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.

学习环境的不同组成部分如何促进科学学习？该研究通过复杂系统的方法研究了实验室实验和计算机模型探索对化学学习的贡献。具体而言，比较了初中学生通过四种不同方法学习化学的方法：使用复杂性方法（MC）的计算机模型；使用复杂性方法（MC）的计算机模型；使用复杂方法的计算机模型。使用复杂性方法（LC）进行实验室实验；使用复杂性方法（MLC）的计算机模型和实验室实验；并采用仅包括实验室实验（LN）的规范性学科方法。跟踪学习相关的科学概念（例如压力）和系统组件思想（例如紧急情况）。159名七年级学生参加了一个非随机的四组比较准实验的预测试，干预，后测试设计，前，后测试的间隔为2-3周。所有模式的学习活动均为12节45分钟的课程。在所有四个组中，学生的得分都有所提高，但是程度有所不同，显示出结合模型和实验室（MLC）的独特而强大的优势，而MC和LC条件之间没有发现差异。与使用规范方法（LN）进行学习相比，使用复杂度方法（LC）进行学习还有一个优势。更重要的是，所学习的特定概念显示出不同的模式，从而区分了每个学习环境组件的贡献。