SBIR Phase I: A Machine-Learning Tool for Social-Emotional Learning, Development, and Intervention for Remote or Hybrid Child Development Support (COVID-19)

这个小企业创新研究（SBIR）第一阶段项目的更广泛的影响/商业潜力是发现儿童（5-12岁）的社会情感问题，并进行早期干预。最近的COVID-19大流行及其对儿童发育的影响加剧了青少年心理健康问题日益严重的趋势。该项目提出了一个机器学习（ML）系统，该系统可以从与孩子和父母的互动中独立学习，并可以检测潜在的社会情感问题。机器学习系统可以在远程或混合环境下的临床环境之外进行个性化评估和监测。这个小企业创新研究（SBIR）第一阶段项目推进了将算法整合到社交情感技能建设课程中的方法。项目提出：1)基于社会情感功能综合评估的用户细分，2)模块对细分用户的相关性和有效性的相关性，3)收集信息识别社会情感缺陷（红旗）。这些活动可以形成一个反馈循环，为每一个孩子和父母提供建议，实时个性化学习。这些算法从父母和孩子使用这项技术时的行为、社会和情感输入中学习。该系统还将发现与社交和情感缺陷相关的危险信号，促进早期干预。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to detect social-emotional issues in children (ages 5-12) for early intervention. A growing trend in juvenile mental health concerns was exacerbated by the recent COVID-19 pandemic and the associated disruption in child development. This project proposes a machine learning (ML) system that learns from interactions with the child and parent independently and can detect potential social-emotional concerns. The ML system enables personalized evaluation and monitoring outside a clinical setting in a remote or hybrid context.This Small Business Innovation Research (SBIR) Phase I project advances algorithms for integration into a social-emotional skill building curriculum. The project proposes: 1) User segmentation based on a comprehensive assessment of social-emotional functioning, 2) Correlation of the relevancy and effectiveness of modules to segmented users, and 3) Collection of information to identify social emotional deficits (red flags). These activities enable a feedback loop to learn and deliver recommendations for each child-parent dyad, personalizing learning in real-time. These algorithms learn from behavioral, social, and emotional inputs from both the parent and child when they engage with the technology. The system will also detect red flags correlated with social and emotional deficits, promoting early intervention.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.