What's Happened with American Adult Understanding of Science Knowledge and Process: 1979-2014

美国成年人对科学知识和过程的理解发生了什么？1979-2016 随着时间的推移，我们对美国公众对科学和技术的理解了解多少？在工业和后工业民主国家，公民经常参与科学技术决策和实施。公民科学和技术素养，或公众理解，在成年公众中被默认为有助于创造一种气氛，促进明智的政策讨论，支持“科学企业”，并提高生活质量。总的来说，公众可能会抵制一些发展，例如，转基因食品，而采用其他，例如，互联网 此外，许多利益相关者-家长、教育工作者、立法者和雇主-都担心美国在科学教育方面“落后”，或未能培养足够数量的科学技术专业人员。鉴于人们对科学和技术的参与和反应，必须定期评估公众的科技知识及其对如何开展科学工作的理解。检查成人的科技知识和态度可以帮助教育工作者规划更有效的课程;它也可能有助于鼓励科学和技术领域的更大多样性。例如，比较工程师和科学家的刻板印象可能会让我们更深入地了解年轻人选择更多的应用与更多的理论研究职业。研究公众成年人如何看待科学家之间的一致性（例如，关于全球变暖）可能会建议如何沟通科学中有争议或没有争议的内容，帮助公民更准确地评估来自不同专家的信息。该项目通过研究性别、种族和教育维度如何与公民科学和技术素养随着时间的推移和世代的变化相关联来解决其中的几个问题。该项目分析了1979年至2016年美国国家科学基金会公众对科学和技术的理解调查（NSF调查）的数据。NSF调查研究了美国成年人的重复横断面概率调查。最初（1981年至2001年），大多数是随机数字拨号电话采访。最近（2006-2016年），综合社会调查（GSS）进行了面对面访谈。问题涉及科学知识和态度、理解科学探究、信息技术的获取、对科学家和工程师的陈规定型观念、对科学家活动的看法以及广泛的人口统计信息，特别是关于教育的信息。一些分析集中在基本的科技知识如何链接到科学探究的理解，以及两者如何与背景变量，并随着时间和世代的变化。例如，目前对老年人使用信息技术的一些分析混淆了年龄、时间段和世代，因此可能会导致那些想要“精通技术”的工人的雇主之间的隐性年龄歧视。这些分析需要更新1979-2006年的数据档案，将其与2008年，2010年，2012年，2014年和2016年的新GSS调查合并。第二个数据库包含关于成人对科学进程的理解的深入项目，从而可以与青年对国家教育进展评估的答复进行比较。 本研究的统计分析包括回归分析、变异数分析、验证性因素分析、结构方程模型、多重分类分析、对数线性模型，包括中介变量和调节变量。成果通过专业渠道传播，并在报告中更容易为一般受众所了解。

What's Happened with American Adult Understanding of Science Knowledge and Process? 1979-2016 What do we know about American's public understanding of science and technology over time? In industrial and post-industrial democracies, citizens often participate in science and technology (S&T) decision-making and implementation. Civic science and technology literacy, or public understanding, among the adult general public is tacitly understood to help create a climate that facilitates intelligent policy discussions, supports the "science enterprise," and enhances quality of life. Overall, the general public may resist some developments, e.g., genetically modified foods, while adopting others, e.g., the Internet. In addition, many stakeholders--parents, educators, legislators, and employers--are concerned that the United States is "falling behind" in science education or failing to develop sufficient numbers of S&T professionals. Given engagement in and reaction to science and technology, it is imperative to periodically gauge S&T knowledge among the general public, as well as their understanding of how science is conducted. Examining S&T knowledge and attitudes among adults can help educators plan more effective coursework; it also may help encourage greater diversity in science and technology fields. For example, comparing engineer and scientist stereotypes may provide insight into young adult choices of more applied versus more theoretical research careers. Examining how general public adults perceive concordance among scientists (e.g., about global warming) may suggest how to communicate what is--or is not--controversial in science, helping citizens to evaluate more accurately information from diverse experts. The project addresses several of these concerns, by examining how gender, ethnicity, and dimensions of education, relate to civic science and technology literacy over time and by generation.The project analyzes data from The National Science Foundation Surveys of Public Understanding of Science and Technology (The NSF Surveys), 1979 -2016. The NSF Surveys examine repeated cross-sectional probability surveys of American adults. Initially (1981-2001) most were random digit dial telephone interviews. More recently (2006-2016) the General Social Survey (GSS) has conducted in-person interviews. Questions address science knowledge and attitudes, understanding science inquiry, information technology access, stereotypes about scientists and engineers, perceptions of scientists' activities, and extensive demographic information, especially about education. Several analyses center on how basic S&T knowledge links to science inquiry understanding, and how both relate to background variables, and changes over time and by generation. For example, some current analyses of older adults' use of information technology confound age, time period, and generation, and thus may contribute to covert age discrimination among employers who want "tech-savvy" workers. Such analyses require updating a data archive spanning 1979-2006, amalgamating it with newer GSS surveys from 2008, 2010, 2012, 2014, and 2016. A second database incorporates in-depth items on adult understanding of science processes, making possible comparisons with responses from youth on the National Assessment of Educational Progress. Statistical analyses on this project include regression, analysis of variance, Confirmatory Factor Analysis, structural equation models, Multiple Classification Analysis, and loglinear models, including mediators and moderators. Results are disseminated through professional channels and also in reports more accessible to general audiences.