Semantic Boggle: A Game for Vocabulary Acquisition

被引：0

作者：

Toma, Irina ^{[1
]}

Alexandru, Cristina-Elena ^{[1
]}

Dascalu, Mihai ^{[1
,2
]}

Dessus, Philippe ^{[3
]}

Trausan-Matu, Stefan ^{[1
,2
]}

机构：

[1] Univ Politehn Bucuresti, Fac Automat Control & Comp, 313 Splaiul Independentei, Bucharest 60042, Romania

[2] Acad Romanian Scientists, Splaiul Independentei 54, Bucharest 050094, Romania

[3] Univ Grenoble Alpes, Lab Sci Educ, F-38000 Grenoble, France

来源：

DATA DRIVEN APPROACHES IN DIGITAL EDUCATION | 2017年 / 10474卷

基金：

欧盟地平线“2020”;

关键词：

Serious games; Vocabulary acquisition; Semantic games; Wordguessing; Boggle; Language learning;

D O I：

10.1007/978-3-319-66610-5_73

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

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.

引用

页码：606 / 609

页数：4

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