Building System Capacity with a Modeling-Based Inquiry Program for Elementary Students: A Case Study

Abstract

Science education in the United States should shift to incorporate innovative technologies and curricula that prepare students in the competencies needed for success in science, technology, engineering, and math (STEM) careers. Here we employ a qualitative case study analysis to investigate the system variables that supported or impeded one such reform effort aimed at improving elementary students’ science learning. We found that, while some program design features contributed to the success of the program (i.e., a strong multi-institutional partnership and a focus on teacher training and instructional supports), other features posed barriers to the long-term system-level change needed for reform (i.e., low levels of social capital activation, low prioritization of science learning, and frequent turnover of key personnel). In light of these findings, we discuss broader implications for building the capacity to overcome system barriers. In this way, an in-depth examination of the context-specific barriers to reform in this educational system can inform efforts for future reform and innovation design.

Keywords

• data literacy
• elementary education
• agent-based simulations
• StarLogo Nova
• science curriculum
• complex systems learning