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

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).

Mathematical modelling of exponential growth as a rich learning environment for mathematics classrooms

“…4.1 & 4.2) and determining the exponential factor at different times (see Sect. 4.3) here shows that exponential growth should play an important role in teaching, not only in the sense of applying calculations, such as by determining growth factors but also in relation to building appropriate basic mental models, such as imagining growth proportional to the current stock (Castillo-Garsow, 2013 ; Sezer & Namukasa, 2021 ). First, students need to define the goal of modelling; for example, should an existing model, which is only represented by a graph, be questioned regarding the appropriateness of the representation of a real situation?…”

Computational Thinking Activities Among Mathematics Teachers: A Systematic Literature Review

“…As such, they have taken the initiative to conduct study to see the effectiveness of the integration of computational thinking in the teaching of mathematics in the country. Computational thinking activities are very effective because they can improve students' understanding of problem-solving skills (Sezer & Namukasa, 2021). However, there are differences in the number published by country, and which are driven by various factors such as the direction of the education system, funding sources and cultural factors.…”

How do we design curricula to foster innovation, motivation and interest in STEM learning?

“…Furthermore, interest in content can be situational according to students' determination of relevance (Nieswandt and Horowitz, 2015). For instance, topics such as the COVID-19 pandemic can be used to model real-world STEM concepts within a classroom setting (Sezer and Namukasa, 2021). Science curricula that situated learning within a real-world context are found to increase students' interest in science, their sense of agency surrounding scientific topics and their scientific literacy (Ke et al, 2021;Kubsch et al, 2023;Redmond et al, 2011).…”