Development and Implementation of a Fully Online Introductory Data Analysis Course to Better Prepare Students for the Public Health Workforce

IF 1.1 Q3 EDUCATION & EDUCATIONAL RESEARCH Pedagogy in Health Promotion Pub Date : 2021-11-24 DOI:10.1177/23733799211060742
Amanda R. Ellis
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引用次数: 2

Abstract

The adversity of the 2020 to 2021 academic year highlighted the need for quality online courses. Challenges of teaching data analysis and helping students meet the Council on Education for Public Health (CEPH) competencies increase in an online environment. To address recent competency changes by the CEPH, a fully online asynchronous course was developed to address the MPH evidence-based approaches to public health competencies and prepare students for the Public Health Workforce. Both problem-based learning and experiential learning theory methodologies informed course design. In the Spring of 2020, with feedback from our Public Health partners, we re-designed a traditional biostatistics course with a holistic approach to data analysis. Students in the class were expected to work individually and as team scientists. They were exposed to data analysis elements from project initiation to dissemination while simultaneously learning methodologic concepts. This article outlines the structure and implementation of an online introductory data analysis course designed for MPH students as a model for re-designing the traditional MPH introductory biostatistics course. Both course development and design are discussed, and evaluations from both students and the instructor are provided.
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开发和实施全在线数据分析入门课程,让学生更好地为公共卫生工作者做好准备
2020至2021学年的逆境凸显了对高质量在线课程的需求。教学数据分析和帮助学生满足公共卫生教育委员会(CEPH)要求的挑战在在线环境中增加。为了应对CEPH最近的能力变化,开发了一个完全在线的异步课程,以解决公共卫生硕士公共卫生能力的循证方法,并为学生加入公共卫生劳动力做好准备。基于问题的学习和体验式学习理论方法论都为课程设计提供了依据。2020年春季,在公共卫生合作伙伴的反馈下,我们重新设计了一门传统的生物统计学课程,采用了全面的数据分析方法。班上的学生被要求以单独和团队科学家的身份工作。他们在学习方法论概念的同时,也接触到了从项目启动到传播的数据分析元素。本文概述了为公共卫生硕士学生设计的在线数据分析入门课程的结构和实施,作为重新设计传统公共卫生硕士生物统计学入门课程的模型。讨论了课程开发和设计,并提供了学生和讲师的评价。
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CiteScore
3.10
自引率
33.30%
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0
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