Collaborative Research: Researching Early Access to Computing and Higher Education (REACH): Understanding CS pathways with a focus on Black women

合作研究：研究早期计算机和高等教育 (REACH)：了解以黑人女性为重点的计算机科学途径

• 批准号: 2201700
• 负责人: Rebecca Zarch
• 金额: $ 41.12万
• 依托单位: SageFox Consulting Group, LLC
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-01 至 2025-06-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2201700&HistoricalAwards=false
• 关键词: Collaborative; Research; Researching; Early; Access

This research project seeks to examine longstanding inequities in access to and participation in computer science (CS) education. Decades of research have shown that certain subgroups (e.g., women, students with disabilities, underrepresented minority students) tend to face substantial barriers to participating in CS courses and programs. As computing education continues to expand in K-12 education systems, it is important to understand how early experiences in computing education relate to enrollment in computing courses and programs in college. By combining quantitative analyses of large-scale enrollment data and student surveys with qualitative data from focus groups and interviews, this project aims to inform efforts to broaden and diversify participation in computing education. Specifically, this project seeks to systematically answer how K-12 computing experiences influence students as they pursue higher education and whether and how that influence differs for distinct subpopulations of students.The goal of this mixed-methods project is to examine equity in computer science (CS) education by investigating the relationship between students’ computing experiences in K-12 and higher education with a focus on the experiences of Black women. The theoretical frameworks guiding this research are Black Feminist Thought, specifically intersectionality, and social capital theory. The project spans three levels of data collection and analysis: state, institution, and individual experience. These levels have reference not to the unit of analysis (all three levels utilize student-level data) but rather to the way the data are organized. Cluster analysis of statewide education data will be used to identify computer science course taking patterns in middle and high school. Multilevel modeling will then be employed to investigate how these course taking patterns are related to participation in computing courses and programs in college. Focus will be placed on understanding how these relationships differ for distinct groups of students. Findings from these analyses will be coupled with analyses of college student surveys to better understand how students’ experiences in K-12 influenced their opportunities, challenges, and decisions regarding computing education in college. Finally, Black women who are majoring in CS will be engaged in data interpretation, focus groups, and interviews to better understand their unique experiences within the CS ecosystem. These analyses will help conceptualize broadening participation in computing along the K-16 pathway in a way that supports students, particularly Black women, in applying computing skills and knowledge to solve problems in a variety of disciplines.This project is supported by NSF's EHR Core Research (ECR) program. The ECR program emphasizes fundamental STEM education research that generates foundational knowledge in the field. Investments are made in critical areas that are essential, broad, and enduring: STEM learning and STEM learning environments, broadening participation in STEM, and STEM workforce development. The program supports the accumulation of robust evidence to inform efforts to understand, build theory to explain, and suggest interventions and innovations to address persistence.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.

该研究项目旨在研究访问和参与计算机科学（CS）教育的长期不平等现象。数十年的研究表明，某些亚组（例如妇女，残疾学生，代表性不足的少数民族学生）倾向于面临参加CS课程和课程的实质性障碍。随着计算教育在K-12教育系统中的不断扩展，重要的是要了解计算教育领域的早期经验与大学的计算课程和课程的注册如何相关。通过将大规模注册数据和学生调查的定量分析与焦点小组和访谈的定性数据结合在一起，该项目旨在为扩大和多样化的计算教育参与提供努力。具体来说，该项目试图系统地回答K-12计算体验在追求高等教育时如何影响学生，以及如何以及如何影响学生的不同亚人群的差异。该混合方法项目的目标是研究计算机科学（CS）教育中的公平性，通过研究学生在K-12和高等教育之间的关系，并专注于黑人女性的计算经验之间的关系。指导这项研究的理论框架是黑人女权主义思想，特别是交叉性和社会资本理论。该项目涵盖了三个级别的数据收集和分析：国家，机构和个人经验。这些级别没有指分析单位（所有三个级别都利用学生级数据），而是指组织数据的方式。全州教育数据的聚类分析将用于识别中学和高中的计算机科学课程。然后，将采用多级建模来研究这些课程模式如何与参与大学的计算课程和课程有关。将重点放在理解不同的学生群体中这些关系如何不同。这些分析中的发现将与大学学生调查的分析相结合，以更好地了解学生在K-12中的经验如何影响他们有关大学计算教育的机会，挑战和决策。最后，在CS专业的黑人妇女将参与数据解释，焦点小组和访谈，以更好地了解其在CS生态系统中的独特经历。这些分析将有助于概念化沿着K-16途径的计算参与的概念，以支持学生，尤其是黑人妇女的方式应用计算技能和知识来解决各种学科中的问题。该项目得到NSF的EHR核心研究（ECR）计划的支持。 ECR计划强调了基本的STEM教育研究，该研究在该领域产生了基础知识。投资是在重要，广泛和结束的关键领域进行的：STEM学习和STEM学习环境，扩大参与STEM以及STEM劳动力的发展。该计划支持积累强大的证据，以告知努力，以理解，建立理论来解释和提出解决持久性的干预措施和创新。该奖项反映了NSF的法定任务，并被认为是通过基金会的智力优点和更广泛的影响来通过评估来获得支持的。