SBIR Phase II: Actionable Learning Analytics for the Classroom

这个小企业创新研究（SBIR）第二阶段项目的更广泛的影响/商业潜力是开发收集、分析和利用学生在线学习活动数据的实用方法，以改善教学和学习。COVID-19导致教育技术的加速采用。教育的新常态可能会更多地融入科技。该项目为教育工作者提供了分析工具，以获得必要的数据洞察力，以设计有效的数字学习体验并充分支持学生。数据分析为许多在线商业组织和企业提供了巨大的价值。这些商业分析用于更好地了解客户，促进期望的客户行为，预测未来的互动并支持许多组织决策。该项目旨在将这些见解提供给教育工作者和学生。在美国有超过300万的教师目前没有实际的方法来收获分析的价值，以深入了解他们为自己的学生设计的在线体验。该项目的目标是为教师提供必要的分析和见解，以使学生负责，提供教学支持，并设计有效的数字课程。这个小企业创新研究（SBIR）第二阶段项目将探索创建自动化流程的方法，从学生的在线学习活动记录中提取关键数据。反过来，该项目寻求将这些数据转化为有用的分析，使教师能够深入了解学生的在线学习体验。该项目可能会改善有针对性的在线学习分析的收集和显示，为教育工作者提供有关学生如何与在线内容互动的关键信息。这些进步将与东斯特劳兹堡大学的博士研究相结合，收集和分析学生的在线学习数据，以创建自动化的“关键学习指标”和“学习经验分数”。该项目将致力于创建一个行业标准，以规范学生在线学习数据的收集、分析和呈现给教育工作者。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 II project is the development of practical methods of collecting, analyzing and utilizing student online learning activity data to improve teaching and learning. COVID-19 caused an accelerated adoption of educational technologies. The new normal of education may be much more infused with technology. This project provides the analytic tools for educators to get the data insights necessary to design effective digital learning experiences and fully support students. Data analytics provide immense value to many online commercial organizations and businesses. These commercial analytics are used to better understand customers, promote desired customer behavior, predict future interactions and support many organizational decisions. This project seeks to make these insights available to educators and students. There are over three million teachers in the United States who currently have no practical way of reaping the value of analytics to gain insight into the online experiences that they are designing for their own students. The objective of this project is to provide teachers with the analytics and insights necessary to hold students accountable, provide instructional support, and design effective digital lessons. This Small Business Innovation Research (SBIR) Phase II project will explore ways to create automated processes that extract key data from student online learning activity records. In turn, the project seeks to translate this data into useful analytics that will offer teachers insights into students’ online learning experience. This project may improve the collection and display of targeted online learning analytics that provide educators with critical information about how students interact with online content. These advances will be coupled with doctoral research studies at East Stroudsburg University to collect and analyze student online learning data in order to create automated “Key Learning Indicators” and “Learning Experience Scores.” This project will work toward creating an industry standard for how student online learning data should be ethically collected, analyzed, and presented to educators.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.