Math Classrooms, Student Mindsets and STEM Pathways in High School

ECR项目强调基础STEM教育研究，这将产生该领域的基础知识。本研究将通过建立关于扩大代表性不足的少数群体（有色人种学生、年轻女性、来自低经济地位家庭的学生、残疾学生、英语学习者）参与STEM教育的理论，以及他们之间的交集，来增加基础知识。该研究将使用来自国家学习心态研究（NSLM）的数据，这是迄今为止最大的国家心理干预随机对照试验，该试验以全国公立高中的概率样本和城市地区学校的超额样本进行，包括来自83所学校的18,000多名学生。NSLM的目标是了解如何在STEM管道中保留代表性不足的学生。通过干预，学生们被教导成长型心态的概念（在学校的挣扎是学习的机会，并不意味着你缺乏智力），以及如何将这一概念应用到他们的功课中。调查评估了数学课堂上的成长心态气候。本研究将分析NSLM数据，以调查九年级数学课堂气氛对学生的影响。使用成长型思维模式共同帮助学生在高中早期成功完成高等数学和科学课程。该研究的四个主要目标包括：(1)编码参加NSLM的8至10年级学生的STEM课程学习模式，并描述少数群体在高级STEM课程中的代表性不足的程度；(2)测试具有较强成长心态气候的9年级数学课是否预测弱势群体学生在10年级STEM课程中的坚持率更高；(3)确定以成长为导向的教师实践，最好地创造成长心态氛围，提高STEM课程的持久性；(4)检验直接给予初中生成长心态干预对初中生STEM课程坚持性的影响是否依赖于初中生数学课堂氛围。对NSLM数据的分析将提供一个独特的机会来研究为什么九年级数学仍然是许多代表性不足的学生的看门人课程。这项研究将超越对字母成绩（即A、B等）的研究，而是关注课程学习模式（即是否在10年级学习代数II）。因此，它将推进关于减少在严格的数学途径中代表性不足的群体的流失的知识。定量技术和综合理论的结合使用将有助于实现未来STEM劳动力多样化的国家目标。区间的分析?它着眼于具有多重劣势的群体，比如既属于少数民族群体又正在学习英语的学生？对于深入了解这些群体所面临的不平等现象至关重要。为此，该研究将建立一个连接学生和教师记录的数据库，以验证对数学课堂气氛和数学教师实践的新颖、有效和可扩展的评估，这些评估有助于改善教学气氛，缩小高中轨迹中的成绩差距。最后，本研究将推进可扩展、低成本干预措施的知识，并确定此类干预措施最有效或最无效的教室。该奖项反映了美国国家科学基金会的法定使命，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。

The ECR program emphasizes fundamental STEM education research that will generate foundational knowledge in the field. This study will add to foundational knowledge by building theory about broadening participation of underrepresented minority groups (students of color, young women, students from low SES families, students with disabilities, English language learners), and intersections among them, in STEM education. The study will use data from the National Study of Learning Mindsets (NSLM), the largest (to date) national randomized-controlled trial of a psychological intervention conducted with a national probability sample of public high schools and an over-sample of urban district schools, including over 18,000 students from 83 schools. The goal of the NSLM was to gain insights about ways to retain underrepresented students in the STEM pipeline. Through the intervention students were taught the concept of a growth mindset (the idea that the struggles in school are opportunities to learn, and do not mean you lack intelligence), and how to apply this concept in their schoolwork. Surveys assessed the growth mindset climates in math classrooms. The present study will analyze NSLM data to investigate if 9th grade math classroom climates and students? use of a growth mindsets worked together to help students successfully complete advanced math and science courses in the early high school years. The four main objectives of the study include: (1) Coding 8th to 10th grade STEM course-taking patterns among students who participated in the NSLM and describing the extent to which minority groups are under-represented in advanced STEM coursework; (2) Testing whether a 9th grade math class with a strong growth mindset climate predicts higher rates of persistence in 10th grade STEM courses among students from under-represented groups; (3) Identifying the growth-oriented teacher practices that best create a growth mindset climate and increase STEM course persistence; and (4) Testing whether the effect on 10th grade STEM course persistence of a growth mindset intervention given directly to students in 9th grade depends on the 9th grade math classroom climate.Analyses of NSLM data will present a unique opportunity to study why 9th grade math continues to be a gatekeeper course for many underrepresented students. The study will move beyond research that focused on letter grades (i.e. A, B, etc.) and instead focus on course taking patterns (i.e. taking Algebra II in 10th grade or not). Thus, it will advance knowledge about reducing attrition of underrepresented groups in rigorous math pathways. The combined use of quantitative techniques and an integrative theory will help address the ongoing national goal for diversifying the future STEM workforce. Intersectional analyses?which look at groups that have multiple disadvantages, such as students who are both in a racial minority group and who are learning English?are essential to uncovering a deeper understanding of inequities faced by these groups. To do so, the study will build a database that links student and teacher records to validate novel, efficient, and scalable assessments of math classroom climates and math teacher practices useful for improving instructional climates that narrow achievement gaps in high school trajectories. Last, this study will advance knowledge about scalable, low-cost interventions, and identify classrooms where such interventions are most or least effective.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.