The development of a graphical representation for performing a task can potentially yield a greater understanding of the task domain, but it is itself a demanding task that can distract from the primary one of learning the domain. In this research, we investigated the impact of constructing versus receiving a graphical representation on learning and coaching the analysis of scientific arguments. Subjects studied instructional materials and used the Belvedere graphical interface to to analyze texts drawn from an actual scientific debate. One group of subjects used a box-and-arrow representation, augmented with text, whose primitive elements had preassigned meanings tailored to the domain of instruction. In the other group, subjects used the graphical elements as they wished, thereby creating their own representation. Our results support the following conclusions. From the perspective of learning target concepts, developing one's own representation may not hurt those students who gain a sufficient understanding of the possibilities of abstract representation, although there are costs in time on task and in the quality of the diagrams produced. The risks are much greater for less able students because, if they develop a representation that is inadequate for expressing the concepts targeted by instruction, they will use those concepts less or not at all. From the perspective of coaching students, a predefined representation has a significant advantage. If it is appropriately expressive for the concepts it is designed to represent, it provides a common language and clearer shared meaning between the student and the coach, enabling the coach to understand students' analysis more easily and to evaluate it more effectively against a model of the ideal analysis.

The Argumentation Project at LRDC aims to support students in knowledge building by means of collaborative argumentation. A component of this project is a system for helping students generate arguments in a dicilogical situation. Empirical research suggests that students generally have difficulty generating arguments for different positions on an issue and may resort to giving arguments that are insincere or irrelevant. Our system will assist the arguer by constraining him to respond relevantly and consistently to the actions of other arguers, suggesting appropriate ways to respond. This assistance wUl be provided by strategies derived from conversational maxims and "good conduct" rules for collaborative argumentation. We describe a prototype system that uses these strategies to simulate both sides of a dialogical argument.