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CAREER: Synthesizing Neuroimaging and Data Driven Approaches to Discover Inspirational Examples in Design

职业：综合神经影像和数据驱动的方法来发现设计中的鼓舞人心的例子

基本信息

批准号：
2145432
负责人：
Kosa Goucher-Lambert
金额：
$ 58.05万
依托单位：
University of California-Berkeley
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：
2022-01-01 至 2026-12-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2145432&HistoricalAwards=false
关键词：
CAREER Synthesizing Neuroimaging Data Driven

项目摘要

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).The goals of this Faculty Early Career Development (CAREER) project are: (1) to understand the behaviors and cognition that enable engineering designers to find and utilize inspiring examples in their technical work; and (2) to use this knowledge to develop new data-driven tools to assist in the process of automated inspiration discovery. Designers across industries, ranging from engineering to architecture and animation, increasingly utilize intelligent tools to find inspirational examples. Such tools can track designers’ real-time progress and use this information to predict and return inspiring examples to the designer. Critical to our nation’s competitive advantage, such examples enable designers to ultimately develop more creative and higher quality solutions (e.g., geometric styling that is more attractive to users, analogous systems that improve functional performance). This project will develop a novel computational design tool that recognizes free-form engineering sketches, text descriptions, and 3D models and uses these inputs to infer the ideas and intentions of a designer; in turn, the tool will return examples that are predicted to be inspiring to the designer. An initial version of this tool will be created and used in behavioral and neuroimaging studies with student and professional designers, in which participants will solve real engineering design challenges. Behavioral and neuroimaging data will be used to answer fundamental questions about which types of inspirational examples are most helpful and why. In addition to the primary research activities, an integrated education and outreach plan will increase the number of underrepresented students in STEM through the expansion of a 10-week summer research program for undergraduate students, and through a learning module for middle school students. The project will produce assessments of the outreach activities, as well as deployable models for other institutions to implement similar programs.The research objective of this CAREER project is to demonstrate the combined efficacy of neuroimaging and data-driven techniques to advance the science of 'design via inspiration', enabling designers to use new computational tools in order to discover impactful inspirational stimuli that enhance their creativity and design outcomes. The specific aims of the project are to: (1) characterize brain activation patterns using functional magnetic resonance imaging relating to different representations of design concepts; (2) understand designer behavior during the discovery and application of inspirational stimuli; and (3) develop new, data-driven design tools that support the discovery of inspirational stimuli across a range of interaction modalities (e.g., text descriptions, sketching, 3D models). Research studies will recruit student and professional designers engaged in representative early-stage design ideation tasks in the domain of mechanical engineering. The education and outreach goals of this project are centered on the expansion of a 10-week summer program developed by the PI for underrepresented undergraduate students. The project will create new pedagogical content, assessment methods, and add engagement with a local charter school. Results from the education and outreach work will be packaged and disseminated to the broader community in order to encourage the adoption of similar program models by other institutions.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.

该奖项的全部或部分资金来自《2021年美国救援计划法案》(公共法律117-2)。该学院早期职业发展(CALEAR)项目的目标是：(1)了解使工程设计人员能够在其技术工作中发现和利用鼓舞人心的范例的行为和认知；以及(2)利用这些知识开发新的数据驱动工具，以协助自动灵感发现过程。从工程到建筑和动画，各行各业的设计师越来越多地使用智能工具来寻找鼓舞人心的例子。这类工具可以跟踪设计师的实时进度，并使用这些信息来预测并将鼓舞人心的例子返回给设计师。这些例子对我们国家的竞争优势至关重要，使设计师最终能够开发出更具创意和更高质量的解决方案(例如，对用户更具吸引力的几何造型，改善功能性能的类似系统)。该项目将开发一种新的计算设计工具，该工具可以识别自由形式的工程草图、文本描述和3D模型，并使用这些输入来推断设计师的想法和意图；反过来，该工具将返回预计会给设计师带来灵感的示例。该工具的初始版本将被创建并用于学生和专业设计师的行为和神经成像研究，在这些研究中，参与者将解决实际的工程设计挑战。行为和神经成像数据将被用来回答基本问题，即哪些类型的鼓舞人心的例子最有帮助，为什么。除了初级研究活动外，一项综合教育和推广计划将通过为本科生扩大为期10周的暑期研究计划和通过为中学生开设学习模块来增加STEM中代表性不足的学生人数。该项目将对外展活动进行评估，并为其他机构实施类似项目提供可部署的模型。这一职业项目的研究目标是展示神经成像和数据驱动技术的组合功效，以促进“通过灵感进行设计”的科学，使设计师能够使用新的计算工具，以发现有效的灵感刺激，提高他们的创造力和设计结果。该项目的具体目标是：(1)使用与设计概念的不同表示相关的功能磁共振成像来表征大脑激活模式；(2)了解设计师在发现和应用灵感刺激期间的行为；以及(3)开发新的、数据驱动的设计工具，以支持在一系列交互模式(例如，文本描述、草图、3D模型)中发现灵感刺激。研究性学习将招收从事机械工程领域具有代表性的早期设计构思任务的学生和专业设计师。该项目的教育和外展目标集中在扩大由国际学生联合会为代表不足的本科生制定的为期10周的暑期计划。该项目将创建新的教学内容、评估方法，并增加与当地特许学校的接触。教育和外展工作的结果将被打包并传播给更广泛的社区，以鼓励其他机构采用类似的计划模式。该奖项反映了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，被认为值得支持。

项目成果

期刊论文数量（6）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

Understanding inspiration: Insights into how designers discover inspirational stimuli using an AI-enabled platform

理解灵感：深入了解设计师如何使用人工智能平台发现灵感刺激

DOI：
10.1016/j.destud.2023.101202
发表时间：
2023
期刊：
Design Studies
影响因子：
3.5
作者：
Kwon, Elisa;Rao, Vivek;Goucher-Lambert, Kosa
通讯作者：
Goucher-Lambert, Kosa

Uncovering hidden patterns of design ideation using hidden Markov modeling and neuroimaging

DOI：
10.1017/s0890060423000021
发表时间：
2023-02-27
期刊：
AI EDAM-ARTIFICIAL INTELLIGENCE FOR ENGINEERING DESIGN ANALYSIS AND MANUFACTURING
影响因子：
2.1
作者：
Hu，Mo;McComb，Christopher;Goucher-Lambert，Kosa
通讯作者：
Goucher-Lambert，Kosa

EXAMINING THE BOUNDARY BETWEEN NEAR AND FAR DESIGN STIMULI

检查近处和远处设计刺激之间的界限