Examining the Factors that Influence Retention and Effectiveness of Computer Science Teachers in High-Need Middle and High Schools

该项目旨在满足国家需要，在高需求学校培养和留住有效的计算机科学(CS)教师。接受计算机科学教育的机会在公立学校中的分布不成比例。高需求学校有更多的学生来自计算机领域代表性不足的群体；他们也更有可能有教师流动率，而不太可能有经验丰富的教师和CS机会。这项研究项目将调查教师培训计划如何能够增加高需求学校的CS教师保留率，并为教师提供有效、公平的CS教学做好准备。这是至关重要的，因为对STEM教师的需求不断增加，特别是在高需求学校，以及对准备接触代表不足群体的学生的K-12 CS教师的需求。由于中学CS教师的流动率特别高，目标是产生可用于增加高需求学校CS教师的长期留任的信息。本项目由ETR(教育、培训、研究)协会牵头，与纽约大学、加州州立大学弗雷斯诺分校和路易斯安那理工大学的诺伊斯资助的三个项目以及纽约市公立学校、弗雷斯诺联合学校、中央统一学校、桑格联合学校、边维尔教区、卡多教区、林肯教区、瓦奇塔教区、里奇兰教区和温恩教区的周边学区合作开展。项目目标包括解决有关个人、人际和制度因素在教师培训计划如何增加高需求学校的CS教师保留率方面发挥作用的研究问题。本研究还旨在调查教师培训计划如何为教师在初中和高中课堂上提供有效和公平的CS教育做好准备。这项研究将以社会生态和社会公正的教学内容知识理论框架为指导。最初的猜想图记录了基于研究的假设，这些假设是关于如何让教师做好坚持并从事有效的CS教学的准备，将指导这项工作。这项研究的目标是招聘多达80名准备在高需求的初中和高中教授CS的教师。他们将参加他们的职前准备计划和两年的在职教学要求，以及超过这一教学要求。随着时间的推移，将使用混合方法收集调查、访谈、观察和机构数据。这些数据将被分析来描述教师在CS知识和社会公正教育学方面的发展，他们作为实习教师和新手带头人的经历，他们的支持社区，他们作为CS教师的身份，以及准备计划和学校网站的特点。使用设计-研究方法，该团队将使用数据迭代地改进推测图，并在每个机构的项目级别进行更改。该项目有可能有助于理解项目如何使教师做好准备，以公平和包容的方式教授CS内容，包括确定有希望的准备战略和支持，以解决影响高需求学校留住的因素。本研究旨在提供一种理论模型，可用于指导课程设计，从而提高中学计算机科学教师的留任率，并支持中学计算机科学教育的公平进行。诺伊斯项目在地理上的分散性将增加结果与一系列人口和环境相关的可能性。一个由计算机科学教育、教师培训和计算公平方面的专家组成的咨询委员会将监测项目里程碑并提供反馈，并为招聘设计、数据收集和数据分析贡献他们的专业知识。研究结果将通过出版物、演示文稿和CS教师专业发展工具包传播给研究人员和从业者。这个Track 4：Noyce研究项目是由Robert Noyce教师奖学金计划(Noyce)支持的。Noyce计划支持有才华的STEM本科专业和专业人员成为有效的K-12 STEM教师，并支持经验丰富、模范的K-12教师成为高需求学区的STEM硕士教师。它还支持对高需求学区K-12 STEM教师的有效性和留住的研究。这一奖项反映了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 project aims to serve the national need of preparing and retaining effective computer science (CS) teachers in high-need schools. Access to CS education is disproportionately distributed across public schools. High-need schools have greater numbers of students from groups that are underrepresented in computing fields; they are also more likely to have teacher turnover and less likely to have experienced teachers and CS opportunities. This research project will investigate how teacher preparation programs can increase CS teacher retention in high-need schools and prepare teachers to deliver effective, equitable CS instruction. This is essential due to the increasing demand for STEM teachers, particularly in high-need schools, and the call for K-12 CS teachers who are prepared to engage students from underrepresented groups. With turnover particularly high among secondary CS teachers, the goal is to generate information that can be used to increase the longer-term retention of CS teachers in high-need schools. The project will also identify the features of programs that prepare teachers to deliver effective, equitable CS instruction.This project is led by ETR (Education, Training, Research) Associates in partnership with three Noyce-funded projects at New York University, California State University Fresno, and Louisiana Tech University and their surrounding school districts of New York City Public Schools, Fresno Unified, Central Unified, Sanger Unified, Bienville Parish, Caddo Parish, Lincoln Parish, Ouachita Parish, Richland Parish, and Winn Parish. Project goals include addressing research questions around what individual, interpersonal and institutional factors play a role in how teacher preparation programs can increase the retention of CS teachers in high-need schools. The research also intends to investigate how teacher preparation programs can prepare teachers to deliver effective and equitable CS education in middle and high school classrooms. The research will be guided by socio-ecological and social justice pedagogical content knowledge theoretical frameworks. An initial conjecture map that documents research-based hypotheses about how to prepare teachers to persist and engage in effective CS instruction will steer the work. The study aims to recruit up to 80 teachers who are being prepared to teach CS in high-need middle and high schools. They will participate during their pre-service preparation program and their 2-year in-service teaching requirement, as well as beyond this teaching requirement. Mixed methods will be used to collect survey, interview, observation, and institutional data over time. The data will be analyzed to describe teachers’ development of CS knowledge and social justice pedagogy, their experience as a student teacher and a novice lead teacher, their community of support, their identity as a CS teacher, as well as features of the preparation program and school sites. Using a design-research approach, the team will use the data to iteratively refine the conjecture map and make changes at the program level at each institution. This project has the potential to contribute to understanding of how programs can prepare teachers to deliver CS content in an equitable and inclusive way, including identifying promising preparation strategies and supports to address factors that affect retention in high-need schools. It is intended to result in a theoretical model that can be used to inform the design of programs that can increase CS teacher retention and support equitable CS instruction in middle and high school. The geographic dispersion of Noyce projects will increase the likelihood that the results will be relevant to a range of populations and settings. An advisory board of experts on computer science education, teacher preparation, and equity in computing will monitor and provide feedback on project milestones, as well as contribute their expertise to the design of recruitment, data collection, and data analyses. Study findings will be disseminated to researchers and practitioners through publications, presentations, and a CS teacher professional development toolkit. This Track 4: Noyce Research project is supported through the Robert Noyce Teacher Scholarship Program (Noyce). The Noyce program supports talented STEM undergraduate majors and professionals to become effective K-12 STEM teachers and experienced, exemplary K-12 teachers to become STEM master teachers in high-need school districts. It also supports research on the effectiveness and retention of K-12 STEM teachers in high-need school districts.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.