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

与候选人特征相互作用的教师准备计划要素的研究，以支持小学新手教师进行雄心勃勃的数学教学

• 批准号: 1535024
• 负责人: Peter Youngs
• 金额: $ 149.76万
• 依托单位: University of Virginia Main Campus
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-10-01 至 2020-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1535024&HistoricalAwards=false
• 关键词: Study; Elements; Teacher; Preparation; Programs

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.

准备大量的小学教师制定高质量的或雄心勃勃的数学教学是一个中心的政策挑战，在美国，虽然一些研究试图确定教师准备和学生成绩之间的联系，很少有大规模的研究已经解决了教师准备和雄心勃勃的数学教学，一个更接近的结果之间的关系。 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，关于如何支持开始制定这样的教学教师。为此，NSF EHR核心研究II级研究将调查教师准备计划如何支持小学候选人制定雄心勃勃的数学教学以及与这些计划的毕业生如何作为第一年和第二年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）将被应用于研究初级候选人的特征（即，他们的教学身份，信念和知识方面的教学数学）与他们的机会学习（OTL）的数学方法课程和学生的教学经验，影响他们制定雄心勃勃的数学教学作为第一和第二年的教师。 本研究亦将探讨新教师的特质如何与学校的资源及期望相互作用，进而影响他们作为纪录教师的数学教学。 研究结果将告知以大学为基础的教师准备计划的设计，包括选择具有特定特征的小学候选人，数学方法课程的内容，以及学生教学任务的理想特征。这项工作得到了EHR核心研究（ECR）计划的支持。 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，并建议干预和创新，以解决STEM兴趣，教育，学习和参与。本研究将调查150名小学候选人，他们来自三个州的六个教师培训项目，在他们的最后一年和前两年的准备工作中，教学 数学扫描（M-Scan）课堂观察仪器将被用来观察这些毕业生多次，因为他们教数学作为第一和第二年的教师。 M-Scan通过评估教师对数学任务、话语、表征和连贯性的使用来衡量雄心勃勃的数学教学。 此外，本研究将在每个大学的基本准备项目主任和数学方法教师的访谈，它将具有教师教育工作者，执业教师，数学教学教练和校长谁与新手教师研究参与者的调查。 本研究的主要成果是通过使用四个M-Scan结构：数学任务，话语，表征和连贯性来衡量新手制定雄心勃勃的数学教学。 每个结构都代表自己的因变量。 多元回归将被用来研究主要结果作为几个独立变量（包括个别教师的特点，OTL在数学方法课程和学生教学，资源和期望在新手教师的学校）和这些变量之间的相互作用的函数。 所有模型都将包括教师属性的控制向量（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、城市化程度、课程政策、专业发展课程）。 该项目将有助于建立知识基础，以设计高质量的教师准备和入职课程，支持小学候选人和新手教师的背景经验，信仰和知识的范围。这包括理解抑制或促进雄心勃勃的数学教学发展的因素，以确保新的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。