Collaborative Research: Using Complex Systems Theory and Methods to Gauge the Gains and Persisting Challenges of Broadening Participation Initiatives
合作研究:利用复杂系统理论和方法来衡量扩大参与计划的收益和持续的挑战
基本信息
- 批准号:2301197
- 负责人:
- 金额:$ 20.27万
- 依托单位:
- 依托单位国家:美国
- 项目类别:Standard Grant
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-07-01 至 2026-06-30
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
During the last decades, there have been significant investments in Broadening Participation Initiatives (BPIs) aimed to increase the participation of marginalized groups in engineering. Yet the plethora of factors that influence the success of BPIs and persistent challenges faced by BPIs complicate a strong grasp of their impact. Not understanding the aspects that make BPIs effective, limits their potential for institutional change. BPIs are often implemented within higher education institutions, which are complex systems with intricate dynamic interactions among multiple people and factors. Therefore, to gauge the impact of BPIs it is necessary to adopt systems approaches that acknowledge such dynamic complexity. This project adopts two well-established complex systems methods to bring theoretical and practical value to harness the impact of BPIs in higher education institutions: (1) Qualitative Comparative Analysis (QCA) to create a comprehensive theoretical model of the complex dynamics and distinct configurations of factors that lead to the outcomes targeted by a BPI; and (2) Systems Dynamics Modeling (SDM) to refine the theory of drivers and barriers to the BPI goals. The research outcomes of this project include the refinement of institutional change theories that advance women faculty in engineering and identify barriers and areas that can be leveraged for women’s success.The goals of this two-phase project are to (1) test the capabilities of QCA and SDM in refining theories for institutional change, and (2) innovate in the translation of qualitative evidence into quantitative performance measures that could support the complex system modeling of BPIs impact. This project focuses on an exemplary, well-established BPI case: the ADVANCE initiatives to influence the success of women faculty in engineering. In phase 1, Acker’s Inequality Regimes will be used as a theoretical framework, and publicly available data will be collected from 15 research one (R1) institutions that were early ADVANCE grantees and 15 comparable institutions that were not. Qualitative data will be transformed into quantitative measures through content analysis and discourse analysis. QCA models could identify the different theoretical paths leading to outcomes related to the recruitment and retention of women, particularly women of color. In phase 2, the theory of ADVANCE impact will be further refined through SDM. First, by identifying dynamics in the system illustrated in Causal Loop Diagrams (CLDs) through qualitative data collected from interviews with women faculty and administrators from a subset of the selected institutions in phase 1; and second, by enriching and strengthening the developed CLDs through Group Based Modeling performed in focus groups. The research outcomes of this project will include (1) refined theories of institutional change for the advancement of women faculty in engineering, including potentially new and confirmed causal relationships, as well as identification of persisting barriers and points of leverage for women’s success, (2) methodological innovations in translating qualitative data to quantitative performance measures, and the use of complex systems methods to study institutional change. The project results will be shared with practitioners through webinars, virtual workshops, and participation in relevant summits and conferences, in particular those appealing to the ADVANCE community, such as AIM and ARC, as well as women in engineering networks, such as WEPAN.This project is supported by NSF's EDUCore 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.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.
