An innovative consensus map-embedded collaborative learning system for ER diagram learning: sequential analysis of students’ learning achievements
作者：Li-Chen Cheng, Hui-Chun Chu
Interactive Learning Environments
Although computer-supported collaborative learning has been successfully applied in educational settings to improve group learning performance, most such systems still lack effective strategies for knowledge representation which could help reduce discussion time. In this study, concept mapping, already applied as a tool to help visualize and organize existing or newly learned knowledge, is incorporated to address this problem in a newly developed concept map and computer-supported collaborative learning system (CMCLS). It was designed as a quasi-experiment study and was carried out with 77 university students. The system was first used by the groups of students to illustrate their knowledge and achieve consensus during a learning activity, after which their performance and feelings of satisfaction with this innovative approach were evaluated. Patterns of learning within the proposed framework were explored. The learning behaviors, including the actions and interactions with peers of the participants during the learning activity were recorded. Finally, lag-sequential analysis was used to compare the interactions and the differences in the behavior patterns of the two groups, one using the newly developed CMCLS consensus map-embedded approach and a control group which did not use this approach. The results showed significant improvement in the learning achievement of students using the novel approach, as well as a higher degree of perceived usefulness and satisfaction. The novel consensus map-embedded approach was useful for knowledge construction and for assisting with integration of the team members’ results to produce the final ER diagram.