Takahashi Bruno, Tandoc Edson C
Michigan State University, USA
Nanyang Technological University, Singapore.
Public Underst Sci. 2016 Aug;25(6):674-90. doi: 10.1177/0963662515574986. Epub 2015 Mar 19.
Knowledge about science and technology has become increasingly important in this age of digital information overload. It is also becoming increasingly important to understand what contributes to scientific learning, including information sources and trust in those sources. In this study, we develop and test a multivariate model to explain scientific knowledge based on past theories on learning from the news from the fields of political communication, sociology, and media psychology. We focus on the impact of sources-by platform, such as television and online, and by expertise, such as scientists and the media-in understanding what predicts scientific knowledge. The results show that interest in science not only directly predicts knowledge but also has indirect effects on knowledge through its effects on Internet use, confidence in the press, and perception of scientists. In addition, distrust on the news sources is an important pathway to learning about science.
在这个数字信息过载的时代，关于科学技术的知识变得越来越重要。理解促成科学学习的因素，包括信息来源以及对这些来源的信任，也变得越来越重要。在本研究中，我们基于政治传播学、社会学和媒体心理学领域中关于从新闻中学习的过往理论，开发并测试了一个多变量模型来解释科学知识。我们聚焦于信息来源的影响——按平台划分，如电视和网络；按专业性划分，如科学家和媒体——以了解哪些因素能够预测科学知识。结果表明，对科学的兴趣不仅直接预测知识水平，还通过其对互联网使用、对新闻媒体的信任以及对科学家的认知的影响，对知识产生间接影响。此外，对新闻来源的不信任是了解科学的一条重要途径。
