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Vocabulary Learning Based on Learner-Generated Pictorial Annotations: Using Big Data as Learning Resources

机译:基于学习者生成的图形注释的词汇学习:使用大数据作为学习资源

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摘要

This research discusses the potential of using big data for vocabulary learning from the perspective of learner-generated pictorial annotations. Pictorial annotations lead to effective vocabulary learning, the creation of which is however challenging and time-consuming. As user-generated annotations promote active learning, and in the big data era, data sources in social media platforms are not only huge but also user-generated, the proposal of using social media data to establish a natural and semantic connection between pictorial annotations and words seems feasible. This research investigated learners’ perceptions of creating pictorial annotations using Google images and social media images, learners’ evaluation of the learner-generated pictorial annotations, and the effectiveness of Google pictorial annotations and social media pictorial annotations in promoting vocabulary learning. A total of 153 undergraduates participated in the research, some of whom created pictorial annotations using Google and social media data, some evaluated the annotations, and some learned the target words with the annotations. The results indicated positive attitudes towards using Google and social media data sets as resources for language enhancement, as well as significant effectiveness of learner-generated Google pictorial annotations and social media pictorial annotations in promoting both initial learning and retention of target words. Specifically, we found that (i) Google images were more appropriate and reliable for pictorial annotations creation, and therefore they achieved better outcomes when learning with the annotations created with Google images than images from social media, and (ii) the participants who created word lists that integrate pictorial annotations were likely to engage in active learning when they selected and organized the verbal and visual information of target words by themselves and actively integrated such information with their prior knowledge.
机译:本研究讨论了从学习者生成的图形注释的角度使用词汇学习的大数据的潜力。图案注释导致有效的词汇学习,创造它的创造挑战和耗时。随着用户生成的注释促进主动学习,在大数据时代,社交媒体平台中的数据源不仅是巨大的还是用户生成的,建议使用社交媒体数据来建立图案注释之间的自然和语义连接单词似乎是可行的。这项研究调查了学习者对使用Google Images和社交媒体图像创建画报注释的看法,学习者对学习者生成的画报注释的评估以及谷歌画报注释和社交媒体图示的有效性在推广词汇学习中。共有153名本科生参与了该研究,其中一些人创建了使用谷歌和社交媒体数据的画报注释,一些评估了注释,并有人通过注释学习了目标单词。结果表明,朝向使用谷歌和社交媒体数据集作为语言增强的资源的积极态度,以及学习者生成的Google Pictorial注释和社交媒体图示注解在推广初始学习和保留目标词时的重要效力。具体来说,我们发现(i)Google Images更适合和可靠地为图像注释创建,因此在使用Google Images创建的注释时,他们在与来自社交媒体的图像创建的注释,以及(ii)创建字的参与者列出集成了图形注释的列表可能会在他们自己选择和组织目标单词的口头和视觉信息时从事主动学习,并与他们的先验知识一起积极整合这些信息。

著录项

  • 作者

    Di Zou; Haoran Xie;

  • 作者单位
  • 年度 2021
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  • 原文格式 PDF
  • 正文语种 eng
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