INTELLIGENT GRAPHICS AND MEDIA RICHNESS: REDEFINING TEXT AS A MEDIUM

One of the recent trends in information modeling has been the development of plain-text based (e.g. XML) markup languages for graphics, a practice which affords functional manipulation of images using various kinds of indexing, searching, and formatting techniques that apply to text-based information. But how does this trend, essentially an effort to render images in textual form, fit with theories of media and information richness? (MRT, IRT). The theory of media richness argues that the complex a task is, the richer a media should be used. Thus, is this simply an effort to translate messages from rich to leaner media in order to more efficiently deal with them, (i.e. an idea which supports theories of media/information richness)? Or is it a trend that challenges the definition of "richness" in some way? To explain this phenomenon, we use the case of intelligent graphics. Before moving into the details of whether the way in which intelligent graphics is interfaced in a plain text format satisfies the definition of richness or if the media richness theory is supported, we can first explain how intelligent graphics is used. Intelligent graphics is a form of graphic data that contain graphical objects and associated metadata that cause the graphical objects to be responsive to user-generated or external events (Gebhardt & Gallant, 2000). It is the opportunity to present the combination of text and graphic data in a cohesive whole that is intelligent graphics' major advantage to the end user.
This paper analyzes the question of which is considered as the medium and which as an input towards designing the medium. The answer to this question will decide how equivocal the task is and how it can be addressed. But, we very much agree with the theory of media richness in its proposition that the medium is rich or lean based on its organizational context and how it is used. The central argument in this paper is that the role played by XML in this context has allowed us to consider text and graphics in equal footing. Thus, under XML practice, any form of front end equivocality has been dealt with textually at the back end, irrespective of the extent to which graphics and text were involved in the front end. Thus, it is not correct to say that with increasing equivocality in the front end, a richer medium has not been used. Intelligent graphics can be a brightest example of a rich medium. However, this rich medium was controlled by text at the back end independent of equivocality. Hence this paper argues a new way of looking into richness without discarding the main idea of media richness theory which argues that to deal with more equivocality, one needs a richer medium.
This paper argues that the above argument will help course designers author text and graphics optimally in multiple educational context and with varying levels of task complexity and instructional needs. Intelligent graphics can be factored into course design where complex geometrical figures and shapes needs to be demonstrated, complex dynamic instructions with objects and processes are explained. Rich and complex processes with equivocality can be demonstrated with a richer application of a leaner medium like text. This also drives home a point for technical writers who are increasingly tilting towards minimalist design. The argument for them is that to get rid of associated text in instructional situations, does not necessarily mean that text is not in use.