The Role of Physical and Computer-Based Experiences in Learning Science Using a Complex Systems Approach

Abstract

How do different components of a learning environment contribute to learning in science? The study examines the contribution of laboratory experiments and computer model explorations to the learning of chemistry through a complex-systems approach. Specifically, junior high-school students’ learning of chemistry via four different methods were compared: with computer models using a complexity approach (MC); with laboratory experiments using a complexity approach (LC); with computer models and laboratory experiments using a complexity approach (MLC); and with a normative disciplinary approach that included only laboratory experiments (LN). Learning was tracked for the relevant science concepts, such as pressure, and for system component ideas, such as emergence. One hundred and fifty-nine seventh-grade students participated in a non-randomized four-group comparison quasi-experimental pre-test-intervention-post-test design with identical pre- and post-tests spaced 2–3 weeks apart. The learning activities for all modes were twelve 45-min lessons. Students’ scores rose in all four groups, but to a different extent, showing a distinct and strong advantage to combining models and labs (MLC), while no differences were seen between the MC and LC conditions. There was also an advantage to learning with the complexity approach (LC) compared to learning using the normative approach (LN). More importantly, the specific concepts that were learned show distinct patterns, distinguishing the contributions of each learning environment component. These research findings have both practical implications when designing learning environments and theoretical contributions to understanding the necessary role of different experiences in learning science.