Integrating Computational Science with Environmental Sciences Associated with Habitat Restoration and Education in New York Harbor

随着计算已成为科学，技术，工程和数学（STEM）实践的组成部分，STEM+计算计划旨在通过在幼儿教育中应用计算思维和计算活动的整合来解决计算STEM领域的新挑战。 该项目由STEM+C计划支持，并通过将计算思维，数据素养和统计概念与基于现场的STEM课程模型相结合来推进其使命，该课程模型面向中学生，专注于与栖息地监测和恢复相关的科学领域。这种整合将通过以下方式实现：（1）在纽约港水域内和附近扩大和进一步发展支持实地科学经验的恢复中心;（2）为教师提供专业学习机会，将计算思维与其他STEM学科相结合;（3）开发课程单元，促进计算机科学和数据科学概念和技能的学习，并提高对计算机职业教育途径的认识，该项目将加强一个大规模的设计和开发项目，该项目正在测试一个在城市环境中以社区为基础的科学教育模式。 现有的课程模式侧重于与监测环境条件和栖息地恢复相关的地质，环境和生物科学的关键概念。该项目将通过将数据素养，计算思维和相关统计概念和技能整合到现有课程中来增强现有模式，使学生能够获得与收集和分析与环境监测和栖息地恢复相关的大量实地数据相关的新技能和能力。需要分析的数据范围从基本的水化学数据到与细菌监测和环境DNA采样和分析有关的数据。 本研究基于三个假设：（1）教师在数据素养、计算机科学和STEM实践方面的专业学习将积极影响学生在课堂上的成绩;（2）通过教师在数据素养、计算机科学和科学研究实践方面的专业学习进行教学，再加上教师和学生与科学家的接触，将对学生的计算思维知识和对STEM领域和职业的看法产生积极影响;以及（3）该项目的参与模式，包括基于问题的学习，将提高学生对STEM职业教育途径的认识和意愿。各种各样的措施将被用来与教师和学生在治疗和比较组，以测试这些hypothesis.This奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

As computing has become integral to the practice of science, technology, engineering and mathematics (STEM), the STEM+Computing program seeks to address emerging challenges in computational STEM areas through the applied integration of computational thinking and computing activities within STEM teaching and learning in early childhood education through high school (preK-12). This project is supported by the STEM+C program and advances its mission by integrating computational thinking, data literacy, and statistical concepts with a field-based STEM curriculum model for middle school students that focuses on science fields associated with habitat monitoring and restoration. This integration will be accomplished through: (1) Expansion and further development of Restoration Hubs in and near the water of New York Harbor that support field science experiences; (2) Professional learning opportunities for teachers that feature integration of computational thinking with other STEM disciplines; (3) Development of curriculum units that promote learning of computer science and data science concepts and skills, and raise awareness of education pathways to careers in computing, data sciences, and habitat restoration sciences; and (4) A summer STEM Institute for computer science and computing.This project will augment a large-scale design and development project that is testing a model of community-based science education in an urban environment. The existing curriculum model focuses on key concepts in the geological, environmental, and biological sciences that are associated with monitoring environmental conditions and habitat restoration. This project will enhance the existing model by integrating data literacy, computational thinking and relevant statistical concepts and skills into the existing curriculum, enabling students to gain new skills and competencies associated with gathering and analyzing large amounts of field data associated with environmental monitoring and habitat restoration. Data to be analyzed range from basic water chemistry data to data associated with bacterial monitoring and environmental DNA sampling and analyses. The research associated with this project is guided by three hypotheses: (1) Teacher professional learning in data literacy, computer science, and STEM practices will positively influence student outcomes within their classrooms; (2) Teaching informed by teacher professional learning in data literacy, computer science, and science research practices, coupled with teacher and student engagement with scientists will positively influence student knowledge of computational thinking and perceptions of STEM fields and careers; and (3) The project's model of engagement, including problem-based learning, will enhance student awareness of and intent to pursue education pathways to STEM careers. A variety of measures will be used with teachers and students in treatment and comparison groups to test these hypotheses.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.