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A Mixed-methods Study of Non-text Social Media Content as a Window into African-American Youth STEM Identities

机译:非文本社交媒体内容作为非洲裔美国青年词根形式的混合方法研究

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Historically, researchers have observed that some African American youth suppress public expression of their interests in Science, Technology, Engineering and Math (STEM) topics. Prior research has attributed youth denial of STEM identities to their perceived social pressures. When researchers interview participants in STEM education experiences, we receive certain responses that help us to learn about STEM identities. When we look to social media content, which is sometimes shared publicly and voluntarily, we see a possible window into the perspectives and identities of African American youth and young adults that may help us learn about STEM identities in a new way. Through this window, we may observe social media content that reveals STEM identities and community involvement. Along with text, the social media content may include non-text paralinguistic elements such as emoji, hashtags, images, videoclips, and GIFs (graphics interchange format, typically animated) that may be overlooked in our common discourse analysis techniques; yet these elements could potentially inform our understanding of identity expression.
机译:从历史上看,研究人员已经观察到一些非洲裔美国青年抑制了他们对科学,技术,工程和数学(Stem)主题的兴趣的公开表达。先前的研究将青年拒绝对其所感知的社会压力否认茎身份。当研究人员采访茎教育经历的参与者时,我们会收到某些反应,帮助我们了解词干身份。当我们期待社交媒体内容时,有时和自愿共享,我们会看到可能的窗口进入非洲裔美国青年和年轻人的观点和身份,这可能有助于我们以一种新的方式学习词干身份。通过这个窗口,我们可以观察揭示词干身份和社区参与的社交媒体内容。除了文本之后,社交媒体内容可以包括非文本paralinguistic元素,例如Emoji,HASHTAG,图像,视频电视和GIF(图形交换格式,通常是动画),其在我们的共同话语分析技术中可能被忽视;然而,这些元素可能会通知我们对身份表达的理解。

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