Pedagogical Principles in Implementing a Data Visualization Project in an Undergraduate Public Health Informatics Course

Abstract

Background The Applied Public Health Informatics Competency Model lists “data analysis, visualization, and reporting” as one of the eight competencies when teaching public health informatics. Thus, public health informatics students need to develop knowledge and skills in visualizing public health data. Unfortunately, there is limited work that discusses pedagogical principles that could guide the implementation of pedagogical activities related to data visualization in public health informatics.

Objective This study aimed to introduce, discuss, and reflect on pedagogical principles that were implemented for a data visualization project in an undergraduate public health informatics course.

Methods A reflective teaching approach was used to guide the discussion and reflection on how pedagogical principles were implemented for a data visualization project in an undergraduate public health informatics course. The generic implementation framework (i.e., preimplementation, implementation, and postimplementation) was used to organize the discussion of the course's implementation.

Results Four pedagogical principles were implemented as part of a data visualization project in an undergraduate public health informatics course: scaffolding (i.e., outputs built on top of each other), constructivism (i.e., students apply knowledge and work in teams to create a dashboard), critical consciousness (i.e., embedding social determinants of health (SDOH) in their dashboard), and equity and inclusion (i.e., using a free data visualization software that is easy to use for beginners and is used by public health institutions). Postimplementation reflection revealed areas of improvement, such as enhancing group advising, adding more SDOH variables in the dashboard, and plans for scalability.

Conclusion A data visualization project in an undergraduate public health informatics course could benefit from implementing multiple pedagogical principles. Overall, creating dashboards can be a learning tool to enhance data visualization skills among undergraduate public health informatics students. Dashboards can also emphasize the impact of health disparities and inequities in public health by incorporating the principles of SDOH.

Keywords

public health - public health informatics - education - data visualization - Power BI - strategies for health IT training

Background and Significance

Data visualization refers to the visual representation of data through charts, figures, or animations to make complex data easier to understand.[1] In the context of public health, it is only recently that data visualization in the form of “live dashboards” (i.e., a dashboard that allows users to configure its elements that allow for more interaction) has caught the public's attention. A case in point is the coronavirus disease 2019 (COVID-19) pandemic. At the beginning of the COVID-19 pandemic in January 2020, the creation of the Johns Hopkins University Center for Systems Science and Engineering COVID-19 Dashboard[2] became an important turning point in why data visualization is now an integral part of public health. For instance, it became an important source for media outlets to report updates about the pandemic[3] and it was used by world governments to guide public health actions to control the pandemic.[2]

Data visualization, along with data analysis and reporting, was recognized as early as 2016 by the Public Health Informatics Institute's Informatics Academy as one of the eight core competencies in their Applied Public Health Informatics Competency Model.[4] It is important to note that while the 2009 Competencies for Public Health Informaticians report reflects the need for data visualization skills, it was not considered a core competency at that time.[5] Given the importance of dashboards in communicating public health issues, especially during a public health emergency like the COVID-19 pandemic, there is a need to train future public health practitioners in data visualization.

To date, few works describe principles that could guide the implementation of data visualization as a pedagogical activity in public health courses. For instance, based on the principles of information literacy and science communication, Shanks et al[6] implemented an assignment for undergraduate students to create digital infographics (in the form of static images) to visualize and communicate public health issues to a diverse audience. Moreover, through a health equity lens, Ofrane et al[7] described the implementation of a data-driven policy brief assignment for Master of Public Health (MPH) students. Students were instructed to generate a city-level policy brief based on visualized social determinants of health (SDOH) data found in the City Health Dashboard.[8] Likewise, Borders[9] developed a Tableau-based data visualization project to teach undergraduate public health students how disparities in food accessibility impact health outcomes.

As schools of public health, particularly those offering MPH programs, shift their pedagogical strategies to emphasize authentic assessment (e.g., creating dashboards from real-world data), use of technology for learning (e.g., use of data visualization tools), and teamwork (e.g., creating a dashboard as a group),[10] there is a need to provide public health scholars and educators with pedagogical principles that could guide them in implementing a data visualization project that incorporates training in creating and communicating public health dashboards. Such an initiative aligns with scholars' call to action to enhance data visualization education across disciplines.[11]

Objective

The objective of this paper is to introduce, discuss, and reflect on pedagogical principles that were implemented for a data visualization project in an undergraduate public health informatics course.

