Data in Education Seminar/31 05 2023
Материал из Поле цифровой дидактики
Версия от 13:43, 20 мая 2023; Patarakin (обсуждение | вклад)
| Описание события | Использование данных и цифровых инструментов в исторических исследованиях и преподавании науки истории |
|---|---|
| Тип события | |
| Начало | 2023-05-31T16:00:08.000Z |
| Окончание | 2023-05-31T18:00:08.000Z |
| color | orange |
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| Среды и средства, которые использовались в рамках события | |
| Формируемые в рамках события компетенции | |
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Модели исторических событий
Литература
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- The Joys of Big Data for Historians // Exploring Big Historical Data. WORLD SCIENTIFIC, 2021. P. 1–34.
- Nanetti A. AI, ML, and ABMS for Historical Sciences. Opportunities and Limits // Digital Orientalia. 2021. Vol. 1, № 1. P. 12–18.
- Computer Magazines and Historical Research // Code Nation: Personal Computing and the Learn to Program Movement in America. New York, NY, USA: Association for Computing Machinery, 2020.
- Ponsard C. Teaching Computer Programming to Post-millennial Kids: Overview of Goals, Activities and Supporting Tools. // CSEDU (2). 2019. P. 474–480.
- Nanetti A., Benvenuti D. Animation of two-dimensional pictorial works into multipurpose three-dimensional object. The Atlas of the ships of the known world depicted in the 1460 Fra Mauro’s Mappa Mundi as a showcase // SCIRES-IT-SCIentific RESearch and Information Technology. 2019. Vol. 9, № 2. P. 29–46.
- Floyd S.P. Historical High School Computer Science Curriculum and Current K-12 Initiatives - Proceedings of the 50th ACM Technical Symposium on Computer Science Education. New York, NY, USA: Association for Computing Machinery, 2019. P. 1287.
- Nanetti A., Cheong S.A. Computational History: From Big Data to Big Simulations // Big Data in Computational Social Science and Humanities / ed. Chen S.-H. Cham: Springer International Publishing, 2018. P. 337–363.
- Nanetti A., Cheong S.A. Computational history : from big data to big simulations. Springer Nature Switzerland AG, 2018.
- Matrosov Institute for System Dynamics and Control Theory SB RAS, Lermontov St. 134, Irkutsk, Russia, 664033 et al. Machine Learning in a Multi-Agent System for Distributed Computing Management // Collection of selected papers of the IV International Conference on Information Technology and Nanotechnology. IP Zaitsev V.D., 2018. P. 89–97.
- Chen S.-H., Yu T. Big Data in Computational Social Sciences and Humanities: An Introduction // Big Data in Computational Social Science and Humanities / ed. Chen S.-H. Cham: Springer International Publishing, 2018. P. 1–25.
- Francois P. et al. A macroscope for global history - Seshat Global History Databank: a methodological overview // Digital Humanities Quarterly. Alliance of Digital Humanities Organizations, 2016.
- Edmond J. Will Historians Ever Have Big Data? // Computational History and Data-Driven Humanities / ed. Bozic B. et al. Cham: Springer International Publishing, 2016. P. 91–105.
- Barceló J.A., Del Castillo F. Simulating the Past for Understanding the Present. A Critical Review // Simulating Prehistoric and Ancient Worlds / ed. Barceló J.A., Del Castillo F. Cham: Springer International Publishing, 2016. P. 1–140.
- Gavin M. Agent-Based Modeling and Historical Simulation // DHQ. 2014. Vol. 008, № 4.
- Millington J.D.A., O’Sullivan D., Perry G.L.W. Model histories: Narrative explanation in generative simulation modelling // Geoforum. 2012. Vol. 43, № 6. P. 1025–1034.
