Pandemic as Game Mechanic: Simulation of Infection Spread for the Classroom
| Autor: | Hendrik Knoche, Bastian Ilsø Hougaard, Majken Grunfeld |
|---|---|
| Přispěvatelé: | Chang, Maiga, Chen, Nian-Shing, Sampson, Demetrios G, Tlili, Ahmed |
| Rok vydání: | 2021 |
| Předmět: |
2019-20 coronavirus outbreak
Game mechanics Simulation Game Coronavirus disease 2019 (COVID-19) Isolation (health care) Computer science Data Visualization Serious Games Data literacy Test (assessment) Qualitative feedback Pandemic Mathematics education Data Literacy Game-Based Learning Learning Games |
| Zdroj: | ICALT Hougaard, B I, Grünfeld, M & Knoche, H 2021, Pandemic as Game Mechanic: Simulation of Infection Spread for the Classroom. in M Chang, N-S Chen, D G Sampson & A Tlili (eds), 2021 International Conference on Advanced Learning Technologies (ICALT) . IEEE Computer Society Press, International Conference on Advanced Learning Technologies (ICALT), pp. 231-233, he 21th IEEE International Conference on Advanced Learning Technologies (ICALT 2021), 12/07/2021 . https://doi.org/10.1109/ICALT52272.2021.00075 |
| DOI: | 10.1109/icalt52272.2021.00075 |
| Popis: | In light of COVID-19, we created a novel simulation game, to explain exponential growth in disease spread. The simulation game is an open educational ressource (OER) for children to reflect on how test and isolation can be applied to stop contagious diseases. The game was reviewed in three classrooms (P3-P5) by a primary school teacher to pilot the applicability of the game in an educational setting. Based on qualitative feedback from pupils, we developed accompanying exercise sheets and website in close collaboration with the teacher. |
| Databáze: | OpenAIRE |
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