Enhancing learning through opening the group model in a synchronous computer-based environment

This research seeks to apply the concepts of collaborative learning and open learner modelling in order to find out whether seeing their own group learner model helps learners improve their learning in a computer-based collaborative learning environment. There is previous work on giving back information about learning performance as a group but very little, if any, empirical work on the benefits of a group open learner model (GOLM). A major benefit of collaborative learning is to encourage learners to learn further from what they cannot achieve when do it by themselves but they can manage with another. Combining this with viewing and judging the information about learning found in a learner model, it was expected that this would increase their learning awareness in order to improve their learning performance. Without such group learner models, learners might not improve their learning performance in the collaborative learning environment as much as they might. To find out whether opening the group learner models helped learners to improve their learning performance we developed a system called 'GOLeM', and we focused on the learner's score on learning concepts and their degree of confidence in their answer. GOLeM was used as a learning environment to test for evidence in relation to two comparisons of individual performance. The first was a comparison of individual performance between participants in a non computer-based individual learning environment and a computerbased collaborative learning environment. The second respect was to compare the results of learning in two different computer-based collaborative learning environments which were only different in terms of whether or not the learners could see their group learner model. The content of number-conversion is chosen for the domain knowledge. Dialogue games and sentence openers are used to implement a chat-tool to exchange beliefs between peers. Bar charts and textual explanations are used as external representations of learning performance as a group. The system was implemented and tested in two versions: paperbased, for the plausibility of the content and the user interface; and computer-based, for comparing the learning results among three different learning environments regarding the