A review of vocabulary learning applications: From the aspects of cognitive approaches, multimedia input, learning materials, and game elements

IF 2.5 4区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH Knowledge Management & E-Learning-An International Journal Pub Date : 2021-09-28 DOI:10.34105/j.kmel.2021.13.014
Fu Lee Wang
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引用次数: 5

Abstract

In recent years, mobile applications (apps) have been increasingly used and investigated as a vocabulary learning approach. Despite the extensive use of commercial English as a Foreign Language (EFL) vocabulary learning apps in China, there is a lack of a review of these apps for a systematic understanding of the components and usefulness of app-assisted vocabulary learning. To fill this knowledge gap, this study presents a systematic review of 15 EFL vocabulary learning apps that were most downloaded in China, focusing on how these apps help students develop word knowledge. The results of this study showed that most apps enabled students to access word knowledge through translating words into their native language. Notably, word knowledge was usually presented through text-plus-image and text-plus-image-plus-audio. Most of these mobile apps provided sentence examples as vocabulary learning materials. Many of these apps were integrated with game elements, especially in interactivity or feedback systems and reward systems. Based on the review results, we have provided three recommendations to vocabulary learning app developers concerning the use of video for the input of word knowledge, the efficiency of vocabulary learning, and the integration of more game elements.
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词汇学习应用综述:从认知方法、多媒体输入、学习材料和游戏元素等方面
近年来,移动应用程序作为一种词汇学习方法越来越多地被使用和研究。尽管商业英语作为外语(EFL)词汇学习应用程序在中国广泛使用,但缺乏对这些应用程序的审查,以系统地了解应用程序辅助词汇学习的组成部分和有用性。为了填补这一知识空白,本研究对中国下载量最大的15款英语词汇学习应用程序进行了系统回顾,重点研究了这些应用程序如何帮助学生发展单词知识。这项研究的结果表明,大多数应用程序都能让学生通过将单词翻译成母语来获取单词知识。值得注意的是,单词知识通常通过文本加图像和文本加图像加音频来呈现。这些移动应用程序中的大多数都提供了作为词汇学习材料的句子示例。其中许多应用程序都集成了游戏元素,尤其是在互动或反馈系统和奖励系统中。根据审查结果,我们向词汇学习应用程序开发人员提供了三个建议,涉及使用视频输入单词知识、词汇学习的效率以及整合更多游戏元素。
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来源期刊
CiteScore
4.70
自引率
33.30%
发文量
19
审稿时长
25 weeks
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