Using a Semantic Diagram Tool to Facilitate Deep Learning During Collaborative Problem Solving

• In Event: Forecasting and Supporting Success in Computer-Based Learning Environments

Abstract

In this study semantic diagram tool is proposed to facilitate deep learning during collaborative problem solving (CPS) from cognitive load theory. To investigate its effectiveness, a comparative quasi-experiment was conducted in a university in East China. Group discourse and data analysis of cognitive load perception show that the use of a semantic diagram tool can decrease transaction costs during problem solving. This result is achieved by freeing the working memory capacity of procedural conversations necessary for CPS, which do not directly contribute to cognitive development. Data analysis from pre-and-post testing shows that semantic diagram tool can facilitate student deep learning in CPS. The finding can guide the design of technological support during collaborative problem solving.

Authors

• Huiying Cai, Jiangnan University

• Xiaoqing Gu, East China Normal University