Developing a Scalable Measure of Inclusive STEM Teaching Practices for Diverse Institutions

最近，关于扩大STEM参与的心理学研究已经从以学生为中心的干预（例如，从针对学生的归属感或成长心态干预措施）到针对具体情况的干预措施（针对教师，以创造归属感或成长文化）。然而，缺乏评估这些方案引起的教师实践变化的工具。受欢迎的自我报告的方法，教师可能会偏见，由于错误的回忆或社会期望的偏见，而更密集的观察方法是繁琐的，难以持续。此外，现有措施往往是在一类机构内制定的，可能没有充分强调传统黑人学院和大学以及为西班牙裔服务的机构的教员的包容性做法。这些限制减缓了发现可以扩大STEM参与的项目的进展。本提案旨在开发一个可扩展的，值得信赖的系统的教师和学生的报告，可以是骨干研究评估下一代的背景为重点的干预措施。该项目将开发包容性中学后STEM教学实践的新措施，为少数群体成员创造归属感和动力体验。包容性的做法的措施将开发使用最佳的调查设计，包括半结构化的访谈和认知预测试与教师和学生共同开发。这些措施将在三所大学同时制定和完善：一所以白人为主的大学，一所以西班牙裔为主的大学和一所历史上的黑人大学。这种跨站点验证将确保措施对学生经验的变化敏感，并增加其潜在的应用。这些措施在捕捉实践的频率和质量的敏感性将使用第三方观察，重复的学生报告调查和课程完成结果进行验证。一种机器学习算法，贝叶斯加性回归树（BART），将告知最佳实践项目数量的选择，最大限度地减少受访者的负担，同时最大限度地提高预测。由此产生的措施将被广泛传播，以释放科学家和从业者的创造潜力，通过让他们了解什么是有效的，为什么。这个项目是由NSF的EHR核心研究（ECR）计划支持。ECR计划强调基础STEM教育研究，产生该领域的基础知识。投资是在关键领域是必不可少的，广泛的和持久的：干学习和干学习环境，扩大参与干，干劳动力发展。该计划支持积累强有力的证据，为理解、建立理论解释、提出干预和创新建议以应对教育中持续存在的挑战提供信息。该奖项反映了NSF的法定使命，并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，被认为值得支持。

Recently, psychological research on broadening participation in STEM has shifted from student-focused interventions (e.g., belonging or growth mindset interventions given to students) to context-focused interventions (aimed at instructors to create cultures of belonging or growth). Tools for evaluating the changes in instructors’ practices induced by these programs have been lacking, however. Popular self-report methods for instructors can be biased due to faulty recall or social desirability bias, while more intensive observational methods are cumbersome and difficult to sustain. In addition, existing measures tend to be developed within one type of institution and may underemphasize inclusive practices from instructors at historically Black colleges and universities and Hispanic-serving institutions. These limitations have slowed progress toward the discovery of programs that could broaden participation in STEM. The present proposal seeks to develop a scalable, trustworthy system of instructor- and student-reports that could be the backbone for research evaluating the next generation of context-focused interventions. This project will develop novel measures of inclusive postsecondary STEM teaching practices that create an experience of belonging and motivation for members of minoritized groups. Measures of inclusive practices will be developed using optimal survey design, including semi-structured interviews and cognitive pretesting co-developed with both instructors and students. The measures will be simultaneously developed and refined across three universities: at a predominantly white-serving institution, a predominantly Hispanic-serving institution, and a historically-Black university. This cross-site validation will ensure that measures are sensitive to the variability in students’ experiences and increase their potential application. The sensitivity of these measures in capturing the frequency and quality of practices will be validated using third-party observations, repeated student-report surveys, and course completion outcomes. A machine-learning algorithm, Bayesian Additive Regression Trees (BART), will inform the choice of the optimal number of practices items that minimize respondent burden while maximizing prediction. The resulting measures will be widely disseminated to unlock the creative potential of scientists and practitioners developing inclusive practices by allowing them to learn what is working, and why.This project is supported by NSF's EHR Core Research (ECR) program. The ECR program emphasizes fundamental STEM education research that generates foundational knowledge in the field. Investments are made in critical areas that are essential, broad and enduring: STEM learning and STEM learning environments, broadening participation in STEM, and STEM workforce development. The program supports the accumulation of robust evidence to inform efforts to understand, build theory to explain, and suggest intervention and innovations to address persistent challenges in education.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.