Challenges and Opportunities in Evaluating Broadening Participation in Computing: The STARS Evaluation Cohort Model
Challenges and Opportunities in Evaluating Broadening Participation in Computing: The STARS Evaluation Cohort Model
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评估扩大计算参与的挑战和机遇：STARS 评估队列模型
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
Huifang Zuo
中科院分区：
文献类型：
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作者：
A. Rorrer;T. Barnes;J. Payton;Huifang Zuo
美国国家科学基金会通过将BPC作为计算机和信息科学与工程核心计划提案的必要组成部分，传达了扩大参与计算（BPC）的重要性。这一行动号召要求人们共同理解如何通过质量评估实践来展示BPC计划的影响。通过我们对STARS BPC计划进行大规模国家评估的经验，我们注意到评估BPC计划所特有的三个首要挑战：评估成本、衡量纵向计划影响以及获取多地点计划集体影响的可信证据。STARS评价队列模式通过应用一个赋权评价框架来应对这些挑战，该框架仅适用于BPC工作，并通过培训讲习班和提供评价保真度所必需的工具来建设评价能力。在这份经验报告中，我们分享了支持该模型的评估框架，描述了应对BPC评估挑战的方法，并讨论了证据基础和从我们的实践中吸取的教训。此外，我们提出了我们的方法来维持和促进新的队列参与我们正在进行的努力，以发展评估能力，促进基于证据的BPC倡议的理解和传播。
The National Science Foundation has communicated the importance of Broadening Participation in Computing (BPC) by including BPC as a required component of proposals across the Computer and Information Science and Engineering core programs. This call to action creates a need for collective understanding of how to demonstrate the impact of BPC initiatives through quality evaluation practices. Through our experience in conducting a large-scale national evaluation of the STARS BPC program, we have noticed three overarching challenges that are specific to evaluating BPC programs: evaluation costs, measuring longitudinal program impact, and capturing credible evidence for collective impact of multi-site programs. The STARS Evaluation Cohort Model addresses these challenges by applying an empowerment evaluation framework, which is uniquely applicable to BPC efforts, and by building evaluation capacity through training workshops and offering tools essential for evaluation fidelity. In this experience report, we share the evaluation framework that supports the model, describe the approach toward BPC evaluation challenges, and discuss the evidence base and lessons learned from our practice. Additionally, we present our approach to sustaining and catalyzing new Cohort participation in our ongoing efforts to develop evaluation capacity that facilitates the understanding and propagation of evidence-based BPC initiatives.