CAREER: Promoting Metacognition in Visual Analytics

数据驱动的决策要求参与决策的人对要收集的数据、收集和分析数据的方法以及对结果的解释做出一系列选择。认知、文化和数据偏差可能会在每个阶段干扰这些过程，这就要求数据分析师在工作时深思熟虑和反思。这个项目的目标是帮助分析人员通过工具减少他们的偏见，这些工具可以帮助他们使用元认知或思考来批判性地评估他们的思维过程。元认知将成为开发工具功能的指导思想，帮助分析师意识到可能的偏见。对元认知的研究表明，它在其他教育和分析环境中也很有帮助；本项目将使用这些研究的想法来开发识别潜在偏差的方法，并提供帮助分析人员避免偏差的活动。项目团队还将创建教育材料，并与非营利伙伴组织合作，帮助公众更深入地思考他们自己的分析策略，以及如何改进它们。这个项目将运用元认知理论来解决人类的偏见，并在个人层面上改进决策过程。该项目围绕四个研究重点展开。研究人员将首先组织元认知理论，并将其转化为视觉分析中元认知干预的可操作设计空间（推力1）。接下来，研究人员将与非营利伙伴组织合作，共同设计和开发一套元认知干预措施（Thrust II），并在一系列实验室实验（Thrust III）中评估这些干预措施。最后，研究人员将在元认知干预的案例研究部署中评估经验发现转化为现实世界功效的程度（Thrust IV）。这项工作将测试元认知干预，当成功地应用于数据驱动的决策时，是否可以提高对分析结果技术准确性的认识，并在数据分析中培养更周到、对社会负责和勤奋的实践。该奖项反映了美国国家科学基金会的法定使命，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。

Data-driven decision-making requires the people engaged in it to make a number of choices about the data to collect, and the methods for collecting it and analyzing it, as well as the interpretation of the results. Cognitive, cultural, and data biases can interfere with these processes at every stage, requiring data analysts to be thoughtful and reflective as they do their work. This project’s goal is to help analysts reduce their biases through tools that help them critically assess their thought processes using metacognition, or thinking about thinking. Metacognition will be a guiding idea for developing tool features that help analysts be aware of possible biases. Studies of metacognition have shown that it can be helpful in other educational and analysis settings; this project will use ideas from those studies to develop methods that identify potential biases and present activities to help analysts avoid them. The project team will also create educational materials and work with non-profit partner organizations to help the general public think more deeply about their own analytic strategies and how they might be improved. This project will apply theories of metacognition to address human biases and improve decision-making processes on an individual level. The project is structured around four research thrusts. The researchers will first organize theories of metacognition and translate them into an actionable design space of metacognitive interventions in visual analytics (Thrust I). Next, the researchers will work alongside non-profit partner organizations to co-design and develop a suite of metacognitive interventions (Thrust II) and evaluate those interventions in a series of laboratory experiments (Thrust III). Finally, the researchers will assess the extent to which empirical findings translate to real-world efficacy in a case study deployment of metacognitive interventions (Thrust IV). This work will test whether meta-cognitive interventions, when successfully applied in data-driven decision-making, can both boost awareness of the technical accuracy of analytic results and foster more thoughtful, socially accountable, and diligent practices in data analysis.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.