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Semantic Boggle: A Game for Vocabulary Acquisition

  • Irina Toma
  • Cristina-Elena Alexandru
  • Mihai Dascalu
  • Philippe Dessus
  • Stefan Trausan-Matu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10474)

Abstract

Learning a new language is a difficult endeavor, the main encountered problem being vocabulary acquisition. The learning process can be improved through visual representations of coherent contexts, best represented in serious games. The game described in this paper, Semantic Boggle, is a serious game that exercises vocabulary. It is based on the traditional word-guessing game, but it brings educational value by identifying semantically-related words. The words are found using the ReaderBench framework and are placed in the game grid using a greedy algorithm. The assigned score is computed as the semantic similarity value multiplied by the normalized length of the seed. Our preliminary validation consisted of 20 users, who emphasized its interest and playability.

Keywords

Serious games Vocabulary acquisition Semantic games Word-guessing Boggle Language learning 

Notes

Acknowledgment

This work was partially funded by the FP7 2008-212578 LTfLL project, by the 644187 EC H2020 Realising an Applied Gaming Eco-system (RAGE) project and by University Politehnica of Bucharest through the Excellence Research Grants Program UPB–GEX 12/26.09.2016. We want also to thank Mathieu Loiseau for all his helpful insights.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Irina Toma
    • 1
  • Cristina-Elena Alexandru
    • 1
  • Mihai Dascalu
    • 1
    • 2
  • Philippe Dessus
    • 3
  • Stefan Trausan-Matu
    • 1
    • 2
  1. 1.Faculty of Automatic Control and ComputersUniversity “Politehnica” of BucharestBucharestRomania
  2. 2.Academy of Romanian ScientistsBucharestRomania
  3. 3.Laboratoire des Sciences de l’ÉducationUniv. Grenoble AlpesGrenobleFrance

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