Towards Civility: A Workshop to Evaluate and Inspire Collection and Analysis of Data on Harassing Behaviors in Engineering and Engineering Technology

扩大参与和留住来自工程专业和STEM劳动力专业的不同人口统计数据的学生是国家的一个高度优先事项。然而，骚扰行为阻碍了这一目标。2018年，美国国家科学、工程和医学院（NASEM）发布了一份名为《女性的性骚扰：气候、文化和学术科学、工程和医学的后果》的报告。这份报告将最普遍的性骚扰行为概念化为性别骚扰，描述为“传达敌意、物化、排斥或二等地位的语言和非语言行为”。有证据表明，学术界在性骚扰行为的普遍程度方面仅次于军队。证据还表明，在学术界，工程学仅次于医学。不幸的是，已发表的关于发生频率的特定工程数据很少，从有限的已发表数据中可以明显看出，知识库中存在大量空白。特别令人关切的是，按人口统计分类的数据（例如，种族/民族，性别认同，性取向，交叉性），缺乏按工程学科分类的数据（例如，航空航天工程与化学工程），以及缺乏关于在体验式学习机会期间骚扰行为的流行率和性质的数据（例如，合作社、实习、研究经验）。最终，该项目的结果将为未来的研究奠定基础，并为干预措施的设计和实施提供信息。 该项目将汇集高等教育机构（IHE）的代表，努力确定高等教育机构已经存在并可以公布的数据，确定补充数据的优先事项，并参与协调的国家努力收集和分析数据。讲习班将以虚拟方式进行，为期几个月，以便让与会者在两次会议之间有时间参与行动分配。研讨会将采用一种参与式行动研究方法，称为小组级评估（GLA），以解决研究问题：（1）谁有兴趣进行这项工作（即，谁是我们的研讨会参与者，他们认为谁是合作者和其他利益相关者）？(2)研讨会参与者（自认为对该主题感兴趣）已经知道什么，他们想知道什么，关于现有数据（在他们的机构内外）和工程领域的前景？(3)研究人员需要哪些方法工具和其他技能和资源来研究他们所在机构的骚扰行为？使用GLA将强调制定由广泛的利益攸关方群体确定的行动计划;让研讨会参与者参与有关数据、优先事项和行动计划的决策过程;并积极模拟研讨会参与者在其数据收集和分析工作中可以使用的方法。除了已发表的论文集外，本次研讨会的成果还将包括数据收集和分析、与IHE利益相关者的对话以及招聘等主题的几个工具包。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。

Broadening participation and retaining students from diverse demographics in engineering majors and professionals in the STEM workforce is a high priority for the nation. However, harassing behaviors impede this goal. In 2018, the National Academies of Sciences, Engineering, and Medicine (NASEM) published the report, Sexual Harassment of Women: Climate, Culture, and Consequences in Academic Sciences, Engineering, and Medicine. This report conceptualizes the most prevalent sexually harassing behaviors as gender harassment, described as “verbal and nonverbal behaviors that convey hostility, objectification, exclusion, or second-class status”. Evidence indicates that academia is second only to the military in prevalence of sexually harassing behaviors. Evidence also indicates that, within academia, engineering is second only to medicine. Unfortunately, published engineering-specific data about frequency of occurrences are scarce and it is evident from this limited published data that there are substantial gaps in the knowledge base. Of particular concern is the disproportionate lack of data disaggregated by demographics (e.g., race/ethnicity, gender identification, sexual orientation, intersectionality), the lack of data disaggregated by discipline within engineering (e.g., aerospace engineering vs. chemical engineering), and the lack of data about the prevalence and nature of harassing behaviors during experiential learning opportunities (e.g., co-ops, internships, research experiences). Ultimately, the results of this project will lay the foundation for future research and inform the design and implementation of interventions. This project will bring together representatives of Institutions of Higher Education (IHE) in an effort to determine what data already exists at IHEs and could be published, to identify priorities for additional data, and to engage in a coordinated national effort to collect and analyze data. The workshop will occur virtually, over several months to give participants time in between sessions to engage in action assignments. The workshop will employ a participatory action research method, known as Group-Level Assessment (GLA), to address the research questions: (1) Who is interested in conducting this work (i.e., who are our workshop participants and who do they identify as collaborators and other stakeholders)? (2) What do workshop participants (self-identified as interested in this topic) already know, and what do they want to know, about existing data (inside and outside their institutions) and the landscape in engineering? (3) What methodological tools and other skills and resources do researchers need for conducting research on harassing behaviors at their institutions? The use of GLA will emphasize the development of action plans determined by a broad group of stakeholders; engage workshop participants in the process of making decisions about data, priorities, and action plans; and actively model a method that could be used by workshop participants in their own data collection and analysis efforts. In addition to published proceedings, outcomes of this workshop will include several toolkits on topics such as data collection and analysis, conversations with stakeholders at IHEs, and recruiting.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.