A Study of Elements of Teacher Preparation Programs that Interact with Candidates' Characteristics to Support Novice Elementary Teachers to Enact Ambitious Mathematics Instruction

在美国，培养大量的小学教师来实施高质量或雄心勃勃的数学教学是一项核心政策挑战。虽然有几项研究试图确定教师准备的特征与学生成绩结果之间的联系，但很少有大规模的研究解决了教师准备与雄心勃勃的数学教学之间的关系，这是一个更接近的结果。为了满足雄心勃勃的数学教学的需要，需要一个更强大的研究基础，关于如何支持初任教师制定这样的教学。为此，这项NSF EHR核心研究二级研究将调查教师准备计划如何支持小学候选人发展雄心勃勃的数学教学，以及与这些计划的毕业生如何作为一年级和二年级教师制定数学教学相关的因素。混合方法研究设计中的文化历史活动理论（CHAT）将被应用于检查初级候选人的特征（即他们的教学身份、信仰和关于数学教学的知识）如何与他们在数学方法课程中的学习机会（OTL）和学生教学经验相互作用，以影响他们作为一年级和二年级教师制定雄心勃勃的数学教学。本研究亦将探讨初任教师的特质如何与学校的资源及期望相互作用，从而影响初任教师的数学教学。研究结果将为大学教师预备课程的设计提供信息，包括有特色的初级候选人的选择，数学方法课程的内容，以及学生教学作业的理想特征。这项工作得到了EHR核心研究（ECR）项目的支持。ECR项目强调在该领域产生基础知识的基础STEM教育研究。投资在至关重要、广泛和持久的关键领域：STEM学习和STEM学习环境，扩大STEM参与，以及STEM劳动力发展。该项目支持积累有力的证据，为理解、构建理论进行解释提供信息，并提出干预和创新建议，以应对STEM兴趣、教育、学习和参与方面的持续挑战。本研究将对150名小学候选人进行调查，这些候选人来自三个州的六个教师准备项目，目的是在他们的最后一年准备和前两年的教学中进行抽样调查。数学扫描（M-Scan）课堂观察仪器将用于多次观察这些毕业生作为一年级和二年级教师教数学。M-Scan通过评估教师对数学任务、话语、表征和连贯的使用来衡量雄心勃勃的数学教学。此外，本研究还将采访各大学的初级准备项目主任和数学方法教师；它还将对教师教育工作者、实习教师、数学教学教练和与新教师研究参与者一起工作的校长进行调查。本研究的主要结果是通过使用四种M-Scan结构：数学任务、话语、表征和连贯来衡量新手制定雄心勃勃的数学教学。每个结构代表它自己的因变量。多元回归将用于研究主要结果作为几个自变量（包括教师个体特征、数学方法课程和学生教学中的OTL、新教师学校的资源和期望）的函数以及这些变量之间的相互作用。所有模型都将包括教师属性（例如，教师的ACT/SAT分数，本科院校的选择性，本科平均成绩）和学校属性（例如，学生种族/民族，学生免费/减少午餐的资格，学校规模，城市化，课程政策，专业发展产品）的控制向量。该项目将有助于建立知识库，以设计高质量的教师培训和入职培训项目，为具有各种背景经验、信仰和知识的初级候选人和新教师提供支持。这包括了解抑制或促进雄心勃勃的数学教学发展的因素，以确保新小学教师能够为所有学生提供支持他们对数学内容的深刻概念理解的教学。

Preparing large numbers of elementary teachers to enact high-quality or ambitious mathematics instruction is a central policy challenge in the U.S. While several studies have tried to identify linkages between features of teacher preparation and student achievement outcomes, few large-scale studies have addressed the relationship between teacher preparation and ambitious mathematics instruction, a more proximal outcome. To meet the need for ambitious mathematics instruction, a more robust research base is needed regarding how to support beginning teachers in enacting such instruction. To that end, this NSF EHR Core Research Level II study will investigate how teacher preparation programs support elementary candidates in developing ambitious mathematics instruction and factors that are associated with how graduates of these programs enact mathematics instruction as first- and second-year teachers. Cultural-historical activity theory (CHAT) in a mixed-methods research design will be applied to examine how elementary candidates' characteristics (i.e., their teaching identity, beliefs, and knowledge with regard to teaching mathematics) interact with their opportunities to learn (OTL) in mathematics methods courses and student teaching experiences to influence their enactment of ambitious mathematics instruction as first- and second-year teachers. The study will also explore how novice teachers' characteristics interact with resources and expectations in their schools to influence their mathematics instruction as teachers of record. The study results will inform the design of university-based teacher preparation programs, including the selection of elementary candidates with particular characteristics, the content of mathematics methods courses, and desirable characteristics of student teaching assignments. This work is supported by the 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 STEM interest, education, learning and participation.This study will feature surveys of 150 elementary candidates from a purposively sampled set of six teacher preparation programs in three states during their final year of preparation and their first two years of teaching. The Mathematics Scan (M-Scan) classroom observation instrument will be used to observe these graduates multiple times as they teach mathematics as first- and second-year teachers. M-Scan measures ambitious mathematics instruction by assessing teachers' use of mathematical tasks, discourse, representations, and coherence. In addition, this study will feature interviews with elementary preparation program directors and mathematics methods instructors at each university; and it will feature surveys of teacher educators, practicing teachers, mathematics instructional coaches, and principals who work with the novice teacher study participants. The study's primary outcome is to measure novices' enactment of ambitious mathematics instruction by using the four M-Scan constructs: mathematical tasks, discourse, representations, and coherence. Each construct represents its own dependent variable. Multiple regression will be used to study the main outcome as a function of several independent variables (including individual teacher characteristics, OTL in mathematics methods courses and student teaching, and resources and expectations in novice teachers' schools) and interactions among these variables. All models will include a vector of controls for teacher attributes (e.g., the teacher's ACT/SAT score, selectivity of undergraduate institution, undergraduate grade point average) and school attributes (e.g., student race/ethnicity, student eligibility for free/reduced lunch, school size, urbanicity, curriculum policy, professional development offerings). This project will contribute to building the knowledge base for designing high-quality teacher preparation and induction programs that support elementary candidates and novice teachers with a range of background experiences, beliefs, and knowledge. This includes understanding factors that inhibit or promote the development of ambitious mathematics instruction to ensure that new elementary teachers are able to provide all students with instruction that supports their deep conceptual understanding of mathematical content.