Improving Data Literacy in Undergraduate Biology Education

该项目旨在通过使用新的教材来提高生命科学本科生的数据科学素养，这些教材将使用计算工具结合数据分析和可视化，从而为国家利益服务。本科生物实验练习将通过要求更多的批判性和定量思维来改进，以完成练习。这些以数据为中心的实验室改进将出现在学生学习的各个层面。虽然练习仍然会说明相同的生物学概念，但通过在学习活动中包括数据、描述性统计、电子表格应用程序和数据可视化工具，数据科学将与练习相结合。在生物学课程的第一年和第二年，学生将学习管理、解释和可视化数据。学生将接受使用基本计算机工具的培训。随着学生在生物学训练中的进步，这些模块将整合编程语言以及更复杂的数据分析活动。这些练习将促进定量素养和批判性思维的发展和使用，这也将帮助学生对基础生物学概念有更深的理解。该项目的研究结果将指导本科生物学课程的进一步改进，并可能被其他STEM领域所采用。生物学专业的学生通常会避开数学和统计学课程，这些课程可以帮助他们加深对生物科学的理解，同时为他们在生物技术行业从事数据丰富的职业做好准备。该项目的目标是通过引入技术增强的以数据为中心的实验室来改变当前的生物学课程，学生可以在实验室中应用数学和统计概念。学生将通过学习如何使用计算工具来可视化生物学中的抽象概念和学习数据科学的基础知识而受益。这些变化将包括引入尺度转化的概念，因为生物学通常以对数尺度发生，如在细菌生长、病毒传播、pH值和基因表达中观察到的那样。学生将学习对数变换可以将这些数据规范化，用于基本统计。通过引入转换的实际应用，以及学习如何使用更复杂的软件进行有用的参数测试，如方差分析和回归分析，学生在生物学背景下应用和解释数据的理解和能力将得到增强。这种改进将增强生物学概念，同时也提高了定量和技术推理能力。这项研究将通过比较各科、各科之间和不同年级的生物和数据理解的前测和后测来评估学生的学习情况，以便跟踪学生在课程中的进步情况。该项目将为改进STEM教育奠定基础，并可在现有课程中实施，以便其他本科院校采用。NSF IUSE: EHR计划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。

This project aims to serve the national interest by increasing data science literacy for life science undergraduate students using new teaching materials that will incorporate data analysis and visualization using computational tools. Undergraduate biology laboratory exercises will be improved by requiring greater critical and quantitative thinking in order to complete the exercises. These data-centric laboratory enhancements will occur at all levels of student learning. While the exercises will still illustrate the same biological concepts, data science will be integrated with the exercises by including data, descriptive statistics, spreadsheet applications, and data visualization tools in the learning activities. In the first and second years of the biology program, students will learn to manage, interpret, and visualize data. Students will be trained in using basic computing tools. As students progress through their biology training, the modules will integrate programming languages as well as more sophisticated data analytic activities. The exercises will facilitate the development and use of quantitative literacy and critical thinking that will also help students gain a deeper understanding of the foundational biological concepts. Findings from this project will guide further curricular improvements in undergraduate biology courses and can potentially be adapted by other STEM fields.Biology majors often avoid mathematics and statistics courses that could aid them in advancing their understanding in biological science while preparing them for data-rich careers in the biotechnology industry. The goal of this project is to transform the current biology curricula by introducing technology-enhanced data-centric laboratories in which students apply mathematical and statistical concepts. Students will benefit by learning how to use computational tools to visualize abstract concepts in biology and by learning the fundamentals of data science. Such changes will include the introduction of the concept of scale transformation, as biology often occurs on a log scale, as observed in bacterial growth, viral spread, the pH scale, and gene expression. Students will learn that log transformations can normalize these data for basic statistics. Students’ understanding and ability to apply and interpret data in a biological context will be enhanced through the introduction of the practical application of transformations and learning how to perform helpful parametric tests like analysis of variance and regression with more complex software. Such improvements will enhance biological concepts while also advancing quantitative and technological reasoning skills. The study will assess student learning by comparing pretests and posttests of biological and data understanding within sections, among sections, and among years so that student progression can be tracked as they advance through the curriculum. This project will lay the groundwork for institutional STEM education improvements that can be implemented in existing courses enabling adoption by other undergraduate institutions. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the 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.