SBIR Phase I: Thinkquery: Empowering People to Thrive in a Complex World
SBIR Phase I: Thinkquery: Empowering People to Thrive in a Complex World
批准号:
2335521
负责人:
Laura Cabrera
金额:
$27.5万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2024
资助国家:
美国
项目状态:
已结题
起止时间:
2024-01-15 至 2024-12-31
中文摘要
这一小型企业创新研究(SBIR)第一阶段项目赋予个人增强的认知技能,这些技能对于现代世界的成功和创新至关重要。在当今的全球经济中,批判性和创造性思维的能力至关重要,但许多人面临着阻碍其经济竞争力的发展障碍。与现有的认知工具不同,这项创新提供了一种用户友好的、基于聊天的方法,利用每个人的语言技能来培养可转移的思维能力。该解决方案引导用户完成系统的问题解决过程,帮助他们绘制自己的心理模型,培养元认知,并使他们能够挑战假设和偏见。归根结底,这项技术使用户能够更好地理解和应对广泛的挑战。该项目的主要目标是支持社区大学入学的多样化和服务不足的人群。这项技术使学生能够按照自己的节奏学习,将发展课程分解为更短的模块,并根据他们特定的职业抱负定制内容。这种适应性和可获得性有可能改变教育,为广大受众提供灵活有效的学习工具。该团队满足了社会对提高认知技能的迫切需求,不仅提高了个人的前景,还为国家的经济活力做出了贡献。这个小企业创新研究(SBIR)第一阶段项目的重点是使个人能够通过利用机器可解释的数据结构中的差异、系统、关系和前景(DSRP)理论有效地应对21世纪的复杂挑战,并将其集成到视觉结构推荐系统中。技术目标是使用户能够使用一种工具,促进对各种问题和主题的深入探索和理解。该项目的关键组件开发了结合DSRP理论和人工智能(AI)/机器学习(ML)技术的算法,以创建协作过滤和基于内容的过滤,以生成用户特定的问题。该解决方案创建了一个全面的报告架构、编码和统计工具,以验证针对不同使用场景的经验度量。该团队还定义了用例条件和用户体验设计参数,以增强技术的有效性。最初,这个项目的目标是发展教育项目中的多样化、未得到充分服务和处于不利地位的学生,他们经常在大学水平的课程学习中苦苦挣扎。这项创新的可及性是由日常语言作为输入推动的,使其成为一种商业上可行的认知技能培训技术,与现有解决方案相比,摩擦减少,用户友好性更强。该技术解决了与思维导图技术相关的技术挑战和教育障碍,有望对学习和解决问题的能力产生重大影响。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。
英文摘要
This Small Business Innovation Research (SBIR) Phase I project empowers individuals with enhanced cognitive skills essential for success and innovation in the modern world. In today's global economy, the ability to think critically and creatively is crucial, but many people face developmental hurdles that hinder their economic competitiveness. Unlike existing cognitive tools, this innovation offers a user-friendly, chat-based approach that leverages each individual's language skills to cultivate transferable thinking abilities. The solution guides users through a systematic problem-solving process, helping them map their mental models, fostering metacognition, and enabling them to challenge assumptions and biases. Ultimately, the technology equips users to better comprehend and address a wide range of challenges. This project's primary aim is to support the diverse and underserved populations enrolled in community colleges. The technology enables students to learn at their own pace, break down developmental courses into shorter modules, and tailor content to align with their specific career aspirations. This adaptability and accessibility have the potential to transform education, providing a flexible and effective learning tool for a wide audience. The team addresses a pressing societal need for improved cognitive skills, enhancing not only individual prospects but also contributing to the nation's economic vitality.This Small Business Innovation Research (SBIR) Phase I project focuses on enabling individuals to effectively navigate complex challenges in the 21st century by leveraging the Distinctions, Systems, Relationships, and Perspectives (DSRP) Theory within a machine-interpretable data structure integrated into a visual-structural recommender system. The technical objective is to empower users with a tool that facilitates in-depth exploration and understanding of various problems and topics. The project's key components develop algorithms that incorporate DSRP theory and Artificial Intelligence (AI)/Machine Learning (ML) techniques to create collaborative filtering and content-based filtering for generating user-specific questions. The solution creates a comprehensive reporting schema, coding, and statistical tools to validate empirical measures for different usage scenarios. The team also defines use case conditions and user experience design parameters to enhance the effectiveness of the technology. Initially, this project targets diverse, underserved, and disadvantaged students in developmental education programs who often struggle with college-level coursework. The innovation's accessibility, driven by the use of everyday language as inputs, makes it a commercially viable cognitive skills training technology with reduced friction and greater user-friendliness compared to existing solutions. The technology addresses both technical challenges and educational barriers associated with mind-mapping technologies, promising a significant impact on learning and problem-solving capabilities.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.
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SBIR Phase I: Measure What We Treasure: Developing a Structural Cognitive Analytics and Assessment (SCAA) Technology
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批准号:1819733
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项目类别:Standard Grant
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资助金额:$22.4万
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财政年份:2018
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负责人:Laura Cabrera
-
依托单位:
国内基金
海外基金
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