States as STEM Learning Environments: Building an Indicator System to Guide Instructional Improvement at Scale

调查人员正在设计一个全州范围的、以经验为基础的指标体系，该体系与田纳西州(TN)关于教学改进的愿景保持一致，并基于对4至8年级数学课堂的教与学进行深入研究而收集的数据。研究人员从一系列结构和测量开始，这些结构和测量被认为可以预测学生在高水平数学评估(高认知需求教学)中的学习，并与教师实施雄心勃勃的教学(教师社会资本)的能力有关。其目的是将这些结构的测量提炼成一组核心的调查指标，这些指标可以预测学生的结果，可以在规模上有效地管理，并对州政策制定者的决策产生影响。使用三层方法-从密集的教师样本(n=50)深入收集数据，从中间样本(n=100)收集不太全面的数据，以及来自量表样本的基于调查的数据，这组样本的数量每年都会增加，到第三年结束时有1000名教师或大约10%的TN 4-8年级数学教师-分析利用对数学教学的深入定性审查和教师社会资本与基于调查的方法对话来构建有效性论点(凯恩，2006)：1)教师对中央结构的替代测量不同，2)这些指标与其他理论上相关的指标相关，3)这些指标在量表样本中分别对学生学习和高质量教学有预测作用。以往关于认知需求的研究为教与学之间的联系提供了理论和经验依据。该项目通过为高认知需求的教学建立代理，并观察它们与数百个教室中学生学习的关系来扩展这项工作。以往关于教师社会资本的研究主要包括理论构建和定性研究，这些研究表明教师社会资本的具体特征与教学水平之间的关系。这项研究在更多的课堂上测试了这种关系，并将其扩展到学生学习中。此外，研究人员还建立了一个实用的理论，说明各州如何支持大规模的教学改进。虽然这方面的大多数理论和研究集中于国家在为大量教师提供专业发展方面面临的挑战，但对监测这些努力的有效性和影响的挑战关注较少。这个项目是基于这样一种想法，即只做更多--而不是从正在做的事情中有系统地学习--是一个失败的命题。在当前的改革时代，越来越多的州将投入大量资源来改善各州的教育。通过将整个州的学习环境概念化，这项工作呼吁人们注意从这一活动中学习的系统和有组织的方法，从而更聪明地了解支持大规模数学改进的有效方法。开发可以在整个州部署的指标本身就是一个广泛影响的迹象。此外，该指标体系是可移植的，因为它与大多数州采用的大学和职业准备标准保持一致，可以被其他州采用，特别是那些致力于共同评估的州。此外，如果田纳西州和其他州的领导人使用指标系统来确定哪里的教学处于停滞状态，哪里需要教师支持，他们将能够就在哪里以及如何帮助各州的教育工作者做出更好的决定。这反过来将有助于实现改善STEM教育的社会目标，从而培养出更具全球竞争力的高中毕业生。最后，如果这项研究成功，我们将建立一个比迄今收集到的更长的证据链。我们将展示(A)教师获得社会资源的机会；(B)教师的教学实践；(C)学生表现之间的联系。

Investigators are designing a state-wide, empirically based indicator system that aligns with Tennessee's (TN) vision of instructional improvement and is built from data gathered through in-depth study of teaching and learning in a sample of 4th through 8th grade mathematics classrooms. Investigators begin with a set of constructs and measures that are known to predict student learning on high-level mathematics assessments (high-cognitive-demand instruction) and that are associated with teachers' capacity to enact ambitious instruction (teacher social capital). The objective is to distill the measurement of these constructs to a core set of survey indicators that are predictive of student outcomes, can be administered efficiently at scale, and are consequential for state policy makers' decision making. Using a 3-tiered approach - in-depth data collection from an intensive sample of teachers (n=50), less comprehensive data from an intermediate sample (n=100), and survey-based data from a scale sample, a group that will increase in number each year, ending in year 3 with 1000 teachers or approximately 10% of TN's grades 4-8 mathematics teachers - the analyses leverage in-depth qualitative examination of mathematics instruction and teacher social capital in dialogue with survey-based approaches to construct a validity argument (Kane, 2006) that 1) teachers vary on proxy measures of central constructs, 2) measures of these proxies are correlated with other theoretically relevant measures, and 3) these proxies are predictive of student learning and high-quality teaching, respectively, in the scale sample.Previous research on cognitive demand has provided both theoretical and empirical warrants for the connection between teaching and student learning. This project extends that work by establishing proxies for high-cognitive-demand instruction and observing their relationship to student learning across hundreds of classrooms. Previous work on teacher social capital has consisted primarily of theory-building, qualitative studies that have shown relationships between specific features of teacher social capital and level of instruction. This study tests that relationship in larger numbers of classroom and extends it to student learning. Additionally, investigators build a practical theory of how states can support large-scale instructional improvement. While most theorizing and research in this regard has focused on the challenges that states confront in providing professional development for large numbers of teachers, less attention has been paid to the challenge of monitoring the effectiveness and impact of those efforts. This project is based on the idea that just doing more - without systematically learning from what one is doing - is a failing proposition. In the era of current reforms, increasing numbers of states will be devoting substantial resources to improving instruction across their states. By conceptualizing an entire state as a learning environment, this work calls attention to systematic and organized ways to learn from that activity, thereby getting smarter about efficient ways to support large-scale improvement in mathematics.The development of indicators that can be deployed across an entire state is, in and of itself, a sign of broad impact. In addition, the indicator system is portable and, because it is aligned with college and career ready standards adopted by the majority of states, could be taken up by other states, especially those who have committed to common assessments. Furthermore, if leaders in TN and other states use the indicator system to identify where instruction is flagging and where teacher supports are needed, they will be positioned to make better decisions regarding where and how to assist educators across their states. This, in turn, will support the achievement of the societal goal of improved STEM education that will produce more globally competitive high school graduates. Finally, if this study is successful we will have established a longer chain of evidence than heretofore has been assembled. We will show linkages among (a) teachers' access to social resources; (b) teachers' instructional practice; and (c) student performance.