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

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.

Pedagogy to Guide the Next 70 Years of SOPHE and 150 Years of American Public Health

“…Carroll et al (2022) Hands-on integrated workshops, incorporating the perspectives of multiple disciplines, sectors, and stakeholders, are used to train public health students to synthesize and apply knowledge in order to solve public health problems in real-time (Sibbald et al, 2022). The need to convert to online education during the COVID pandemic provided the opportunity for one school to redevelop its MPH introductory biostatistics course into an asynchronous data analysis course employing problem-based learning, helping students develop holistic approaches to using data for public health decision making (Ellis, 2022).…”