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Emil Eidin

Datos Biográficos

ID9505589
NOMBREEmil Eidin
NOMBRESEmil
APELLIDOEidin
FIRMAEIDIN E
AFILIACIONESMichigan State University
ORCID0000-0002-2394-2434
VERIFICADOSí
TOTAL DE OBRAS2
TOTAL DE CITAS0
OBRAS COMO AUTOR2
OBRAS COMO EDITOR0
PRIMER AÑO DE PUBLICACIÓN2022
AÑO MÁS RECIENTE DE PUBLICACIÓN2023
ÍNDICE H0
  • The effect of using different computational system modeling approaches on applying systems thinking

    Open Access•Emil Eidin, Jonathan Bowers et al.•ARTICLE•Frontiers in Education•2023

    This paper discusses the potential of two computational modeling approaches in moving students from simple linear causal reasoning to applying more complex aspects of systems thinking (ST) in explanations of scientific phenomena. While linear causal reasoning can help students understand some natural phenomena, it may not be sufficient for understanding more complex issues such as global warming and pandemics, which involve feedback, cyclic patte…

  • A framework for supporting systems thinking and computational thinking through constructing models

    Open Access•Namsoo Shin, Jonathan Bowers et al.•ARTICLE•Instructional Science•2022

    We face complex global issues such as climate change that challenge our ability as humans to manage them. Models have been used as a pivotal science and engineering tool to investigate, represent, explain, and predict phenomena or solve problems that involve multi-faceted systems across many fields. To fully explain complex phenomena or solve problems using models requires both systems thinking (ST) and computational thinking (CT). This study pro…

Sin obras prominentes en esta página.

  • A framework for supporting systems thinking and computational thinking through constructing models

    Open Access•Namsoo Shin, Jonathan Bowers et al.•ARTICLE•Instructional Science•2022

    We face complex global issues such as climate change that challenge our ability as humans to manage them. Models have been used as a pivotal science and engineering tool to investigate, represent, explain, and predict phenomena or solve problems that involve multi-faceted systems across many fields. To fully explain complex phenomena or solve problems using models requires both systems thinking (ST) and computational thinking (CT). This study pro…

  • The effect of using different computational system modeling approaches on applying systems thinking

    Open Access•Emil Eidin, Jonathan Bowers et al.•ARTICLE•Frontiers in Education•2023

    This paper discusses the potential of two computational modeling approaches in moving students from simple linear causal reasoning to applying more complex aspects of systems thinking (ST) in explanations of scientific phenomena. While linear causal reasoning can help students understand some natural phenomena, it may not be sufficient for understanding more complex issues such as global warming and pandemics, which involve feedback, cyclic patte…

Artificial Intelligence (2 obras) · Complex system (2 obras) · Computational model (2 obras) · Computer Science (2 obras) · Engineering (2 obras) · Innovative Teaching and Learning Methods (2 obras) · Management science (2 obras) · Psychology (2 obras) · Systems thinking (2 obras) · Artificial Intelligence (1 obra)

Ethnos_APP • Proyecto Open Source • Licencia MIT • Frontend v2.0.0 • Privacidad y Cookies • Documentación de la API: api.ethnos.app/docs • Código de la API: GitHub • DOI: 10.5281/zenodo.17049435 • Código del Frontend: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae