Computer Science for Appalachia: Expanding a Research-Practice Partnership to Integrate Computer Science and Literacy in Rural East Tennessee Schools

该项目以田纳西州东部学生的文化和语言资源为基础，支持教师以实质性和有意义的方式教授计算机科学(CS)。在现有研究实践伙伴关系的基础上，该小组正在开发CS-扫盲课程，重点是将讲故事作为一种与区域相关的实践。此外，该团队正在发展教师专业发展，以支持课程。以设计为基础的研究指导课程和教师专业发展的规划、开发和完善。参与课程的教师将在课堂上实施课程，以支持学生学习CS和识字。教师参与者将组成阿巴拉契亚教师网络的CS，以便为教育工作者提供一个社区，使他们能够在学校和教室中理解CS扫盲的融合。这些发现将为农村学区如何为教师和学生创造机会，让他们在小学年级与CS进行有意义的互动提供一个模式。第一部分主要探讨了教师认同与课堂教学认同的关系，以及教师人格特征在教师课堂教学认同形成中的作用。数据将通过调查、访谈和工作会议的视频录制来收集。定性数据的归纳/演绎编码将用于提供与CS相关的教师身份识别的丰富描述，而定量数据将使用描述性统计进行总结。第二个研究重点是学生与CS相关的学习和参与。数据将包括学生评估、工作成果和学生参与度的退学券。内容分析将用于分析学生评估，描述性统计以及分层线性建模将用于分析学生随时间推移的学习和参与情况。第三部分是关于阿巴拉契亚教师网络的CS。数据将通过教师调查收集。将进行网络分析和回归分析，以确定导致网络参与者之间联系增多或减少的特征和因素。这个项目的发现将有助于了解教师网络在支持CS教育的改进和改革努力方面的重要性和效用。该奖项反映了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。

This project supports teachers in teaching computer science (CS) in substantial and meaningful ways that build on the cultural and linguistic resources of students in East Tennessee. Building on an existing Research Practice Partnership, the team is developing a CS-Literacy curriculum with a focus on storytelling as a regionally relevant practice. In addition, the team is developing teacher professional development to support the curriculum. Design-based research guides the planning, development, and refinement of the curriculum and teacher professional development. Participating teachers will implement the curriculum in their classrooms to support students’ learning of CS and literacy. The teacher participants will form a CS for Appalachia Teacher Network in order to provide educators with a community to make sense of CS Literacy integration in their schools and classrooms. The findings will provide a model for how rural school districts create opportunities for teachers and students to engage meaningfully with CS in elementary grades.Three strands of research guide this project. The first strand focuses on teacher identity related to CS and the role of the teacher PD in shaping CS identify. Data will be collected via surveys, interviews, and video recordings of work sessions. Inductive/deductive coding of qualitative data will be used to provide rich descriptions of teacher identify related to CS and quantitative data will be summarized using descriptive statistics. The second strand of research focuses on student learning and engagement related to CS. Data will include student assessments, work products, and exit tickets that capture student engagement. Content analysis will be used to analyze student assessments and descriptive statistics as well as hierarchical linear modeling will be used to analyze student learning and engagement over time. The third strand focuses on the CS for Appalachia Teacher Network. Data will be collected via teacher surveys. Network analyses will be conducted as well as regression analyses to determine the characteristics and factors that contribute to greater or fewer connections among the network participants. The findings from this project will contribute to knowledge about the importance and utility of teacher networks for supporting improvement and reform efforts in CS education.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.