The Effects of Pre-Training Types on Cognitive Load, Collaborative Knowledge Construction and Deep Learning in a Computer-Supported Collaborative Learning Environment

Abstract

This study investigated the effects of pre-training types on the cognitive load, collaborative knowledge construction and level of learning in a computer-supported collaborative learning environment. Pre-training was provided to help learners optimise their cognitive load, build accurate shared-knowledge and achieve successful deep learning. The participants were randomly assigned into one of two groups. Each group received either guided or self-directed pre-training. The participants were provided with three learning phases, which included the pre-training phase, knowledge-sharing phase and knowledge-construction phase. After completing each learning phase, we analysed the participants’ cognitive load and level of collaborative knowledge. One week after the computer-supported collaborative learning phase, we conducted a transfer test to measure the quality of learning. The results suggested that the guided pre-training is more effective in reducing unnecessary cognitive load, building a higher level of collaborative knowledge and achieving deep learning.