Math Classrooms, Student Mindsets and STEM Pathways in High School

ECR计划强调基础STEM教育研究，这将产生该领域的基础知识。这项研究将通过建立关于在STEM教育中扩大代表不足的少数群体(有色人种学生、年轻女性、来自低SES家庭的学生、残疾学生、英语学习者)以及他们之间的交集的理论来增加基础知识。这项研究将使用全国学习心态研究(NSLM)的数据，这是迄今为止规模最大的全国性随机对照心理干预试验，对公立高中进行了全国性概率抽样，对城区学校进行了超抽样，包括来自83所学校的18,000多名学生。NSLM的目标是深入了解如何在STEM渠道中留住代表性不足的学生。通过干预，学生们学到了成长心态的概念(认为在学校的挣扎是学习的机会，并不意味着你缺乏智力)，以及如何在他们的学业中应用这一概念。调查评估了数学课堂上的成长心态氛围。本研究将分析NSLM的数据，以调查九年级数学课堂气氛和学生？利用成长的思维模式，帮助学生在高中早期成功完成高等数学和科学课程。这项研究的四个主要目标包括：(1)编码参加NSLM的学生中8到10年级的STEM课程选择模式，并描述少数群体在高级STEM课程中的代表性不足的程度；(2)测试具有强烈成长心态氛围的9年级数学课是否预示着来自代表不足群体的学生在10年级STEM课程中的坚持率更高；(3)确定最能创造成长心态氛围和增强STEM课程持久性的以成长为导向的教师做法；以及(4)测试直接给予9年级学生的成长心态干预对10年级STEM课程持续性的影响是否取决于9年级数学课堂气氛。对NSLM数据的分析将提供一个独特的机会，来研究为什么9年级数学仍然是许多代表不足的学生的一门把关课程。这项研究将超越专注于字母等级(即A、B等)的研究。而是专注于选课模式(例如，是否在10年级上代数II)。因此，它将在严格的数学途径中推进关于减少代表不足群体的自然减员的知识。量化技术和综合理论的结合使用将有助于实现目前正在进行的国家目标，即使未来的STEM劳动力多样化。交叉分析--着眼于具有多重劣势的群体，例如既是少数族裔群体的学生，又在学习英语的学生--对于深入了解这些群体面临的不平等至关重要。为此，这项研究将建立一个数据库，将学生和教师的记录联系起来，以验证对数学课堂气氛和数学教师实践的新颖、高效和可扩展的评估，这些评估有助于改善教学气氛，缩小高中成绩差距。最后，这项研究将促进有关可扩展的低成本干预措施的知识，并确定此类干预措施最有效或最不有效的课堂。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势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.