Social Wearables: Enhancing Girls' Computational Learning and Motivation

该奖项采用创新的方法来解决一个持续的，普遍的和持久的社会问题：女性在计算机职业中的代表性仍然严重不足。该项目针对的是中学年龄的女孩，因为这是她们中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候。该项目将设计，开发和部署一个为期一周的经验，重点是中学女生，针对这个问题与教学技巧和技术的新颖组合。该项目将使用可穿戴计算设备来支持女孩的社交互动，因为她们一起学习计算和解决技术挑战。该项目的目标是提高女孩对计算能力的兴趣、认知能力和参与。此外，该项目旨在增加女孩的计算社区意识，使追求计算技能与她们的身份和生活更加相关，并有助于继续参与计算。该项目将每年四次与社会经济多样化的露营者一起部署为期一周的体验。该项目还将开发一个“盒装方案"工具包，供希望为女孩提供类似体验的其他人广泛使用。计划中的研究将确定在真人角色扮演的背景下使用社交可穿戴构建的为期一周的体验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%的参与者将是低收入，第一代大学生，或在高等教育中代表性不足。学生将通过与萨利纳斯山谷，教育伙伴关系中心和帕亚罗山谷联合学区的一级学校的长期合作伙伴关系招募，其中82%的学生是西班牙裔/拉丁裔，42%是英语学习者，73%有资格获得免费或减少午餐。研究问题是：1）建议的经验增加女孩的自我报告的能力，自我效能，并在计算技能和职业的兴趣？以及2）所提出的经验是否会导致基于活动的证据，证明在群体社会水平上的学习和计算技能的整合？该项目将使用混合方法，基于设计的研究方法，这是一个迭代的设计过程，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。将通过观察、访谈、焦点小组、调查和工作人员日志收集数据。将使用频率、平均值和离散度指标分析定量数据，并将其应用于两个时间点的调查数据。Pearson相关系数将用于描述连续因素之间的双变量关系。ANOVA将评估各组之间的连续测量是否存在显著差异。定性数据将使用持续比较法进行分析。该奖项由推进非正式STEM学习（AISL）计划资助，该计划旨在推进非正式环境中STEM学习设计和开发的新方法和基于证据的理解。这包括提供多种途径，以扩大获取和参与STEM学习经验。该奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

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.