Methods

Reflective teaching refers to the situation by which an instructor engages in thinking critically about their situation to gain new understanding, insights, and knowledge.[12] Scholars have shown that reflective teaching is instrumental in enhancing instructors' professional development,[13] [14] course design,[15] and student satisfaction[14] [16] in the health sciences (e.g., public health,[16] nursing,[12] [13] pharmacy,[15] and medicine[14]). Although reflective teaching can be initiated at the point of teaching the course (i.e., reflection-in-action), the contents of this paper are based on the instructor's reflection after teaching the course (i.e., reflection-on-action).[13] The reason for choosing the latter is that it facilitates understanding of the totality of the instructor's thoughts (e.g., pedagogical principles that were used to guide course implementation), actions (e.g., activities that were implemented), and reflections (e.g., aspects that can be enhanced in the future) in teaching the course.

To better organize the process by which the pedagogical principles were implemented in an undergraduate data visualization project, the following sections below were divided based on the generic implementation framework (GIF).[17] This includes preimplementation, implementation, and postimplementation. Previous studies have used GIF to guide the design and delivery of health care simulation[18] and quality management[19] programs.

The Institutional Review Board of the University of Missouri-Columbia (J.R.B.'s present institution) determined that this work does not constitute human subjects research.

Implementation Activities

Preimplementation: Course Development

Development on the syllabus and course content for I320M: Public Health Informatics (hereafter, I320M) started in Fall 2022.[20] It was the first upper-level course for the newly established Health Informatics Concentration of UT iSchool's Undergraduate Informatics Program.[21] Considering that data visualization is a core competency under the Applied Public Health Informatics Competency Model,[4] two of the six learning outcomes (LOs) in I320M were related to enhancing students' data visualization knowledge and skills: “Design and create a dashboard based on open-access public health data” (LO5) and “Generate public health insights based on information derived from a public health dashboard” (LO6). To achieve these LOs, students were assigned individual (10% of course grade) and group (50%) projects that focused on developing a dashboard related to a public health topic. The resulting individual and group dashboards were evaluated using a four-point rubric that measured the following: organization and clarity, delivery of presentation, visualization objects in the dashboard, and visual appeal of the dashboard.[20]

After obtaining clearance from UT iSchool, I320M was offered as an in-person course for Spring 2023 and 15 informatics and noninformatics students (e.g., those who majored in health sciences, chemistry, neuroscience, communications, or government) enrolled in the course. Microsoft Power BI (hereafter, Power BI) via Microsoft 365 (i.e., cloud version) was utilized as the course's data visualization software.

Implementation: Implementing Pedagogical Principles

The implementation of a data visualization project in I320M was guided by four pedagogical principles: (1) scaffolding, (2) constructivism, (3) critical consciousness, and (4) equity and inclusion. [Table 1] provides a summary of these principles and their application.

Table 1 Pedagogical principles and their application

Pedagogical principles	Description	Activity	Assessment
Scaffolding	Initial activities typically start with a high degree of support and structure which then gradually reduces as students develop the knowledge, skills, and confidence to perform tasks to complete the project	Provide intensive support in the individual dashboard project and at the beginning of the group dashboard project with a gradual shift to independent group work in the latter part of the project	After the brainstorming and data collection phases (see [Fig. 2]), observe whether each group can perform the subsequent tasks more independently
Constructivism	Individuals construct new knowledge and skills based on interactions with what they already know and the ideas that they come into contact with	The group project required three students to create a public health dashboard and brainstorming sessions were conducted in class to facilitate peer learning	Each group submits and presents a live dashboard
Critical consciousness	Facilitating students to critically reflect on an oppressive social issue and providing them with opportunities to address such issues	Groups were required to incorporate one SDOH variable in their dashboard	Each group identified and incorporated at least one SDOH variable in their live dashboard
Equity and Inclusion	Equity refers to actions that are fair and just while inclusion refers to actions that eliminate barriers to participation	Ensuring that students learn data visualization using software that is readily accessible and easy to use	Each student can access Power BI via Microsoft 365 on their laptop and use it to create a dashboard

Abbreviation: SDOH, social determinants of health.

