Discourse to Improve Student Conceptual Understanding of Statistics in Inclusive Settings

在包容性环境中提高学生对统计概念理解的讨论

• 批准号: 2314358
• 负责人: Jennifer McNally
• 金额: $ 39.15万
• 依托单位: Curry College
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2026-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2314358&HistoricalAwards=false
• 关键词: Discourse; Improve; Student; Conceptual; Understanding

This project aims to serve the national interest by investigating the conditions under which improved student learning occurs in introductory statistics classes. Traditional approaches to teaching statistics focus on theoretical models that describe the features of sampling distributions. Research has reported that implementing a different approach, called Simulation-Based Inference (SBI), enhances students’ conceptual development of statistics. The SBI approach has also been shown to reduce achievement gaps for students of color and students with learning disabilities and executive functioning challenges. This project aims to identify the qualities of instructional practice in inclusive SBI classes that increase student-to-student and instructor-to-student discourse and further enhance the development of students’ conceptual understanding. The project is expected to develop an online compendium of audio-visual and text resources to support instructors’ implementation of an SBI approach to teaching. The long-term goals of the project are to contribute to the professional development of statistics instructors, who will in turn support their students’ development of conceptual understanding of introductory statistics ideas.This project will systematically investigate the affordances of the simulation-based inference approach to the post-secondary, algebra-based introductory statistics course for students, particularly students with learning and attention disabilities and other students who have been excluded from the scholarship of the discipline. Three goals guide the work of this project. First is to identify and explicate the instructional practices that support students with learning disabilities to access the content in these introductory statistics courses. Second is to identify and explicate students’ statistical conceptions – both productive and less productive – that arise in an introductory simulation-based inference statistics course. Third, and finally, is to develop resources for statistics instructors that will enhance their ability to listen for and productively respond to students’ conceptions in real time. The project team will disseminate these online resources through a growing network of instructors who are using the SBI approach. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through its Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools.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.

该项目旨在通过调查统计入门课程中提高学生学习水平的条件，为国家利益服务。传统的统计学教学方法侧重于描述抽样分布特征的理论模型。研究报告称，实施一种不同的方法，称为基于模拟的推理（SBI），可以增强学生对统计学的概念发展。SBI方法也被证明可以减少有色人种学生和有学习障碍和执行功能障碍的学生的成绩差距。本项目旨在确定包容性SBI课堂教学实践的质量，以增加学生对学生和教师对学生的话语，并进一步加强学生概念理解的发展。预计该项目将开发一个在线视听和文本资源纲要，以支持教师实施SBI教学方法。该项目的长期目标是促进统计讲师的专业发展，他们将反过来支持学生对入门统计思想的概念性理解的发展。该项目将系统地研究基于模拟的推理方法在高等教育、基于代数的统计学入门课程中的应用，特别是有学习和注意力障碍的学生以及其他被排除在该学科奖学金之外的学生。三个目标指导这个项目的工作。首先是确定和阐明支持有学习障碍的学生访问这些统计学入门课程内容的教学实践。其次是识别和解释学生在基于模拟的推理统计入门课程中产生的统计概念——既有生产性的，也有生产性的。第三，也是最后，是为统计讲师开发资源，以提高他们实时倾听和有效回应学生概念的能力。项目小组将通过越来越多使用SBI方法的教员网络传播这些在线资源。NSF IUSE: EDU项目支持研究和开发项目，以提高所有学生STEM教育的有效性。通过其参与学生学习轨道，该计划支持有前途的实践和工具的创建，探索和实施。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。