Beyond assessing knowledge about models and modeling: Moving toward expansive, meaningful, and equitable modeling practice
Beyond assessing knowledge about models and modeling: Moving toward expansive, meaningful, and equitable modeling practice
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除了评估有关模型和建模的知识之外:走向广泛、有意义和公平的建模实践
DOI:
10.1002/tea.21770
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发表时间:
2022
影响因子:
4.6
通讯作者:
Manz, Eve
中科院分区:
文献类型:
--
作者:
Schwarz, Christina V.;Ke, Li;Salgado, Michelle;Manz, Eve
Modeling is a powerful science and engineering practice (National Research Council, 2012). The core work of modeling is embodying, using, and refining ideas through iteratively developing representations to describe, connect, explain, and predict phenomena and systems. That is, any object or representation that is used to think about a process or system can be considered as a model. There are a variety of forms that serve the function of modeling—and those can be remarkably diverse for people in a variety of settings and in different disciplines. From this point of view, testing computer simulations to predict the effects of climate change and using physical embodiments like stream tables to think about how rivers change over time can be considered as acts of modeling. And so, too, can children's pretend play (National Academies of Sciences, Engineering, and Medicine, 2021) and stories developed and told across generations that exemplify critical relationships and systems (Kimmerer, 2013; Marin & Bang, 2018). Modeling can be powerful for learners in PK-16 settings. It can support learners' sensemaking by enabling them to externalize and revise their ideas, making them public, and experiencing science knowledge development as a social, conjectural, and iterative process (Passmore & Stewart, 2002; Schwarz et al., 2009). Over the past 35 years, science educational researchers have generated critical knowledge about the practice of modeling. Teachers, the classroom learning environment, and curriculum all play an important role in how learners can engage in modeling practice (eg, Salgado, 2021; Vo et al., 2015; Windschitl et al., 2008;
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影响因子:
1.9
作者:
B. Reiser;Michael Novak;Tara A. W. McGill;W. Penuel
通讯作者:
W. Penuel
影响因子:
1.9
作者:
Tzou, Carrie;Bang, Megan;Bricker, Leah
通讯作者:
Bricker, Leah
DOI:
--
发表时间:
2017
期刊:
影响因子:
--
作者:
Laura Zangori;Tina Vo;C. Forbes;C. Schwarz
通讯作者:
C. Schwarz
DOI:
--
发表时间:
2019
期刊:
The Annals of the American Academy of Political and Social Science
影响因子:
--
作者:
W. Penuel;Douglas A. Watkins
通讯作者:
Douglas A. Watkins
影响因子:
4.6
作者:
Cynthia Passmore;J. Stewart
通讯作者:
J. Stewart