RET Site: Berkeley Research Experiences for Teachers plus Data Science (BERET+D)

加州大学伯克利分校的 RET 站点名为“RET 站点：伯克利教师研究经验加数据科学 (BERET D)”，将重点研究旨在向职前和在职数学和科学教师介绍如何使用数据科学来理解、分析和可视化工程和科学数据，包括来自整个校园科学中心的分布式数据集。 BERET D 计划的一个关键要素是支持教师获取必要的教学内容知识，以便让自己的 K-12 学生参与数据科学。在职和职前教师团队将在加州大学伯克利分校的各种工程实验室和科学中心进行研究。教师团队还将参加一系列夏季和学年的专业发展活动，以支持他们将研究成果转化为课程。 BERET D 将把参加加州大学伯克利分校 CalTeach 项目的职前教师与经验丰富的在职教师配对，为合作公立学区的代表性不足的学生提供服务。这些教师团队将通过参与数据科学研究来培养必要的研究、分析和可视化技能。基于共同的研究经验，教师团队将开发将当前研究与 K-12 科学和数学教育联系起来的课程，并激励学生将 STEM 视为一项令人兴奋的职业并在现实生活中得到应用。教师们的研究工作受到实验室导师的指导，他们将通过在夏季担任研究顾问以及在学年担任 K-12 课堂的教学伙伴来获得教学经验。此外，还将通过支持参与教师共同主持学年专业发展研讨会，向他们提供领导机会。BERET D 将支持教师进行该领域的研究，学习将数据科学融入课堂教学的有效策略，以及开发、使用和传播基于标准的课程，从而为工程和科学研究以及 K-12 教育做出贡献。 BERET D 将指导教师通过对专业发展活动中的这些经验进行深入、真实的研究和支架式反思，了解开展研究的过程，特别是涉及大数据集的过程。 BERET D 将使参与者做好准备，将他们的研究经验融入到课堂中，并让 K-12 学生理解和处理重要数据集。 CalTeach 将使用 RET 计划数据作为其教师教育和专业发展研究持续努力的一部分，评估独特的伙伴关系（职前教师、在职教师和研究生之间）如何在进行真实的工程研究和在课堂上共同实施相关课程中发挥作用。该奖项反映了 NSF 的法定使命，并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，被认为值得支持。

This RET site at the University of California Berkeley entitled, "RET Site: Berkeley Research Experiences for Teachers plus Data Science (BERET+D)", will focus on research aimed at introducing pre-service and in-service math and science teachers to the use of data science in understanding, analyzing and visualizing engineering and science data, including distributed data sets from science centers across campus. A key element of the BERET+D program is support for teachers to acquire the necessary pedagogical content knowledge to engage their own K-12 students in data science. In-service and pre-service teacher teams will conduct research in a variety of engineering labs and science centers at UC Berkeley. Teacher teams will also participate in a sequence of summer and academic-year professional development activities that support them in translating their research into curriculum. BERET+D will pair pre-service teachers enrolled in the UC Berkeley CalTeach program with experienced in-service teachers serving predominantly underrepresented students in partnering public school districts. These teacher teams will develop essential research, analysis and visualization skills by engaging in data science research. Based on their common research experience, the teacher teams will develop curricula that connect current research to K-12 science and mathematics education and inspire students to see STEM as an exciting career with real-life applications. The teachers are guided in their research efforts by lab-based mentors who will gain instructional experience by serving as research advisers during the summer and as teaching partners in the K-12 classroom during the academic year. In addition, leadership opportunities will be provided to participating teachers by supporting them to co-facilitate academic year professional development workshops.BERET+D will contribute to engineering and scientific research, and K-12 education by supporting teachers to conduct research in the field, learn effective strategies for integrating data science into their classroom instruction, and develop, use and disseminate standards-based curricula. BERET+D will guide teachers to gain an understanding of the processes of conducting research, especially involving large data sets, by engaging in in-depth, authentic research and scaffolded reflections on these experiences in professional development activities. BERET+D will prepare participants to incorporate their research experiences into their classrooms and engage their K-12 students in both understanding and dealing with significant data sets. CalTeach will use RET program data as part of its ongoing efforts in research on teacher education and professional development, evaluating how the unique partnership (between pre-service teachers, in-service teachers, and graduate students) functions in doing authentic engineering research and co-implementing related curriculum in the classroom.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.