Scaffolding

Scaffolding refers to an instructor providing support to learners to complete tasks that are initially beyond the learners' initial capacity.[22] Scaffolding was important in implementing I320M's data visualization project because there was an expectation that both informatics and noninformatics students would enroll in the course. This means that students will likely have limited knowledge of data visualization, public health, or both. With this in mind, the data visualization activities were divided into an individual project followed by a group project.

Before starting the individual project in week 5, students were given introductory lectures on public health (i.e., Introduction to Public Health, Epidemiology, Public Health Surveillance, and Overview of Public Health Informatics) and data visualization (i.e., Introduction to Power BI). These lectures provided students with the much-needed information to create a public health dashboard using Power BI. [Fig. 1] shows the individual project activities.

Fig. 1 Individual dashboard activities. COVID-19, coronavirus disease 2019.

Since it is the first time that students will create a public health dashboard, they were given a cleaned COVID-19 dataset that was retrieved from the CDC[23] (see [Supplementary Material S1] [available in the online version]). The dataset contains provisional COVID-19 deaths by place of death and state from January 2020 to November 2022. Students were provided with a brief overview of what the data fields are, including data wrangling and cleaning procedures (e.g., removing “by year” grouping, recoded start and end date into a single “month” variable, deleting footnotes, and removing the counts for the entire United States). Providing students with a clean dataset ensures that they can focus more on creating visuals rather than the painstaking process of data wrangling and cleaning which were beyond the focus of the individual project.

With the cleaned dataset, students were instructed to create a Power BI dashboard containing five unique visuals. Since classes were held twice a week, the second class day of weeks 5 and 6 was allocated to work on their dashboard. Aside from interpreting the visuals in their dashboard, students were also coached on generating an insight that reflects one of the three core functions of public health (i.e., assessment, policy development, and assurance).[24] If there was some confusion in interpreting their dashboard (e.g., the numbers or visuals did not make sense), students were advised to revise it (see feedback arrow in [Fig. 1]). They were also instructed how to embed a live Power BI dashboard in their PowerPoint presentation so they can interact with it during their presentation.[25] In week 7, students gave a 2-minute presentation on their dashboard. Students received feedback from the instructor and peers to improve their dashboards (e.g., adjusting the legend's font size, enlarging the size of charts, and using less distracting colors in the charts).

Now that the students are familiar with using Power BI to create a public health dashboard, they are ready for a group project that will require them to select their public health topic, find a relevant dataset, and create a dashboard. [Fig. 2] describes the scaffolding of group project activities. Given the extensive activities involved in the group project, half of the time for the first class day (i.e., 45 minutes) and the entire time for the second class day (i.e., 90 minutes) were dedicated to group work.

Fig. 2 Group dashboard activities.

After all students presented their dashboards on week 7, they were asked to form groups composed of three students for the group project. In the following two weeks (i.e., weeks 8 and 9), the instructor facilitated a brainstorming session wherein group members discussed their potential health topic and prospective data sources. By week 10, each group had selected their topic and data source. For example, one group visualized the prevalence of U.S. teen abortions from 2012 to 2016 using U.S. pregnancy, birth, and abortion data archived in data.world.[26]

In week 11, groups were tasked to collect and prepare their dataset. All groups received advice on which data points to retain and whether some data fields should be recoded. In week 12, each group started creating a dashboard using their cleaned dataset. It is expected that students would spot inconsistencies in their dashboard and they were advised to review their dataset (see feedback arrow from data visualization to data preparation in [Fig. 2]). Likewise in the individual project, students were advised to revise their dashboard if there was some confusion in interpreting their visualizations (see feedback arrow from dashboard interpretation to data visualization in [Fig. 2]). In week 13, groups were given 10 minutes to present their work. This is considerably longer than the individual project's 2-minute presentation because each group needs to provide an overview of their public health topic, discuss the process of collecting and preparing the data, explain key public health insights from their dashboard, and provide public health recommendations.