在过去的几十年里,在扩大参与倡议(BPI)方面进行了大量投资,旨在增加边缘群体对工程学的参与。然而,影响BPI成功的因素过多,以及BPI面临的持续挑战,使对其影响的有力把握变得更加复杂。不了解使BPI有效的各个方面,限制了它们进行体制变革的潜力。高校内部经常实施BPI,这是一个复杂的系统,具有复杂的多人和多因素之间的动态相互作用。因此,为了衡量BPI的影响,有必要采用承认这种动态复杂性的系统方法。本项目采用了两种成熟的复杂系统方法,以带来理论和实践价值,以利用BPI在高等教育机构中的影响:(1)定性比较分析(QCA),创建导致BPI目标结果的复杂动态和不同因素配置的综合理论模型;(2)系统动力学建模(SDM),完善BPI目标的驱动因素和障碍理论。该项目的研究成果包括完善制度变迁理论,促进女性工程学教师的发展,并确定可用于女性成功的障碍和领域。这个分两个阶段的项目的目标是(1)测试QCA和SDM在完善制度变革理论方面的能力,以及(2)在将定性证据转化为量化绩效衡量标准方面进行创新,以支持BPI影响的复杂系统建模。这个项目的重点是一个模范的、公认的公众宣传局案例:影响工程学女教员成功的先行举措。在第一阶段,Acker的不平等制度将被用作一个理论框架,公开可用的数据将从15个研究一(R1)机构收集,这些机构是早期获得预付款的机构,以及15个不是预付款的可比机构。定性数据将通过内容分析和话语分析转化为定量测量。QCA模型可以确定导致与招募和留住妇女,特别是有色人种妇女有关的结果的不同理论路径。在第二阶段,将通过SDM进一步完善提前影响理论。首先,通过在第一阶段通过对部分选定机构的女性教职员工和管理人员的访谈收集的定性数据,确定因果环图(CLD)中所示的系统动态;第二,通过在重点小组中进行的基于群体的建模,丰富和加强已开发的CLD。该项目的研究成果将包括(1)完善的制度变革理论,以促进工程学女教师的进步,包括潜在的新的和已证实的因果关系,以及确定女性成功的持久障碍和杠杆点,(2)将定性数据转化为定量绩效衡量的方法创新,以及使用复杂系统方法研究制度变革。项目成果将通过网络研讨会、虚拟研讨会和参与相关峰会和会议与实践者分享,特别是那些吸引先进社区的峰会和会议,如AIM和ARC,以及工程网络中的女性,如WEPAN。该项目由NSF的EDUCore Research(ECR)计划支持。ECR计划强调基础STEM教育研究,以产生该领域的基础知识。这一奖项反映了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,认为值得支持。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Juan Cruz其他文献
Computational thinking in pre-university education
大学前教育中的计算思维
- DOI:
10.1145/3012430.3012490 - 发表时间:
2016 - 期刊:
- 影响因子:0
- 作者:
F. García;Juan Cruz - 通讯作者:
Juan Cruz
Knowledge Discovery in Virtual Worlds Usage Data: approaching Web Mining concepts to 3D Virtual Environments
虚拟世界使用数据中的知识发现:将 Web 挖掘概念应用于 3D 虚拟环境
- DOI:
- 发表时间:
2013 - 期刊:
- 影响因子:0
- 作者:
Juan Cruz;Roberto Therón;Emiliana Pizarro Lucas;F. García - 通讯作者:
F. García
Comparing Natural Language Processing and Quantum Natural Processing approaches in text classification tasks
比较文本分类任务中的自然语言处理和量子自然处理方法
- DOI:
10.1016/j.eswa.2024.124427 - 发表时间:
2024 - 期刊:
- 影响因子:8.5
- 作者:
David Peral;Juan Cruz;F. García - 通讯作者:
F. García
Research Advances on User Interactions in Social Media Using Data Science Approaches
使用数据科学方法进行社交媒体用户交互的研究进展
- DOI:
10.3390/app122110929 - 发表时间:
2022 - 期刊:
- 影响因子:0
- 作者:
Felicidad García;Juan Cruz - 通讯作者:
Juan Cruz
Developing a Research Method to Analyze Visual Literacy Based on Cross-Cultural Characteristics
开发基于跨文化特征的视觉素养分析研究方法
- DOI:
- 发表时间:
2018 - 期刊:
- 影响因子:0
- 作者:
Felicidad García;José Gómez;Roberto Therón;Juan Cruz;J. C. Sánchez - 通讯作者:
J. C. Sánchez
Juan Cruz的其他文献
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{{ truncateString('Juan Cruz', 18)}}的其他基金
Collaborative Research: Rising Doctoral Institute
合作研究:瑞星博士研究所
- 批准号:
2029784 - 财政年份:2021
- 资助金额:
$ 20.27万 - 项目类别:
Standard Grant
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