Collaborative Research: Improving the Validity and Reliability of Creativity Ratings in Engineering Design

协作研究：提高工程设计创造力评级的有效性和可靠性

• 批准号: 1727849
• 负责人: Scarlett Miller
• 金额: $ 21.41万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-08-01 至 2020-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1727849&HistoricalAwards=false
• 关键词: Collaborative; Research; Improving; Validity; Reliability

Without creativity, there is no potential for innovation. Consequently, creativity is seen as an essential component of engineering design. Numerous creativity metrics have been developed to assess the creativity of designs people produce. Such metrics are important for assessing business and engineering practices, a key part of improving US innovation and economic competitiveness. However, existing metrics are often scattered across different, specialized domains and it is difficult to validate their ability to accurately measure the creativity of the wide variety of engineered solutions that are produced. In addition, past research provides limited guidance on how to use and validate creativity metrics for a given design problem. This has led to universally applying metrics without systematic assessment of where and when a given metric is appropriate for a given task. This award supports fundamental research into how to evaluate the effectiveness of different creativity metrics for different types of products or services. This project does so by unifying statistical models that can experimentally validate how well different creativity metrics perform across design domains. Thus, the work will impact society by providing a verifiable method for identifying what does and does not improve creativity. Because creativity and innovation are the drivers of economic success, the work has the opportunity to drive design innovation and, as a bi-product, help stimulate the economy. In addition, the unified statistical framework developed as part of the research will advance the field of engineering design and applied mathematics by providing evidence on the utility of this approach for measuring accuracy and precision. The research involves several disciplines including engineering, psychology and applied mathematics. The multidisciplinary approach will help broaden participation of underrepresented groups in research.The technical objectives of this project are to: (1) evaluate the effectiveness of creativity metrics through the development of a unified statistical framework that combines two techniques--the minimax conditional entropy principle and the Lovasz-Bregman Divergence--to compare the accuracy and precision of different metrics for a given problem; and (2) experimentally validate a methodology for validating the transfer of creativity metrics across different design domains to identify metrics that are robust across different applications within design and systems engineering via variance and confidence measures of the Lovasz-Bregman Divergence. The results from this project will advance the field of engineering by developing a unified method of measuring and comparing mathematical, computational, and human-judgment models of creativity. This new knowledge will provide a rigorous foundation upon which to build and verify methods of design creativity across a wide variety of design disciplines (e.g., arts and architecture, psychology, engineering, business).

没有创造力，就没有创新的潜力。因此，创造力被视为工程设计的重要组成部分。已经开发了许多创造力指标来评估人们生产的设计的创造力。这样的指标对于评估商业和工程实践非常重要，这是改善美国创新和经济竞争力的关键部分。但是，现有的指标通常散布在不同的专业领域，很难验证其准确测量所产生的各种工程解决方案的创造力的能力。此外，过去的研究提供了有关如何使用和验证给定设计问题的创造力指标的有限指导。这导致普遍应用指标，而没有系统地评估给定指标适合给定任务的何处和时间。该奖项支持有关如何评估不同类型的产品或服务的不同创造力指标有效性的基础研究。该项目通过统一统计模型可以实验验证不同创造力指标在设计域的表现如何。因此，这项工作将通过提供可验证的方法来识别有什么作用和不改善创造力的方法来影响社会。由于创造力和创新是经济成功的驱动力，因此这项工作有机会推动设计创新，作为一项双层产品，有助于刺激经济。此外，作为研究的一部分而开发的统一统计框架将通过提供有关该方法的实用性来衡量准确性和精确度的实用性来推动工程设计和应用数学领域。该研究涉及几个学科，包括工程，心理学和应用数学。 The multidisciplinary approach will help broaden participation of underrepresented groups in research.The technical objectives of this project are to: (1) evaluate the effectiveness of creativity metrics through the development of a unified statistical framework that combines two techniques--the minimax conditional entropy principle and the Lovasz-Bregman Divergence--to compare the accuracy and precision of different metrics for a given problem; （2）实验验证一种方法，用于验证创造力指标在不同设计域中的传递，以识别设计和系统工程中通过方差和置信度divergence的置信度的指标。该项目的结果将通过开发一种统一的测量和比较数学，计算和人类判断性创造力模型来推动工程领域。这些新知识将为建立和验证各种设计学科（例如艺术和建筑，心理学，工程，商业）的设计创造力的方法提供严格的基础。

项目成果

Interpreting Idea Maps: Pairwise Comparisons Reveal What Makes Ideas Novel

• DOI: 10.1115/1.4041856
• 发表时间: 2018-12
• 期刊: Journal of Mechanical Design
• 影响因子: 3.3
• 作者: Faez Ahmed;S. Ramachandran;M. Fuge;Samuel T. Hunter;Scarlett R. Miller

Design Variety Measurement using Sharma-Mittal Entropy

使用 Sharma-Mittal 熵设计品种测量

• DOI: 10.1115/1.4048743
• 发表时间: 2020
• 期刊: Journal of Mechanical Design
• 影响因子: 3.3
• 作者: Ahmed, Faez;Ramachandran, Sharath Kumar;Fuge, Mark;Hunter, Samuel;Miller, Scarlett
• 通讯作者: Miller, Scarlett

Unpacking Subjective Creativity Ratings: Using Embeddings to Explain and Measure Idea Novelty

• DOI: 10.1115/detc2018-85470
• 发表时间: 2018-08
• 作者: Faez Ahmed;M. Fuge;Samuel T. Hunter;Scarlett R. Miller

Measuring, Learning and Optimizing Design Variety using Herfindahl Index

使用赫芬达尔指数测量、学习和优化设计多样性

• 发表时间: 2019
• 期刊: ASME 2018 International Design Engineering Technical Conferences & Design Conference
• 作者: Ahmed, F.;Ramachandran, S.K.;Fuge, M.;Hunter, S.;Miller, S.R.
• 通讯作者: Miller, S.R.

Calibrating Novelty Metrics Using Human Raters: A Case Study

使用人类评估者校准新颖性指标：案例研究

• 发表时间: 2019
• 期刊: ASME 2018 International Design Engineering Technical Conferences & Design Conference
• 作者: Ramachandran, S.K.;Ahmed, F.;Fuge, M.;Hunter, S.;Miller, S.R.
• 通讯作者: Miller, S.R.