Constructivism

Constructivism, as a learning theory, suggests that individuals construct new knowledge (and later, skillsets) based on interactions with what they already know and the ideas that they come into contact with.[27] Based on constructivism, I320M required a group project wherein three students needed to create a public health dashboard. This is important because each student brought a particular skill set required to complete the project while minimizing the free-rider problem.[28] For instance, one student may be familiar with data wrangling, while the other two are adept in user experience design and health informatics.

Enhancing peer interaction during group sessions was also instrumental in maximizing the benefits of constructivism. For instance, brainstorming sessions served as an opportunity for peers to learn more from their peers. Based on the instructor's observation, this facilitated group cohesiveness which led to active participation in the co-creation of their dashboard in succeeding project sessions.

Critical Consciousness

Freire[29] describes critical consciousness as actions that express social discontent resulting from an awareness of real oppressive situations. As a form of pedagogy, it involves students to critically reflect on an oppressive social issue and provide them with opportunities to address such issues.[30] In public health, an oppressive societal problem that has persisted is health disparity. The National Institute on Minority Health and Health Disparities defines health disparity “as a health difference, on the basis of one or more health outcomes, that adversely affects disadvantaged populations.”[31] In a public health course, students must be critically conscious of health disparity, and addressing it requires knowledge of SDOH and activities that apply such knowledge.

To incorporate critical consciousness in I320M, all lecture topics were embedded with discussions about SDOH. More importantly, students were tasked to be critically conscious of SDOH in their group project by incorporating at least one SDOH variable in their dashboard. In general, all groups used location data (i.e., zip codes, list of U.S. states, or list of countries) as an SDOH variable. Other SDOH variables include human development index, level of education, and park proximity. One group used three SDOH variables. Based on the 2020 dataset from the CDC's National Environmental Public Health Tracking Network,[32] they created a dashboard that visualized the association between park proximity (percentage of people living within 0.5 or 1 mile of a park), education (percentage of population ≥25 years of age with a high school diploma or higher), and location (postal code data recoded to state) or obesity (crude prevalence).

Equity and Inclusion

Students come with diverse knowledge and skill sets that influence their capability to learn. Since there is an expectation that I320M students will come from informatics and noninformatics programs, there is a need to ensure that none of them are left behind in learning about data visualization in the context of public health. To accomplish this, integrating principles of equity (i.e., fair and just practices) and inclusion (i.e., being able to participate by eliminating barriers)[33] were crucial in selecting the software that students will use to learn data visualization in I320M.

Four software selection issues were resolved by focusing on equity and inclusion (see [Table 2]). The first one is cost. To be equitable and inclusive, that software should be available to students without financial cost. The second is ease of use. To be equitable and inclusive, it needs to be beginner-friendly, especially for those who are not familiar with (or fearful of) coding. It is crucial to note that I320M is not a data visualization-focused course so more time should be spent on using it to develop the dashboard rather than learning how to use it. The third is accessibility. To be equitable and inclusive, the students can access it on any large-screen device like a laptop or tablet. Fourth is public health relevance. To be equitable and inclusive, the skills they will learn from using it will be relevant when they decide to work in public health organizations.

Table 2 Comparing Power BI and Tableau across four issues

Issues	Microsoft Power BI	Salesforce Tableau
Cost	• Power BI Desktop is free (no registration)[35]  • Cloud version is free as part of a Microsoft 365 subscription for university students[37]	• Students can register for a free academic license to download Tableau Desktop[36]  • Cloud version is free via Tableau Public but resulting dashboards are publicly released by default[38]
Ease of use	• Easier to use than Tableau[39] [40]	• Steep learning curve[39] [40]
Accessibility	• Desktop version is only for Windows computers[35]  • Cloud version can be used in any web browser[35]	• Tableau Desktop is available for Windows and Mac computers[36]  • Tableau public can be used in any web browser[36]
Public health relevance	• Used by the CDC[41] [42] [43] and U.S. State Health Departments[44] [45]	• Used by U.S. State Health Departments[46] [47]

