RESEARCH ARTICLE Impact of computer modeling on learning and teaching systems thinking Ha Nguyen | Rossella Santagata School of Education, University of California, Irvine, California Correspondence Ha Nguyen, School of Education, University of California, 3200 Education Bldg., Irvine, CA 92617. Email: thicn@uci.edu. Abstract Researchers have found that computer modeling fos- ters 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 prac- tices in enacting computer tools, few studies have con- sidered teachers' use of computer modeling and its implications for student learning in classroom interac- tions, 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, particu- larly students' ability to provide causally coherent state- ments in explaining scientific ideas and evidence. Enactment of computer modeling may be associated Received: 25 May 2020 Revised: 16 September 2020 Accepted: 2 October 2020 DOI: 10.1002/tea.21674 | © 2020 National Association for Research in Science Teaching J Res Sci Teach. 2020;1–28. wileyonlinelibrary.com/journal/tea 1