Teaching a Modeling Process: Reflections from An Online Course
Teaching a Modeling Process: Reflections from An Online Course
The outbreak of the COVID-19 pandemic in 2020 posed unique challenges for academic and professional education, while at the same time offering opportunities related to the mass switching of the delivery of courses to the online mode. In this paper, we share the experience of organizing and delivering an online doctoral-level course on Agent-Based Modeling for Social Research. Our aim was to teach interdisciplinary content on various elements of the modeling process in a coherent and practical way. In the paper, we offer a critical assessment of different aspects of the course, related to content as well as organization and delivery. By looking at the course in the light of the current knowledge on good teaching and learning practices from the educational and psychological literature, and reflecting on the lessons learned, we offer a blueprint for designing and running complex, multi-thread simulation courses in an efficient way.
Bijak, Jakub
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Hilton, Jason
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Hinsch, Martin
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Lipscombe, Kim
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Nurse, Sarah
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Prike, Toby
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Smith, Peter W.F.
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Reinhardt, Oliver
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Uhrmacher, Adelinde M.
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Higham, Philip A.
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Grow, Andre
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2021
Bijak, Jakub
e33bf9d3-fca6-405f-844c-4b2decf93c66
Hilton, Jason
da31e515-1e34-4e9f-846d-633176bb3931
Hinsch, Martin
660b9bb4-148f-4692-9014-8db1d751ae57
Lipscombe, Kim
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Nurse, Sarah
1dc41320-0dd0-4eed-99ea-7ca7dae9f734
Prike, Toby
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Smith, Peter W.F.
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Reinhardt, Oliver
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Uhrmacher, Adelinde M.
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Higham, Philip A.
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Grow, Andre
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Bijak, Jakub, Hilton, Jason, Hinsch, Martin, Lipscombe, Kim, Nurse, Sarah, Prike, Toby, Smith, Peter W.F., Reinhardt, Oliver, Uhrmacher, Adelinde M., Higham, Philip A. and Grow, Andre
(2021)
Teaching a Modeling Process: Reflections from An Online Course.
In 2021 Winter Simulation Conference, WSC 2021.
vol. 2021-December,
IEEE.
12 pp
.
(doi:10.1109/WSC52266.2021.9715415).
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Conference or Workshop Item
(Paper)
Abstract
The outbreak of the COVID-19 pandemic in 2020 posed unique challenges for academic and professional education, while at the same time offering opportunities related to the mass switching of the delivery of courses to the online mode. In this paper, we share the experience of organizing and delivering an online doctoral-level course on Agent-Based Modeling for Social Research. Our aim was to teach interdisciplinary content on various elements of the modeling process in a coherent and practical way. In the paper, we offer a critical assessment of different aspects of the course, related to content as well as organization and delivery. By looking at the course in the light of the current knowledge on good teaching and learning practices from the educational and psychological literature, and reflecting on the lessons learned, we offer a blueprint for designing and running complex, multi-thread simulation courses in an efficient way.
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Published date: 2021
Additional Information:
Funding Information:
This research underpinning the course received funding from the European Research Council (ERC) via the research project Bayesian Agent-based Population Studies (grant number 725232), which is gratefully acknowledged. The course was organized in collaboration with the Max Planck Institute for Demographic Research, the ESRC Centre for Population Change and the National Centre for Research Methods. We thank Heiner Meier and three WSC reviewers for their helpful comments on earlier drafts.
Funding Information:
This section presents details on the course of Agent-Based Modeling for Social Research, organized as one deliverable of the Bayesian Agent-Based Population Studies project, funded by the European Research Council. The course took place virtually, on 3–25 November 2020, with plenary sessions held online every week, interspersed with small-group activities and tutorials, as discussed in detailed below.
Publisher Copyright:
© 2021 IEEE.
Venue - Dates:
2021 Winter Simulation Conference, WSC 2021, , Phoenix, United States, 2021-12-12 - 2021-12-15
Identifiers
Local EPrints ID: 475670
URI: http://eprints.soton.ac.uk/id/eprint/475670
ISSN: 0891-7736
PURE UUID: 23c63ec1-4ca2-4ff6-8f0a-78c4f9d7c170
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Date deposited: 23 Mar 2023 17:49
Last modified: 18 Mar 2024 03:48
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Contributors
Author:
Martin Hinsch
Author:
Kim Lipscombe
Author:
Toby Prike
Author:
Oliver Reinhardt
Author:
Adelinde M. Uhrmacher
Author:
Andre Grow
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