Although there are several open-source visualization software to choose from,[34] two candidates were Microsoft Power BI[35] and Salesforce Tableau.[36] [Table 2] compares Power BI and Tableau across four issues. Based on [Table 2], Power BI is more equitable and inclusive based on cost,[35] [36] [37] [38] ease of use,[39] [40] accessibility,[35] [36] and public health relevance.[41] [42] [43] [44] [45] [46] [47] Thus, PowerBI was selected for dashboard creation in I320M. To standardize learning and enhance accessibility, students were taught to use the cloud version of Power BI so that they could access it regardless of their computer's operating system. Skill transfer would be less of an issue given the similarity in layout and function between Power BI's desktop and cloud versions. Likewise, experience in using Power BI can help students learn Tableau.

Postimplementation: Reflecting on Challenges and Recommendations

In teaching the course, two challenges were identified that serve as a basis for recommendations to improve the implementation of the data visualization project. The first challenge is the amount of advising for groups. Although consultation sessions were conducted weekly for the group project, two of the five groups required more coaching and consultation. The reason for this is that these groups did not have members who were familiar with data cleaning and preparation. This delayed their transition from data preparation to data visualization by a week. Since the course does not expect students to be proficient in data management, instructors should always be ready to provide support for those experiencing such a challenge. On a positive note, although the course was not designed to be a data management course, the project provided them with a hands-on experience that they could use in other courses.

Another challenge was the lack of publicly-available raw datasets that included rich SDOH data. Studies show that the access to and quality of such datasets are limited.[9] [48] [49] This led to all groups using location data (e.g., zip code, state, or country) to satisfy the requirement of having one SDOH variable in the dashboard. In the future, students should be required to add at least three SDOH variables in their dashboards and provide them links to data repositories that contain rich SDOH data.

Finally, scalability must be considered when implementing the activities in a large-class setting. To appropriately supervise 15 students with a single instructor handling five groups (class size of I320M) in an in-person class, a large in-person class (e.g., at least 60 students) can increase the number of instructors or students per group. The number of instructors and students per group should also be considered when the project is implemented in a fully online asynchronous course.

Contribution to Public Health Education

This paper shows the intricacies of implementing a data visualization project in an undergraduate public health informatics course. For students to learn data visualization skills, it could be beneficial to consider multiple pedagogical principles, such as scaffolding (e.g., outputs build on top of each other), constructivism (e.g., students apply knowledge and work in teams to create a dashboard), critical consciousness (e.g., embedding SDOH in their dashboard), and equity and inclusion (e.g., using a free data visualization software like Power BI that is easy to use for beginners). Although I320M is just one of the numerous public health informatics courses offered in the United States,[9] [50] [51] it is one of the few offered at the undergraduate level. By teaching it among undergraduate students, the course provides them with a head start in data visualization, which fulfills a core competency under the Applied Public Health Informatics Competency Model.[4]

The data visualization project described here contributes to public health education by providing a sample pedagogical activity that transcends those that were implemented before. For instance, although Shanks et al[6] gave insights on teaching students to collaboratively develop static infographics to easily public health issues,[6] their activity is not responsive to the Applied Public Health Informatics Competency Model's suggestion of teaching students to perform data visualization. Although similar in approach to Border's[9] data visualization project that focused on food insecurity and health outcomes, the dashboard project described in this paper provided students the freedom to develop a dashboard for any public health issue while still incorporating principles of SDOH. Finally, compared to Ofrane et al's[7] work detailing MPH students' project in writing a policy brief based on a preexisting dashboard that contains SDOH data, the data visualization project described in this paper offered an opportunity for students to write public health recommendations based on data (that includes SDOH variables) presented in dashboards that they created. Although the recommendations shared by the students were not as extensive as those expected from MPH students, having undergraduate students translate data and information from a dashboard to actionable knowledge that could improve public health is a valuable learning experience.

Considering the lack of curricular dissemination about SDOH,[52] this paper contributes to educational practices that could enhance how SDOH is taught to public health students. Rather than using a passive learning approach, an active learning approach in SDOH[27] that requires students to select and incorporate SDOH variables in their dashboard (through the principles of constructivism and critical consciousness) provides an engaging and student-centered learning experience. Beyond public health education, this paper also responds to Bach et al's[11] call to action for more research and discussion on data visualization education by providing pedagogical principles that could be implemented to advance data visualization education.

