Understanding the Numbers: Quantitative Literacy for Experimental Rigor

理解数字：实验严谨性的定量素养

• 批准号: 10722653
• 负责人: Sara Elizabeth Gombash Lampe
• 金额: $ 8.94万
• 依托单位: OHIO STATE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2026-07-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10722653
• 关键词: Active Learning; Address; Adult; Advisory Committees; Area; Attitude; Behavioral; Competence; Critiques; Data; Data Analyses; Data Reporting; Data Set; Decision Making; Development; Discipline; Doctor of Philosophy; Education; Educational Curriculum; Educational Materials; Educational Status; Educational process of instructing; Educational workshop; Evaluation; Experimental Designs; Failure; Foundations; Funding; Generations; Internships; Knowledge; Knowledge acquisition; Learning; Life; Literacy Programs; Logic; Mathematics; Mission; Molecular; National Institute of Neurological Disorders and Stroke; Neurosciences; Ohio; Performance; Postbaccalaureate; Process; Program Accessibility; Publications; Reading; Reporting; Research; Resources; Role; Science; Scientific Advances and Accomplishments; Solid; Statistical Methods; Students; Training; Training Programs; United States National Institutes of Health; Universities; Visual Literacy; Work; complex data; data literacy; design; education research; education resources; equity, diversity, and inclusion; experience; field study; high school; higher education; improved; innovation; interest; knowledge base; literacy; literate; mathematical ability; nervous system disorder; novel; pedagogical content; preservation; programs; scientific literacy; simulation; skills; statistics; student training; training opportunity; undergraduate student; wasting

PROJECT SUMMARY Quantitative literacy is an essential component of rigorous research. Quantitative literacy incorporates mathematical knowledge, statistics, reasoning, and data and visual literacies to assign meaning to numerical data. In scientific research, being quantitatively literate includes being proficient in contextualizing quantitative datasets and reading and reporting numerical data. Being quantitatively literate is critical to identifying and avoiding weakness in rigor. Our team will design engaging, clear content for the purposes of providing a foundational understanding what quantitative literacy is and its role in scientific rigor, developing strategies and practices in interpreting, analyzing and contextualizing numerical data analysis, and educating learners on best practices in reporting numerical data to promote scientific rigor. Our educational design invites novice, intermediate and advanced learners to review and interact with quantitative literacy concepts through five different learning units. Users have the option to progress through the units covering foundational principles of quantitative literacy, practices in contextualizing data, interpreting statistics, evaluating and utilizing illustrative reports and reporting quantitative data, or can acquire knowledge through independent activities, catering to individualize learning needs. Our expertise and practice in quantitative literacy as well as in building educational programs will be utilized to construct educational experiences that will ultimately improve scientific rigor.

项目摘要 量化素养是严谨研究的重要组成部分。量化扫盲包括 数学知识，统计学，推理，数据和视觉素养，以赋予数字的意义， 数据在科学研究中，具备定量知识包括精通情境化定量 数据集以及阅读和报告数值数据。具备一定数量的识字能力对于识别和 避免僵硬的弱点。我们的团队将设计吸引人的，清晰的内容，以提供一个 基本理解什么是量化素养及其在科学严谨性，制定战略和 解释，分析和情境化数值数据分析的实践，并教育学习者最好的 报告数字数据以促进科学严谨性的做法。我们的教育设计邀请新手， 中级和高级学习者通过五个步骤来回顾和互动量化识字概念 不同的学习单位。用户可以选择通过涵盖以下基本原则的单元进行学习： 量化知识，将数据置于背景中的做法，解释统计数据，评估和利用说明性 报告和报告定量数据，或者可以通过独立的活动获得知识， 个性化的学习需求。我们在量化素养以及构建 教育计划将被用来构建教育经验，最终将提高科学 僵硬