SBIR Phase I: Learnics: Actionable Learning Analytics for the Classroom

SBIR第一阶段项目资助的研究将导致软件和流程的开发，旨在通过为教师提供有关学生学习方式的可操作分析来帮助他们改善教学。通过有针对性的学习分析，该项目将为课堂上的个别教师提供有关学生如何在网络上学习的有用信息。这项高风险研究的重点不是关注目前研究中常见的大规模、州或全国范围的分析，而是开发关于个别学生的分析，供个别教师在课堂上使用。有了这些分析，教师将能够更好地了解他们个别学生的优势和局限性，特别是与他们的课堂相比。该项目将创建软件和算法，利用教师和计算机的优势，让教师专注于学生，而计算机专注于信息和分析。其结果是：为教师提供更好、更有用的信息，帮助学生充分发挥潜力。这项研究将有助于填补一个空白，存在于教师接受有关他们的学生形成信息的方式？在线活动。教师往往对正在发生的实际在线学习体验视而不见，导致错过教育机会和次优教育。该项目将弥合这一差距，并创建教学方法和在线活动，最终实现技术提供的承诺。SBIR第一阶段项目正在资助高风险研究，这些研究将导致软件和算法的开发，通过为教师提供有关学生学习方式的可操作分析来帮助他们改进教学。通过使用有针对性的在线学习分析，该项目将为课堂上的个别教师提供有关学生学习情况的有用信息。目前的研究主要集中在大规模的州或全国范围的分析上，这些分析来得太晚了，而且范围太广，个别教师无法帮助学生。这项高风险研究的重点是开发关于个别学生的分析，供个别教师在课堂上实时使用，并在整个学年中监控这些分析的进展。有了这些分析，教师将能够更好地了解他们个别学生的优势和局限性，特别是与他们的课堂相比。使用机器学习和NLP，这些新的算法和流程将能够更好地确定学习分析，例如学生参与度，数字素养和任务外行为。其结果是：为教师提供自动的、可操作的分析，以帮助学生充分发挥潜力。这项高风险的研究将有助于填补教师接收学生在线活动形成信息的方式中存在的空白。教师往往对正在发生的实际在线学习体验视而不见。该项目将弥合这一差距，并创建教学方法，在线活动和课程，最终实现技术提供的承诺。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 SBIR Phase I project is funding research that will lead to the development of software and processes that are aimed at helping teachers to improve their instruction by providing them with actionable analytics about how their students are learning. Using targeted learning analytics, this project will bring to individual teachers in the classroom useful information about how their students are learning on the web. Rather on focusing on large-scale, state- or nationwide- analytics as is currently common in the research, the focus of this high-risk research is to develop analytics about individual students for use by individual teachers in the classroom. Armed with these analytics, teachers will be able to better understand the strengths and limitations of their individual students, especially as compared to their classroom. The project will create software and algorithms that will exploit the strengths of both teachers and computers by allowing teachers to focus on students, while computers to focus on information and analytics. The result: better, more useful information for teachers to help their students achieve their full potential. This research will help to fill a void that exists in the way teacher receive formative information about their students? online activity. Teachers are often blind to the actual online learning experience that is taking place, leading to missed educational opportunities and suboptimal education. This project will bridge this gap and create instructional methods and online activities that finally realize the promise offered by technology. This SBIR Phase I project is funding high-risk research that will lead to the development of software and algorithms that help teachers improve their instruction by providing them with actionable analytics about how their students are learning. Through the use of targeted online learning analytics, this project will bring to individual teachers in the classroom useful information about how their individual students are learning. Current research focuses on large-scale, state- or nationwide- analytics, which comes years too late and is too broad to be usable by individual teachers to help students. The focus of this high-risk research is to develop analytics about individual students for use by individual teachers in the classroom in real-time, and monitor progress of these analytics throughout the school year. Armed with these analytics, teachers will be able to better understand the strengths and limitations of their individual students, especially as compared to their classroom. Using machine learning and NLP, these new algorithms and processes will be able to better ascertain learning analytics such as student engagement, digital literacy, and off-task behavior, to list a few. The result: automatic, actionable analytics for teachers to assist students in achieving their full potential. This high-risk research will help to fill a void that exists in the ways teachers receive formative information about their students' online activity. Teachers are often blind to the actual online learning experience that is taking place. This project will bridge this gap and create instructional methods, online activities, and curriculum that finally realize the promise offered by technology.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.