Developing Computational Thinking Teaching Strategies to Model Pandemics and Containment Measures

Roberto Araya, Masami Isoda and Johan van der Molen Moris
Additional contact information
Roberto Araya: Center for Advanced Research in Education, Institute of Education, Universidad de Chile, Santiago 8320000, Chile
Masami Isoda: Faculty of Humanities and Social Sciences, University of Tsukuba, Tsukuba 305-8577, Japan
Johan van der Molen Moris: MRC Biostatistics Unit, University of Cambridge, Cambridge CB2 0SR, UK

IJERPH, 2021, vol. 18, issue 23, 1-30

Abstract: COVID-19 has been extremely difficult to control. The lack of understanding of key aspects of pandemics has affected virus transmission. On the other hand, there is a demand to incorporate computational thinking (CT) in the curricula with applications in STEM. However, there are still no exemplars in the curriculum that apply CT to real-world problems such as controlling a pandemic or other similar global crises. In this paper, we fill this gap by proposing exemplars of CT for modeling the pandemic. We designed exemplars following the three pillars of the framework for CT from the Inclusive Mathematics for Sustainability in a Digital Economy (InMside) project by Asia-Pacific Economic Cooperation (APEC): algorithmic thinking, computational modeling, and machine learning. For each pillar, we designed a progressive sequence of activities that covers from elementary to high school. In an experimental study with elementary and middle school students from 2 schools of high vulnerability, we found that the computational modeling exemplar can be implemented by teachers and correctly understood by students. We conclude that it is feasible to introduce the exemplars at all grade levels and that this is a powerful example of Science Technology, Engineering, and Mathematics (STEM) integration that helps reflect and tackle real-world and challenging public health problems of great impact for students and their families.

Keywords: COVID-19; computational thinking; computational modeling; lesson study (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1660-4601/18/23/12520/pdf (application/pdf)
https://www.mdpi.com/1660-4601/18/23/12520/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jijerp:v:18:y:2021:i:23:p:12520-:d:689848

Access Statistics for this article

IJERPH is currently edited by Ms. Jenna Liu

More articles in IJERPH from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().