent, and German Kruszewski. 2012. Generating grammar exercises. In Proceedings of the Seventh Workshop on Building Educational Applications Using NLP, NAACL HLT ’12, pages 147–156, Stroudsburg, PA, USA. Association for Computational Linguistics.
Aarne Ranta. 2009. The GF Resource Grammar Library. Linguistic Issues in Language Technology, 2(2).
Aarne Ranta. 2011. Grammatical Framework: Programming with Multilingual Grammars. CSLI Publications, Stanford.
Ian M. Richmond. 1994. Doing It Backwards: Using Translation Software To Teach Target- Language Grammaticality. Computer Assisted Language Learning, 7(1):65–78.
Penelope Sweetser and Peta Wyeth. 2005. Game-Flow: AModel for Evaluating Player Enjoyment in Games. Computers in Entertainment (CIE), 3(3):3–3.
Wilson L. Taylor. 1953. ”cloze procedure”: A new tool for measuring readability. Journalism Quarterly, 30(4):415–433.
