SBIR Phase I: Mapping a Pathway to College Using Predictive Analytic Modeling and Decision Support

SBIR第一阶段项目支持为期六个月的研发，为5至12年级的学生及其家庭开发目标设定和规划软件工具，与目前的财务规划或旅行规划工具没有什么不同。学生和家庭将受益于基于预测的目标设定，以及一个早期预警系统，该系统可以在学生偏离教育目标时发出警告，并提供基于证据的项目建议，帮助学生回到目标的轨道上。在美国的教育系统中导航是复杂的，对于第一代大学申请者和新移民学生和家庭来说更是如此。在九年级到大学一年级之间，50%的美国学生放弃了接受高等教育的道路，尽管研究表明，没有高等教育文凭的学生无法挣到维持生活的工资。今天，几乎每一所美国学校都提供电子成绩单和家长门户网站，与学生和他们的家人分享学生的成绩数据。这个由sbir赞助的工具将与这些现有门户无缝集成，为一个超过15年没有变化的系统提供增值功能。众所周知，辅导员与学生的比例为471:1，而且获得支持的机会分布不均（比如为那些负担得起的人提供私人咨询服务），这样的技术可能会很好地成为美国学校的平衡工具。SBIR的支持为我们提供了技术转移的机会，将我们在财务规划和商业实践方面的知识转化为纯粹基于数据分析和最佳实践的教育规划和目标设定。这项由深圳研究局赞助的创新利用了商业智能和决策支持智能的进步，并将其应用于教育。这是一个全新的市场工具，具有数据图形显示、进度图、预测分析、基于研究和定制的干预措施，与改善的学生成绩有关，所有这些都在美国广泛使用的家长门户系统中。这个网络和移动支持的工具监控性能和进度，与今天为健康爱好者提供的移动腕带设备没有什么不同。在最初的6个月融资后，该项目将确定用于分析目的的数据集的适当组合，将开发使用去识别学生数据的预测分析模型，将开发一个数据可视化仪表板，在学校网络平台上展示这一前瞻性工具的力量，并将与客户就其兴趣水平、易用性和预测结果的准确性进行反馈会议。使用的方法将包括多元回归，逻辑回归和描述性分析。预测准确度将以逻辑回归及ROC曲线分析评估。

The SBIR Phase I project supports six months of R/R & D to develop a goal-setting and planning software tool for students from 5th to 12th grade and their families, not unlike current tools for financial planning or trip planning. Students and families will benefit from the power of prediction-based goal setting as well as an early warning system that indicates when students are off track of their education goal, and evidence-based program suggestions to get students back on track of their goal. Navigating the education system in the U.S. is complex, even more so for first-generation college seekers and new immigrant students and families. Between 9th grade and the first year of college, 50% of America's students fall off the path toward higher education even as research shows that students cannot make a living wage without a post-secondary diploma. Today, nearly every U.S. school offers an electronic grade book and a parent portal that shares student performance data with students and their families. This SBIR-sponsored tool would integrate seamlessly with these existing portals to offer added-value features to a system that has not changed in over 15 years. With notoriously poor counselor-to-students ratio of 471:1, and with the uneven distribution of access to supports (such as private counseling services for those who can afford it), technology such as this may very well serve as a leveling instrument in U.S. schools. SBIR support provides the opportunity for technology transfer of what we know about financial planning and business practices to inform education planning and goal-setting based purely on data analytics and best practices.This SBIR-sponsored innovation harnesses the advances of business intelligence and decision support intelligence and applies it to education. This is a new-to-the-market tool with graphic displays of data, progress mapping, predictive analytics, research-based and customized interventions associated with improved student outcomes, all within parent portal systems that are widely used across the U.S. This web and mobile-enabled tool monitors performance and progress, not unlike what the mobile wrist band devices that offer health enthusiasts today. After initial 6 months of funding, the project will have determined proper alignment of data sets for analytic purposes, will have developed predictive analytic models using de-identified student data, will have developed a data visualization dashboard that showcases the power of this forward-looking tool on school web-based platforms, and will have conducted feedback sessions with customers on their interest level, ease of use, and accuracy of predictive outcomes. The methods used will include multiple regression, logistic regression and descriptive analysis. Prediction accuracy will be evaluated by logistic regression and ROC curve analysis.