Building Multi-level Alignment in Local Computer Science for All Implementations for Sustainability

美国的计算机科学(CS)教育是教育变革中一项快速发展的实践。随着社区和学区响应将计算机科学纳入K-12教育环境的日益增长的愿望，为城市和州的所有学生提供优质计算机科学教育的地方倡议正在涌现。成功的倡议往往得到对CS内容和教育都有了解的非营利组织或地区领导的支持。这种多管齐下的方法使CS for All运动在扩大K-12学习者获得计算机教育的机会的目标上取得了快速进展。然而，这种快速的扩展也造成了巨大的困难，因为学校和教师的选择已经超过了学区在没有CS教育专家的情况下深思熟虑地选择CS教育合作伙伴以促进教师专业发展和课程实施所需的支持。选择CS教育合作伙伴需要了解如何协调愿景、实施和课程决策。因此，该项目将创建研究-实践伙伴关系(RPP)，以支持K-8学校制定协调的愿景和多年级实施计划，以促进它们发展可持续的CS课程，并扩大到更广泛的参与。通过研究和实施，该项目将有助于理解在K-8级别实施计算机科学教育的选择。这些实施选择是全国范围内可持续的CSfor所有倡议的关键。该项目将有助于对这一决策过程的理解，有助于在这一过程中帮助学校和学区的支持，以及学校和学区用来评估其正在进行的实施是否符合社区愿景的措施。这些成果将有助于就如何促进与CS教育相关的系统性教育变革努力提供基本的见解。这项研究是一项描述性研究，将专注于记录和理解愿景、一致的决策制定和实施行动的过程，以促进更广泛地参与K-8计算教育。四个项目目标指导研究实践者伙伴关系(RPP)工作：目标1：在纽约大学CSforAll联盟和纽约农村和郊区合作教育服务的两个委员会之间建立RPP，以支持CS的所有努力，着眼于长期伙伴关系和未来的迭代工作。目标2：设计和试点设想、决策和实施例程，为所有实施提供综合工具包，以促进K-8学校和学区围绕CS进行决策。目标3：制定一套切实可行的措施，为地区和学校提供快速、成型的衡量标准，以评估其CS在一段时间内对所有倡议的协调和实施情况。目标4：对伙伴关系开展的指导性决策和实施过程进行研究，从而为所有可扩展、可持续并可触及更广泛的学习者群体的实施决策提供更细致入微和更稳健的CS。

Computer science (CS) education in the United States is a rapidly evolving exercise in educational change. Local initiatives to bring quality CS education to all students in cities and states are emerging as communities and school districts respond to the growing desire to include computer science in K-12 education settings. Successful initiatives are often supported by non-profit organizations or district leadership that possess an understanding of both CS content and education. The multi-pronged approach has positioned the CS for All movement to make rapid progress in the goal of broadening access to computing education for K-12 learners. However, this rapid expansion has also created significant difficulties, as the options available to schools and teachers have outpaced the supports necessary for a school district, without an expert in CS education, to thoughtfully select CS education partners to facilitate teacher professional development and curricular implementation. Selection of CS education partners requires an understanding of how to coordinate vision, implementation, and curriculum decisions. Thus, this project will create a research-practice partnership (RPP) to support K-8 schools in developing coordinated visions and multi-grade implementation plans that facilitate their development of sustainable CS programs that scale to broader participation. Through research and implementation, the project will contribute to an understanding of CS education implementation choices at the K-8 level. These implementation choices are key to sustainable CSforAll initiatives around the country. The project will contribute to the understanding of that decision making process, supports that can help schools and districts in the process, and measures for schools and districts to use to assess the alignment of their ongoing implementation to community visions. These outcomes will contribute fundamental insights about how to foster systemic educational change efforts as they relate to CS education. The research, a descriptive study, will focus on documenting and understanding the process of visioning, aligned decision making, and implementation moves that can facilitate broader participation in K-8 computing education. Four project goals guide the Researcher Practitioner Partnership (RPP) work: Goal 1: Establish an RPP between the CSforAll Consortium, New York University, and two Boards of Cooperative Educational Services in rural and suburban New York to support CS for All efforts, with an eye toward long-term partnership and future, iterative work. Goal 2: Design and pilot visioning, decision-making, and implementation routines that can provide an integrated toolkit for facilitating K-8 school and district decision making around CS for All implementation. Goal 3: Develop a set of practical measures that can provide fast, formative metrics for districts and schools to evaluate the alignment and implementation of their CS for All initiatives over time. Goal 4: Conduct research on the guided decision-making and implementation processes that the partnership undertakes that will result in scholarly insights about enabling more nuanced and robust CS for All implementation decisions that can be scalable, sustainable, and reach broader populations of learners.