SBIR Phase I: Increasing Student Engagement with Scalable Project-based Learning

这个SBIR一期项目致力于构建一个可扩展的基于项目的学习教育技术平台。这个项目中的技术是基于一个聊天机器人，它可以支持与每个学生进行的跨学科对话。该平台旨在为中学生提供课程材料，让他们接触真实而引人入胜的现实世界问题，在几周或几个月的过程中，这些问题聚集在一起，形成对项目提示的一致回应。该项目的目标是建立和完善这一新形式的电子学习平台，该平台有可能极大地提高参与度和学习成果，特别是针对低收入和少数族裔学生。这一目标将通过使符合标准的教育内容有意义并与学生的兴趣相关，并通过使教学材料迎合每个学生的技能水平，以便他们能够按照自己的步伐掌握材料来实现。为了衡量这项技术对学生成绩的影响，这个项目将根据《每个学生成功法案》(ESSA)的指导方针进行最先进的功效研究。这个SBIR第一阶段项目致力于开发一个基于决策树架构的前瞻性教育平台，该平台建立在聊天机器人的基础上，以人工智能(AI)为动力，支持长期的、面向目标的对话。这款高度定制化的聊天机器人旨在使基于项目的学习具有可扩展性，方法是允许学生从一系列选项中选择和定制他们自己的项目主题，然后提供对话解释和练习题，说明共同核心标准如何应用于学生-S项目。这项研究将包括开发和训练自定义神经网络来解释学生的反应和问题。它还将涉及开发算法，以正确识别每个学生的阅读理解水平，并独立地识别概念理解。在了解学生水平的基础上，将开发另一个算法，在学生的S阅读理解水平上选择合适的材料和资源。这些算法将通过用户测试进行改进，对这种教育干预效果的初步研究将在与统计控制相关的研究中进行测试。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This SBIR Phase I project is dedicated to building a scalable project-based learning education technology platform. The technology in this project is based on a chatbot that sustains ongoing, interdisciplinary conversations with each student. The platform is designed to provide middle school students with curriculum materials that expose them to authentic and engaging real-world problems that, over the course of weeks or months, come together to form a cohesive response to a project prompt. The goal of this project is to build and refine this new form of eLearning platform that has the potential to greatly improve engagement and learning outcomes, especially for low-income and minority students. This goal will be achieved by making the standards-aligned educational content meaningful and relevant to the interests of students and by catering the instructional materials to each individual student's skill level so they can move through the materials at their own pace towards mastery. To measure the impact of this technology on student outcomes, this project will involve state-of-the-art efficacy research in accordance with guidelines in the Every Student Succeeds Act (ESSA).This SBIR Phase I project is concerned with developing a forward-looking education platform built around a chatbot that sustains long term, goals-oriented conversations powered by artificial intelligence (AI) and based on a decision tree architecture. The highly-customized chatbot is designed to make project-based learning scalable by empowering students to choose and customize their own project theme from a set of options, and then providing conversational explanations and practice questions that illustrate how Common Core standards apply to the student?s project. This research undertaking will involve developing and training custom neural networks to interpret student responses and questions. It will also involve developing algorithms that correctly identify each student's level of reading comprehension and, independently, conceptual understanding. With an understanding of the student's level, another algorithm will be developed that selects the appropriate materials and resources at the student?s reading comprehension level. These algorithms will be refined through user testing and a preliminary study of the efficacy of this education intervention will be tested in a correlational study with statistical controls.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.