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: 2201701
• 负责人: Bailey Brown
• 金额: $ 23.22万
• 依托单位: Spelman College
• 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=2201701&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在获得和参与计算机科学（CS）教育方面长期存在的不平等现象。几十年的研究表明，某些亚组（例如，妇女、残疾学生、代表性不足的少数民族学生）在参加CS课程和方案时往往面临很大的障碍。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的早期经验与大学计算课程和课程的入学率之间的关系。通过将大规模招生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相结合，该项目旨在为扩大和多样化参与计算教育的努力提供信息。具体地说，该项目旨在系统地回答K-12计算经验如何影响学生，因为他们追求高等教育，以及这种影响是否以及如何对不同的学生亚群有所不同。该混合方法项目的目标是通过调查学生在K-12中的计算经验之间的关系来检查计算机科学（CS）教育的公平性。12和高等教育，重点是黑人妇女的经验。指导本研究的理论框架是黑人女性主义思想，特别是交叉性和社会资本理论。该项目跨越三个层次的数据收集和分析：国家，机构和个人经验。这些级别不是指分析单位（所有三个级别都使用学生级别的数据），而是指数据的组织方式。全州教育数据的聚类分析将用于确定初中和高中的计算机科学课程模式。多层次建模，然后将调查这些课程采取模式是如何相关的参与计算课程和计划在大学。重点将放在了解这些关系如何不同的学生群体。这些分析的结果将与大学生调查的分析相结合，以更好地了解学生在K-12的经历如何影响他们在大学计算机教育方面的机会，挑战和决策。最后，主修CS的黑人女性将参与数据解释，焦点小组和访谈，以更好地了解他们在CS生态系统中的独特体验。这些分析将有助于概念化扩大参与计算沿着K-16途径的方式，支持学生，特别是黑人妇女，在应用计算技能和知识，以解决各种学科的问题。ECR计划强调基础STEM教育研究，产生该领域的基础知识。投资是在关键领域是必不可少的，广泛的，持久的：干学习和干学习环境，扩大参与干，干劳动力发展。该计划支持积累强有力的证据，为理解、建立理论解释和建议干预措施和创新以解决持久性问题提供信息。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。