Social Wearables: Enhancing Girls' Computational Learning and Motivation

该奖项以创新的方式解决了一个持续、普遍和持久的社会问题：女性在计算机职业生涯中的代表性仍然严重不足。这个项目的目标是中学年龄的女孩，因为这是一个她们中的许多人对追求技术教育和计算机职业失去兴趣和信心的时期。这个项目将设计、开发和部署一个为期一周的体验，以中学女生为重点，通过一种新颖的教学技术和技术组合来解决这个问题。该项目将使用可穿戴计算设备来支持女孩们在一起学习计算和解决技术挑战时的社交互动。该项目的目标是提高女孩的兴趣、感知能力和参与计算能力。此外，该项目旨在增加女孩的计算社区感，使追求计算技能与她们的身份和生活更相关，这有助于继续参与计算。该项目将每年部署四次为期一周的体验，让不同社会经济背景的露营者参加。该项目还将开发一个“盒子里的程序”工具包，供其他希望为女孩提供类似体验的人广泛使用。这项计划中的研究将确定一周的体验，即在真人角色扮演的背景下使用社交可穿戴式构建，是否可以使用计算社区形成的中介过程来积极影响中学女生对计算的参与和兴趣。计算社区被定义为女孩一起参与学习计算、交易资源和知识以及支持成长的过程。研究参与者将包括100名6至9年级的女孩。至少75%的参与者要么是低收入、第一代受过大学教育的人，要么是接受高等教育的人数不足。学生将通过与萨利纳斯山谷、教育合作中心和帕贾罗山谷联合学区的第一标题学校的长期合作伙伴关系进行招生，那里82%的学生是西班牙裔/拉丁裔，42%是英语学习者，73%有资格享受免费或减价午餐。研究问题是：1)被提议的经历是否提高了女孩的自我报告能力、自我效能感以及对计算技能和职业的兴趣？2)拟议的经验是否会导致基于活动的证据，证明计算技能在群体社会层面上的学习和整合？该项目将使用混合方法、基于设计的研究方法，这是一个迭代设计过程，以快速收集和分析数据，并定期与设计团队讨论实践的影响。将使用观察、访谈、焦点小组、调查和员工日志来收集数据。定量数据将使用频率、方法进行分析，分散测量将应用于两个时间点的调查数据。皮尔逊相关系数将被用来描述连续因素之间的二元关系。ANOVAS将评估不同组之间的连续测量是否存在显著差异。该奖项由推进非正式STEM学习计划(AISL)资助，该计划旨在促进对非正式环境中STEM学习的设计和发展的新方法和基于证据的理解。这包括提供多种途径来扩大获得和参与STEM学习经验的途径。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。

This award takes an innovative approach to an ongoing, pervasive, and persistent societal issue: women are still drastically underrepresented in computing careers. This project targets middle school-aged girls because it is a time when many of them lose interest and confidence in pursuing technical education and computing careers. This project will design, develop, and deploy a one-week experience focused on middle school girls that targets this issue with a novel combination of teaching techniques and technology. The project will use wearable computing devices to support girls' social interactions as they learn computing and solve technical challenges together. The goals of the project are to raise interest, perceived competence, and involvement in the computational ability of girls. Additionally, the project aims to increase a sense of computational community for girls that makes pursuing computational skills more relevant to their identities and lives, and that helps continued participation in computing. The project will deploy a one-week experience four times per year with a socioeconomically diverse range of campers. The project will also develop a 'program in a box' kit that can be broadly used by others wishing to deliver a similar experience for girls. The planned research will determine if a one-week experience that uses social wearable construction in the context of live-action role play can use the mediating process of computational community formation to positively impact middle school girls' engagement with and interest in computation. Computational community is defined as girls engaging together in the process of learning computation, trading resources and knowledge, and supporting growth. Research participants will include 100 6th to 9th-grade girls. At least 75% of the participants will be either low income, first-generation college-bound, or underrepresented in higher education. Students will be recruited through the longstanding partnerships with title one schools in the Salinas Valley, the Educational Partnership Center, and in the Pajaro Valley Unified School district, where 82% of the students are Hispanic/Latinx, 42% are English Learners, and 73% are eligible for free or reduced lunch. The research questions are: 1) Does the proposed experience increase girls' self-reported competence, self-efficacy, and interest in computational skills and careers? and 2) Will the proposed experience lead to activity-based evidence of learning and integration of computational skills at the group social level? The project will use a mixed-methods, design-based research approach which is an iterative design process to rapidly collect and analyze data, and regularly discuss the implications for practice with the design team. Data will be collected using observations, interviews, focus groups, surveys, and staff logs. Quantitative data will be analyzed using frequencies, means, and measures of dispersion will be applied to survey data from both time points. Pearson correlation coefficients will be used to describe the bivariate relationship between continuous factors. ANOVAs will assess whether there are significant differences in continuous measures across groups. Qualitative data will be analyzed using a constant comparison method.This award is funded by the Advancing Informal STEM Learning (AISL) program, which seeks to advance new approaches to, and evidence-based understanding of, the design and development of STEM learning in informal environments. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences.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.