Limitations

Despite the contributions that it offers to public health informatics education, this paper has several limitations. First, the insights shared here were based primarily on the subjective account of the instructor, thus limiting its generalizability. Since feedback from students was not deliberately obtained, future work will be geared towards obtaining students' quantitative and qualitative feedback that specifically asks about their experience. Second, it is important to note that the activities and experiences shared here by the instructor are based on teaching undergraduate students who are not public health majors (a majority are informatics majors concentrating in health informatics). As such, instructors who are interested in adapting the project in their courses should carefully plan their activities to better align with course objectives, especially if the intended students are public health majors (e.g., MPH students). Third, it is important to acknowledge that the insights generated from this paper are based on teaching in a U.S. university where students have access to technology (i.e., laptop and internet) for their coursework. Research from other countries, especially those with limited resources, is encouraged to better understand the nuances of teaching data visualization in public health informatics across countries and contexts. Finally, the generalizability of the pedagogical principles is limited since they were only implemented in teaching data visualization in public health informatics. Although the pedagogical principles discussed here can be implemented in other educational contexts (especially those that incorporate problem-based learning approaches), studies are needed to assess the generalizability of the findings.

Conclusion

As demand for public health informatics professionals with data visualization skills increases,[53] it is hoped that the experiences and reflections shared here can provide public health scholars and educators with useful and practical insights into educating and training public health students in data visualization. It is also important to note that creating public health dashboards can serve as an opportunity to emphasize the impact of health disparities and inequities in public health by incorporating principles of SDOH in data visualization. Such an experience provides students with skills that would allow them to use and visualize data for social good.

Clinical Relevance Statement

The next generation of public health professionals should be adept at transforming public health data into public health insights through data visualization. This paper highlights and reflects on four pedagogical principles that were used in implementing a data visualization project in an undergraduate public health informatics course. Moreover, it shows how dashboards can be used as a learning tool to emphasize public health disparities, barriers, and inequities by incorporating principles of SDOH in data visualization.

Multiple-Choice Questions

1. A project that allows students to create a dashboard as a group is reflective of which pedagogical principle?

   • Scaffolding

   • Constructivism

   • Critical consciousness

   • Equity and Inclusion

   Correct Answer: The correct answer is option b. Considered to be an active learning approach, a popular way of applying constructivism in class activities involves project-based learning (PBL). Scholars found constructivism to be a leading learning theory when teaching visualization among college students. More importantly, knowledge generation through constructivism is not only through hands-on activities but also through exposure to different ideas presented by peers. As such, it is common for PBL activities to be group work that facilitates not only teamwork but also co-creation of an output.

2. Which among the following facilitates critical consciousness when students develop dashboards for public health purposes?

   • Selecting a free software that students can use to design and develop the dashboard.

   • Guiding students when creating the dashboard at the early stages and providing them with greater independence as they complete the project.

   • Encouraging students to work together to facilitate teamwork and active co-creation.

   • Emphasizing that dashboards can be an opportunity for students to emphasize the role of SDOH in health outcomes.

   Correct Answer: The correct answer is option d. As a form of pedagogy, critical consciousness involves students critically reflecting on an oppressive social issue. In public health, an oppressive societal problem that has persisted is health disparity. As such, students must be critically conscious of the issue of health disparity, and addressing it requires knowledge of SDOH. As such, integrating SDOH variables in the dashboard facilitates critical consciousness.

Conflict of Interest

None declared.

Acknowledgments

J.R.B. acknowledges the MU Sinclair School of Nursing for providing the time and resources to complete this paper.

Protection of Human and Animal Subjects

The Institutional Review Board of the University of Missouri-Columbia (J.R.B.'s current institution) determined that this work does not constitute human subjects research.

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Publication History

Received: 29 March 2024

Accepted: 12 August 2024

Accepted Manuscript online:
13 August 2024

Article published online:
30 October 2024