The curriculum of the Faculty has been radically revised over the last two years and is now based on the concept of "Problem-Based Learning". The subject matter taught is divided thematically into specific issues that are taught in six week blocks. The vehicles for these blocks are specially selected and adapted case studies prepared by teams of staff members. These provide a focus for integrating specialist subjects around a studio based design theme. In the case of second year this studio is largely computer-based: many drawings are produced by computer and several specially written computer applications are used in association with the specialist inputs.

This paper describes the "block structure" used in second year, giving examples of the special computer programs used, but also raises a number of broader educational issues. Introduction of the block system arose as a method of curriculum integration in response to difficulties emerging from the independent functioning of strong discipline areas in the traditional work groups. The need for a greater level of selfdirected learning was recognised as opposed to the "passive information model" of student learning in which the students are seen as empty vessels to be filled with knowledge - which they are then usually unable to apply in design related contexts in the studio. Furthermore, the value of electives had been questioned: whilst enabling some diversity of choice, they may also be seen as diverting attention and resources from the real problems of teaching architecture.

The term "model" in the above paragraph has been used in various ways and in this context is defined as any representation through which design intent is expressed. This includes accurate/ rational or abstract drawings (2- dimensional and 3-dimensional), physical models (realistic and abstract) and computer models (solid, void and virtual reality). The various models that fall within the categories above have been derived from the need to "view" the proposed design in various ways in order to support intuitive reasoning about the proposal and for evaluation purposes. For example, a 2-dimensional drawing of a floor plan is well suited to support reasoning about spatial relationships and circulation patterns while scaled 3-dimensional models facilitate reasoning about overall form, volume, light, massing etc. However, the common denominator of all architectural design projects (if the intent is to construct them in actual scale, physical form) are the discrete building elements from which the design will be constructed. It is proposed that a single computational model representing individual components supports all of the above "models" and facilitates "viewing"' the design according to the frame of reference of the viewer.

Furthermore, it is the position of the authors that all reasoning stems from this rudimentary level of modeling individual components.

The concept of component representation has been derived from the fact that a "real" building (made from individual components such as nuts, bolts and bar joists) can be "viewed" differently according to the frame of reference of the viewer. Each individual has the ability to infer and abstract from the assemblies of components a variety of different "models" ranging from a visceral, experiential understanding to a very technical, physical understanding. The component concept has already proven to be a valuable tool for reasoning about assemblies, interferences between components, tracing of load path and numerous other component related applications. In order to validate the component-based modeling concept this effort will focus on the development of spatial understanding from the component-based model. The discussions will, therefore, center about the representation of individual components and the development of spatial models and spatial reasoning from the component model. In order to frame the argument that spatial modeling and reasoning can be derived from the component representation, a review of the component-based modeling concept will precede the discussions of spatial issues.

One cannot conduct such studies on real cities except, perhaps, as a point of departure at some specific point in time to provide an initial layout for a city knowing that future forms derived by the studies will diverge from that recorded in history. An entirely imaginary city is therefore chosen. Although the components of this city at the level of individual buildings are taken from known cities in history, this choice does not preclude alternative forms of the city. To some degree, building types are invariants and, as argued in the Appendix, so are the urban typologies into which they may be grouped. In this imaginary city students of urban history play the role of citizens or groups of citizens. As they defend their interests and make concessions, while interacting with each other in their respective roles, they determine the nature of the city as it evolves through the major periods of Western urban history in the form of threedimensional computer models.

My colleague R.J. van Pelt and I presented this approach to the study of urban history previously at ACADIA (Seebohm and van Pelt 1990). Yet we did not pay sufficient attention to the manner in which such urban models should be structured and how the efforts of the participants should be coordinated. In the following sections I therefore review what the requirements are for three-dimensional modeling to support studies in urban history as outlined both from the viewpoint of file structure of the models and other viewpoints which have bearing on this structure. Three alternative software schemes of progressively increasing complexity are then discussed with regard to their ability to satisfy these requirements. This comparative study of software alternatives and their corresponding file structures justifies the present choice of structure in relation to the simpler and better known generic alternatives which do not have the necessary flexibility for structuring the urban model. Such flexibility means, of course, that in the first instance the modeling software is more timeconsuming to learn than a simple point and click package in accord with the now established axiom that ease of learning software tools is inversely related to the functional power of the tools. (Smith 1987).