A Framework for Model-Based Inquiry Through Agent-Based Programming

There has been increased recognition in the past decades that model-based inquiry (MBI) is a promising approach for cultivating deep understandings by helping students unite phenomena and underlying mechanisms. Although multiple technology tools have been used to improve the effectiveness of MBI, there are not enough detailed examinations of how agent-based programmable modeling (ABPM) tools influence students’ MBI learning. The present collective case study sought to contribute by closely investigating ABPM-supported MBI processes for 8th grade students learning about natural selection and adaptation. Eight 8th grade students in groups of 2–3 spent 15 h during a span of 4 weeks collaboratively programming simulations of adaptation based on the natural selection model, using an ABPM tool named NetLogo. The entire programming processes of these learning groups, up to 50 h, were videotaped and then analyzed using mixed methods. Our analysis revealed that the programming task created a context that calls for nine types of MBI actions. These MBI actions were related to both phenomena and the underlying model. Results also showed that students’ programming processes took place in consecutive programming cycles and aligned with iterative MBI cycles. A framework for ABPM-supported MBI learning is proposed based upon the findings. Implications in developing MBI instruction involving ABPM tools are discussed.