In the information engineering learning environment, there may be more than one solution to any given problem. We have developed CAMELOT using the Nominal Group Technique for group problem solving. This paper describes the collaborative learning system on the Internet using discussion model, the effectiveness of collaborative learning in modeling the entity-relationship diagram within the field of information engineering, and how to apply AI technologies such as rule-based reasoning and case-based reasoning to the pedagogical strategy. By using CAMELOT, each learner learns how to analyze through case studies and how to collaborate with his or her group in problem solving. As a result. We have found evidence for the effectiveness of collaborative learning, such as getting a deeper understanding by using CAMELOT than by individual learning, because they can reach better solutions through discussion, tips from other learners, examination of one another's individual solutions, and understanding alternative solutions using case-based reasoning.

In the business systems design learning environment, there may be more than one solution to any given problem. For instance, the data model will be different depending on each learner's perspective. Accordingly, group learning systems are very effective in this domain. We have developed CAMELOT (Collaborative and Multimedia Environment for Learners on Teams) [18] using the Nominal Group Technique for group problem solving. In this paper, the basic framework of the collaborative learning system and the effectiveness of collaborative learning in designing the Data Model are described. By using CAMELOT, each learner learns how to analyze through case studies and how to cooperate with his or her group in problem solving. Learners come to a deeper understanding from using CAMELOT than from studying independently because they are enabled to reach better solutions through discussion, tips from other learners, and examination of one another's works.