Exploring Physiological Computing Education in the Alabama Black Belt

生理计算系统有可能通过可穿戴技术造福社会，例如智能手表、电子纺织服装和一般的脑机接口。目前，在计算机科学教育和生理计算的交叉点上，大多数工作都集中在使用生理技术来增强学习体验或预测表现。缺乏研究如何使K-12学生获得设计和构建利用生理传感器的未来技术和应用所需的知识和技能。本项目将设计、开发和实现一个教育生理学计算学习工具，并评估该工具对高中生计算思维技能习得的影响。这项拟议的工作将为计算机科学教育界提供关于如何在K-12教育中最好地利用新的生理传感技术的基础研究。除了为更广泛的研究社区贡献研究成果外，PI团队还将建立一个暑期推广计划，让阿拉巴马州黑带(ABB)的高中生接触到新的脑机接口传感技术。作为STEM学科中强大的计算创新和应用的结果，STEM+C计划支持研究和开发跨学科和跨学科的方法，将计算整合到STEM教与学中，供K-12预科学生在正式和非正式环境中使用。这个试点项目将推进生理传感和数据处理与计算思维的整合。研究人员将使用以用户为中心的方法来确定教育生理计算工具的有效设计。这包括解决与学生和教育工作者对新的生理计算技术的态度和理解有关的知识差距的研究。研究人员将对阿拉巴马州黑带探索计算机科学(ECS)的学生和教育工作者进行半结构化的用户访谈，以增进他们对生理传感技术的感知和心理模型的知识。从这些访谈中获得的见解将为试验低保真原型的迭代设计提供参考。在用户实验期间，将收集学生对每个原型的体验的定性和定量数据。在低保真原型研究期间获得的反馈将指导设计解决方案的开发。该项目将采用数据流和基于块的编程等混合计算机编程方法来开发学习工具。学生的用户研究将被用来评估工具对学生计算实践模式的影响，包括增量和迭代编程、测试和调试、抽象和模块化、表达和提问的计算视角，以及生理计算系统的知识。这个项目将贡献一个为K-12教育设计的基于网络的教育生理计算工具。这个奖项反映了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。

Physiological computing systems have the potential to benefit society through wearable technologies such as smart watches, electronic textile clothing, and brain-computer interfaces in general. Currently, most work at the intersection of computer science education and physiological computing focuses on using physiological technology to augment learning experiences or predict performance. There is a lack of research investigating ways to enable K-12 students in acquiring the knowledge and skills needed to design and build future technologies and applications that leverage physiological sensors. This project will design, develop, and implement an educational physiological computing learning tool, and evaluate the tool's impact on upper secondary student's acquisition of computational thinking skills. The proposed work will provide the computer science education community field with foundational research on how best to leverage novel physiological sensing technologies within K-12 education. In addition to contributing findings to the broader research community, the PI team will build a summer outreach program that exposes high school students from the Alabama Black-Belt (ABB) to novel brain-computer interface sensing technologies. As a result of the powerful innovation and application of computing in STEM disciplines, the STEM+C program supports research and development of interdisciplinary and transdisciplinary approaches to the integration of computing within STEM teaching and learning for preK-12 students in both formal and informal settings. This pilot project will advance the integration of physiological sensing and data processing with computational thinking.Researchers will use a user-centered approach to identify effective designs for educational physiological computing tools. This includes studies that address knowledge gaps related to students' and educators' attitudes and understandings of novel physiological computing technology. Researchers will conduct semi-structured user interviews with Alabama Black Belt Exploring Computer Science (ECS) students and educators to advance knowledge regarding their perceptions and mental models of physiological sensing technologies. Insights gained from these interviews will inform the iterative design of pilot low-fidelity prototypes. Qualitative and quantitative data on students' experiences with each prototype will be collected during user experiments. Feedback gained during the low-fidelity prototype studies will guide the development of design solutions. The project will employ hybrid computer programming approaches such as data-flow and block-based programming for the learning tool development. User studies with students will be used to evaluate the tool influence on students' patterns of computational practice including incremental and iterative programming, testing and debugging, abstracting and modularization, computational perspectives of expressing and questioning, and knowledge of physiological computing systems. This project will contribute a web-based educational physiological computing tool designed for K-12 education.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.