Integration of Computer-Assisted Methods and Human Interactions to Understand Lesson Plan Quality and Teaching to Advance Middle-Grade Mathematics Instruction

教材的规划和选择是数学教学中最复杂、最重要的组成部分之一。随着在线教学材料的持续激增，学校和教育工作者除了依赖教科书外，还依赖于在线教学材料。虽然开放免费提供的教育资源有好处，但确保其质量和对教师和学生的效用仍然是首要问题。这项研究的一个重要贡献是确定了使用尖端机器学习技术、有效数学教育知识和人类反馈相结合的方法来衡量大量教案的质量。该项目的后期阶段包括就教师的计划实践采访教师，测量教案质量，并分析学生的工作，以提供对中学年级数学教案质量的多角度看法。使用机器学习来衡量教案质量对数学教育领域具有变革的潜力。该项目将确定使用自然语言处理和人类编码的混合方法来分析大量数学教案的方法。该项目以初中数学课为重点，包括教师和学生的数据以及教案文件本身。这项研究有三个研究目的。首先，通过组织一个由主要研究人员和熟练教师组成的专家计划，制定一个共享的概念框架，并指定中学数学优质教案的维度。第二，通过应用最先进的计算机辅助方法(例如，机器学习)和人工编码来分析根据知识共享许可证获得的大量数字教案，来制定和验证捕捉关键维度的措施。第三，进行探索性的顺序混合方法研究，研究教师如何处理、解释和选择信息来制定自己的教案，以及教案的质量如何与学生完成的数学作业相关。混合方法考核教案质量是推进数学教与学研究的一项重要创新。该项目得到了美国国家科学基金会EDU核心研究(ECR)计划的支持。ECR计划强调基础STEM教育研究，以产生该领域的基础知识。这一奖项反映了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，认为值得支持。

Planning and selecting instructional materials is one of the most complex and important components of mathematics teaching. As online instructional materials continue to proliferate, schools and educators are relying on them in addition to textbooks. While there are advantages to open educational resources that are freely available, questions about ensuring their quality and utility to teachers and students remain paramount. An important contribution of this study is identifying ways to measure the quality of large quantities of lesson plans using an integration of cutting-edge machine learning techniques, knowledge of effective mathematics education, and human feedback. Later phases of the project include interviewing teachers about their planning practices, measuring lesson plan quality, and analyzing students' work to provide multiple perspectives on mathematics lesson plan quality in the middle grades. The use of machine learning to measure lesson plan quality holds transformative potential for the field of mathematics education. The project will identify ways to analyze large numbers of mathematics lesson plans using a mixed methods approach of natural language processing and human coding. The project focuses on middle grades mathematics lesson and includes data from teachers and students as well as the lesson plan documents themselves. The study has three research aims. First, to develop a shared conceptual framework and specify dimensions of quality lesson plans for middle-grades mathematics by organizing an expert plan of leading researchers and skilled teachers. Second, to develop and validate measures to capture the key dimensions by applying state-of-the-art computer-assisted approaches (e.g., machine learning) and human coding to analyzing a large volume of digital lesson plans obtained under Creative Commons Licenses. Third, to conduct an exploratory sequential mixed-methods study of how teachers attend to, interpret, and select information to create their own lesson plans, and how lesson plan quality is related to students' completed mathematical work. The mixed methods approach to examining lesson plan quality is an important innovation for advancing research about mathematics teaching and learning. This project is supported by NSF's EDU Core Research (ECR) Program. The ECR program emphasizes fundamental STEM education research that generates foundational knowledge in the field. Investments are made in critical areas that are essential, broad and enduring: STEM learning and STEM learning environments, broadening participation in STEM, and STEM workforce development.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.