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Impact of computer modeling on learning and teaching systems thinking
Author(s) -
Nguyen Ha,
Santagata Rossella
Publication year - 2021
Publication title -
journal of research in science teaching
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.067
H-Index - 131
eISSN - 1098-2736
pISSN - 0022-4308
DOI - 10.1002/tea.21674
Subject(s) - curriculum , mathematics education , computer science , class (philosophy) , teaching method , computer assisted instruction , scientific modelling , science education , causal model , psychology , pedagogy , artificial intelligence , philosophy , epistemology , medicine , pathology
Abstract Researchers have found that computer modeling fosters the learning of causal mechanisms in systems, an important crosscutting concept in science that many novice learners find challenging. Despite the research that highlights the role of teacher's instructional practices in enacting computer tools, few studies have considered teachers' use of computer modeling and its implications for student learning in classroom interactions, compared to interactions without computer tools. In this study, we examine (a) the impact of computer modeling on students' understanding of causal links in decomposition and (b) classroom interactions with use of computer modeling. We employed a quasi‐experimental design with eight middle school science classes that served predominately Latinx students. The random treatment was at the class level (computer modeling; n = 60, four classes) and control (paper modeling; n = 59, four classes). Analyses incorporated student preassessment and postassessment, classroom observations, and audio‐recorded modeling instruction. Results indicate that compared to paper modeling, computer modeling enriched systems thinking, particularly students' ability to provide causally coherent statements in explaining scientific ideas and evidence. Enactment of computer modeling may be associated with a shift in classroom interactions to include more invitation for students' elaboration of causal systems. We discuss aspects of computer modeling that may foster systems thinking, with implications for the future design of tools and curricula.