Real-world problems through computational thinking tools and concepts: the case of coronavirus disease (COVID-19)

Hatice Beyza Sezer,Immaculate Kizito Namukasa

doi:10.1108/jrit-12-2020-0085

Hatice Beyza Sezer, Immaculate Kizito Namukasa

Open Access

https://doi.org/10.1108/jrit-12-2020-0085

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Abstract

PurposeMany mathematical models have been shared to communicate about the COVID-19 outbreak; however, they require advanced mathematical skills. The main purpose of this study is to investigate in which way computational thinking (CT) tools and concepts are helpful to better understand the outbreak, and how the context of disease could be used as a real-world context to promote elementary and middle-grade students' mathematical and computational knowledge and skills.Design/methodology/approachIn this study, the authors used a qualitative research design, specifically content analysis, and analyzed two simulations of basic SIR models designed in a Scratch. The authors examine the extent to which they help with the understanding of the parameters, rates and the effect of variations in control measures in the mathematical models.FindingsThis paper investigated the four dimensions of sample simulations: initialization, movements, transmission, recovery process and their connections to school mathematical and computational concepts.Research limitations/implicationsA major limitation is that this study took place during the pandemic and the authors could not collect empirical data.Practical implicationsTeaching mathematical modeling and computer programming is enhanced by elaborating in a specific context. This may serve as a springboard for encouraging students to engage in real-world problems and to promote using their knowledge and skills in making well-informed decisions in future crises.Originality/valueThis research not only sheds light on the way of helping students respond to the challenges of the outbreak but also explores the opportunities it offers to motivate students by showing the value and relevance of CT and mathematics (Albrecht and Karabenick, 2018).

Highlights

UnderstandingWhen the novel coronavirus was first identified, countries and the World Health Organization real-world (WHO) could not largely understand the risk and rate at which this disease would culminate into a global crisis
We focus on computational simulations of outbreak based on susceptible – infectious – recovered (SIR) model which commonly have been used to illustrate the spread of the COVID-19 disease (Ciarochi, 2020)
Following the COVID-19 outbreak, the society has been bombarded with the mathematical artefacts based on mathematical models of outbreak, which explain the rates and probabilities of spread, track progress of the outbreak and report the effects of the interventions on the pandemic

Summary

Introduction

UnderstandingWhen the novel coronavirus was first identified, countries and the World Health Organization real-world (WHO) could not largely understand the risk and rate at which this disease would culminate into a global crisis. The following questions needed to be answered rapidly by experts when responding to the outbreak: at what rate was the infection going to spread in different problems through CT populations? Health officials and policymakers going to effectively convey information that would help in understanding the nature of the outbreak? By providing tools for assessment, analysis and predictions, mathematical modeling has been very vital in efforts by experts from a variety of fields who have investigated the dynamics of both emerging and reemerging infectious diseases and insights drawn from them help policymakers to determine and debate courses of action that may prevent high mortality rates (Siettos and Russo, 2013; Wang et al, 2020; Yates, 2020)

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