Addressing Ubiquitous STEM Gender Performance Differences

这是一个广泛的项目，结合了一些NSF优先事项和早期NSF支持的项目，包括“写作学习”，WIDER（机构转型），INCLUDES（扩大参与），网络学习和大数据分析。使用大数据分析，已经定量确定，在10所主要公立研究型大学参加STEM入门讲座课程的女学生显示出刻板印象威胁的证据，这使她们的课程成绩降低了5%至10%，并阻止一些人继续STEM专业。该项目的目标是继续完善和采用一个数字辅导/治疗工具，该工具已经过试点阶段的测试，提供多达三种类型的治疗，以抵消陈规定型观念的威胁。这个工具有可能为每个学生定制。它是在早期NSF/ DUE赠款的早期支持下开发的。这一工具将使用一个在NSF/IUSE赠款下开发的以写促学工具。该写作工具正在构建一个全面的写作系统，将同行评议工具与自然语言处理工具包相结合，旨在提供有关学生对数字辅导工具的反应的可操作信息。预计该项目将对STEM女学生产生重大的直接影响，并有很好的前景鼓励更多的女学生继续在STEM作为他们的主要大学专业。如果该工具被证明能有效消除STEM课程中的性别表现差异，它很可能会被越来越多的其他研究型大学采用，从而扩大其影响。该项目本身将与5，000名不同的本科女性进行随机治疗设计，以测试基本治疗的疗效，并测试每个学生个性化治疗的改善疗效。由于与学生的所有互动都将通过数字指导/治疗工具框架进行，因此该项目将完全控制每个学生的经历，沿着一份全面的“治疗记录”，记录每个学生在系统中遇到和做了什么，包括他们在回应干预提示时所做的写作。控制和记录每个个体的个性化治疗的能力允许通过随机试验评估治疗。例如，这种方法一直是数字健康指导中顺序多分配随机试验发展的关键。

This is a wide reaching project that combines strands of a number of NSF priorities and earlier NSF-supported projects, including "Writing to Learn," WIDER (institutional transformation), INCLUDES (broadening participation), Cyber learning, and Big Data Analytics. Using big data analytics, it has been quantitatively established that female students taking introductory STEM lecture courses at 10 major public research universities show evidence of stereotype threat, which lowers their course performance by 5% to 10% and discourages some from continuing as STEM majors. The goal of the project is to continue to refine and employ a digital mentoring/ treatment tool that has undergone pilot stage testing to deliver up to three types of treatments to countervail the presence of stereotype threat. This tool has the potential to be customized for each student. It was developed with early stage support from an earlier NSF/ DUE grant. This tool will use a writing-to-learn tool being developed under an NSF/IUSE grant. The writing tool is building a comprehensive writing system, combining peer review tools with a natural language processing toolkit designed to provide actionable information about student responses to the digital mentoring tool. This project is expected to have a substantial direct impact on female STEM students and has good prospects for encouraging more of them to remain in STEM as their primary college major. If the tool proves to be effective in eliminating gender performance differences in STEM courses, it is likely to be employed in a growing number of other research universities, thereby multiplying its impact. The project itself will work with 5,000 distinct undergraduate women in a randomized treatment design to test the efficacy of basic treatment and to test the improved efficacy of individualizing the treatment for each student. Because all of the interactions with students will take place through the digital mentoring/ treatment tool framework, the project will have complete control over what each student experiences, along with a comprehensive "treatment record" of what each student encountered and did within the system, including the writing they did in response to the intervention prompts. The ability to control and record personalized treatment for every individual allows the treatment to be assessed through randomized trials. This approach has been the key to the development of sequential multiple assignment randomized trials in digital health coaching, for example.