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 proposes a theoretical framework that uses modeling as a way to integrate ST and CT. We developed a framework to guide the complex process of developing curriculum, learning tools, support strategies, and assessments for engaging learners in ST and CT in the context of modeling. The framework includes essential aspects of ST and CT based on selected literature, and illustrates how each modeling practice draws upon aspects of both ST and CT to support explaining phenomena and solving problems. We use computational models to show how these ST and CT aspects are manifested in modeling.
We describe a National Science Foundation-funded project called 'Evolution Readiness' that used computer-based interactive models as well as hands-on activities to help fourth grade students learn Darwin's model of natural selection as the process primarily responsible for evolution. The inclusion of 'readiness' in the title is important to keep in mind. A full understanding of evolution would require the acquisition of a detailed model of how information is encoded in DNA, interpreted in cells, and manifested in organisms and species. To understand the evidence presented by the fossil record and its implications for evolutionary theory would require an appreciation of the immensity of geologic time as well as a substantive introduction to geology and paleontology. These topics are not easily accessible to ten-year-olds, but we have found that children can successfully perform virtual experiments that explore the connection between the interdependence of species and their remarkable adaptations and recognize the latter as arising gradually from small variations that affect reproductive success. Working in three school districts, located in Texas, Missouri, and Massachusetts, we implemented a curriculum unit covering 16 class periods. In each state the elementary science standards include all the concepts we cover, but traditional curricula do not attempt to integrate these concepts or to use them to explain observations of the natural world. We compared students who had used our materials to a baseline cohort taught by the same teachers but exposed only to the traditional curriculum. The treatment students outscored the baseline students, demonstrating the feasibility of teaching young students the fundamental concepts behind the theory of evolution and thus preparing them to deepen their understanding when they next encounter the topic.
Developing and using models to make sense of phenomena or to design solutions to problems is a key science and engineering practice. Classroom use of technology-based tools can promote the development of students’ modelling practice, systems thinking, and causal reasoning by providing opportunities to develop and use models to explore phenomena. In previous work, we presented four aspects of system modelling that emerged during our development and initial testing of an online system modelling tool. In this study, we provide an in-depth examination and detailed evidence of 10th grade students engaging in those four aspects during a classroom enactment of a system modelling unit. We look at the choices students made when constructing their models, whether they described evidence and reasoning for those choices, and whether they described the behavior of their models in connection with model usefulness in explaining and making predictions about the phenomena of interest. We conclude with a set of recommendations for designing curricular materials that leverage digital tools to facilitate the iterative constructing, using, evaluating, and revising of models.
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