Developing a Suite of Standards-based Instructionally Supportive Tools for Middle School Computer Science

随着计算机已经成为世界和劳动力不可分割的一部分，K-12教室对计算机科学（CS）教育的需求正在增长。美国各州和学区正在增加计算机科学课程的开设，这增加了对具有计算机科学内容和教学知识的教师的需求。然而，许多计算机科学教师最初并没有获得教授计算机科学的认证，而且往往缺乏必要的工具、资源和培训。该计划将开发一套教育资源、评估工具和教师专业发展活动，以支持教师发展对计算机科学内容和标准的认识。改进CS教学，以应对学生群体的需求和挑战，对于那些在计算机科学方面通常得不到充分服务和代表性的学生人数众多的学区尤为重要。该项目是SRI国际、密尔沃基公立学区和旧金山联合公立学区之间的合作项目，将提供与标准相关的专业发展经验。教师将通过虚拟网络研讨会和面对面教学相结合的方式接受培训。教师将有机会评估自己的教学，并衡量学生在标准方面的进步。本研究将探讨这些教师专业发展活动如何帮助教师改善CS内容和教学知识。该团队将使用混合方法设计来回答三个研究问题：1)如何设计符合计算机科学标准的教育教学支持，使其对使用不同计算机科学课程的中学计算机科学教师具有翔实和有用的信息，教师需要什么样的专业发展（PD）才能使用这些教育教学支持并从中受益？2)教师在计算机科学课程中采用和使用符合标准的教育资源和教学支持的计算机科学评估工具的不同方式是什么？3)标准化教学支持和教师PD如何提高中学教师的CS教学内容知识，提高他们实施标准化CS教学的能力？为了回答研究问题一，团队将使用循证设计方法系统地解开每个标准，并制定一致的教学支持评估和评分指南。研究问题一的数据分析包括对学生认知访谈的定性分析，以确定学生的熟练程度和挑战。教师与研究者评量分数之信度分析。学生反应的心理测量分析为信度和效度证据。教师对评估数据的课堂观察分析。教师访谈，提供对已开发的任务和评分指南的有用性的反馈。对于研究问题2和3，该项目将从多个来源收集和分析数据，包括教师访谈、课堂观察、教师PCK（教学内容知识）调查和教师日志，以确定项目的影响。问题二和问题三的数据分析将包括分析第二年开始到第三年结束期间教师PCK的变化。从课堂试点和案例研究两方面对教师在课堂上使用的教学实践观察进行定性分析。该项目将招募24名不同经验水平的教师。此外，还将招募450名中学生，其中包括相当数量的女性、非裔美国人和西班牙裔学生。项目评估将检查项目目标和目的的总体成就。项目成果将在国家会议上广泛传播，并通过向评审期刊投稿的方式传播。项目资源和包括PD网络研讨会在内的教学支持工具将在线提供给学区和教师。探索研究preK-12项目（DRK-12）旨在通过研究和开发创新资源、模型和工具，显著提高preK-12学生和教师对科学、技术、工程和数学（STEM）的学习和教学。DRK-12计划中的项目建立在STEM教育的基础研究和先前的研究和开发工作的基础上，为拟议的项目提供了理论和实证依据。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

As computing has become an integral part of the world and the workforce, demand for computer science (CS) education in K-12 classrooms is growing. States and school districts in the U.S. are increasing CS course offerings, increasing the need for teachers with CS content and teaching knowledge. However, many CS teachers are not originally certified to teach computer science and often lack the necessary tools, resources, and training. This project will develop a set of educational resources, assessment tools and teacher professional development (PD) activities to support teachers in developing knowledge of CS content and standards. Improved CS instruction that is responsive to the needs and challenges of the student population is particularly critical in school districts with a large population of students who are typically underserved and under-represented in computer science. The project, a partnership between SRI International, the Milwaukee Public School District, and the San Francisco United Public School District, will provide professional development experiences tied to standards. Teachers will receive training via a combination of virtual webinars and face-to-face instruction. Teachers will have opportunities to evaluate their own teaching and measure their students' progress towards the standards. The research will examine how these teacher professional development activities can help improve CS content and pedagogical knowledge for teachers. The team will use a mixed-methods design to answer three research questions: 1) How can CS standards-aligned educative instructional supports be designed to be informative and useful to middle school CS teachers using different CS curricula and what professional development (PD) do teachers need to be able to use and benefit from these educative instructional supports? 2) What are the different ways in which teachers adapt and use the standards-aligned educative resources and instructionally supportive CS assessment tools in their CS classes? 3) How can standards-aligned instructional supports and teacher PD improve middle school teachers' CS pedagogical content knowledge and improve their implementation of standards-aligned CS instruction? To answer research question one, the team will use an Evidence-Centered Design approach to systematically unpack each standard and develop aligned instructionally supportive assessments and scoring guides. Data analysis for research question one includes qualitative analysis of student cognitive interviews to determine the student's proficiencies and challenges. Inter-rater reliability analysis of teacher and researcher scores on assessments. Psychometric analysis of student responses for reliability and validity evidence. Analysis of classroom observations of teachers responding to data from assessments. Teacher interviews providing feedback on the usefulness of the tasks and scoring guides that have been developed. For research questions two and three, the project will collect and analyze data from multiple sources, including teacher interviews, classroom observations, teacher PCK (pedagogical content knowledge) surveys, and teacher logs to determine the impacts of the project. Data analysis for questions two and three will include analysis of shifts in teacher PCK between the start of year two and the end of year three. Qualitative analysis of observations for instructional practices teachers are using in their classroom from the classroom pilot and case studies. The project will recruit 24 teachers of varying experience levels. Additionally, 450 middle school students will be recruited with a significant number of female, African-American, and Hispanic students represented in the sample. Project evaluation will examine the overall achievement of program goals and objectives. Project results will be disseminated widely at national conferences and through submissions to refereed journals. The project resources and instructionally supportive tools including PD Webinars will be made available online to school districts and teachers. The Discovery Research preK-12 program (DRK-12) seeks to significantly enhance the learning and teaching of science, technology, engineering and mathematics (STEM) by preK-12 students and teachers, through research and development of innovative resources, models and tools. Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed projects.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.