Window preference research on a few settings has found that windows are generally preferred and that larger windows are preferred over smaller ones. No theoretical model of window preferences, however, has been proposed. The present experiment was designed to investigate window preferences across a large variety of common spaces and to examine reasons orfactors that may underlie these preferences with the ultimate goal of predicting them. Window preferences, in terms of size, number, and degree of transparency were made for 14 common spaces. Subjects then indicated the factors underlying their specific preferences from a list of 18 potential factors. Results showed that both window preferences and factors vary more widely than previous research would indicate. More important, however, it was demonstrated that the amount of windows desired in a space can be reliably predicted by knowing how important specific factors (e.g., having a view or good ventilation) are to individuals in that space.

We conducted several experiments to determine the characteristics of an optimal wayfinding aid for new users of a complex building. In Experiment 1 wayfinders who used signs found their destinations fastest. Those using you-are-here maps were much slower than even those wayfinders given no aids. The main advantage of signs over you-are-here maps results from information-processing differences: Signs provide clear cues about turns and decisions without requiring study time or imposing a high memory load. In Experiment 2 we found that people prefer routes that require the least amount of energy expenditure. Contrary to findings of previous research, we did not find complexity to be an important variable. A third experiment, using artificial floor plans of buildings, confirmed that minimizing energy is much more important than complexity in determining preferred routes. Finally, in Experiment 4, we investigated wayfinders' heuristics and the information necessary to provide unambiguous signs.

Over the last 50 years, psychologists have included numerous graphics in their journals and textbooks. The textbooks have contained mostly pictures, whereas the journals have contained mostly data graphs. Surprisingly, conceptual graphs (such as a network chart of the relations among types of memory) have been very infrequent. There are two main reasons for this absence of conceptual graphs: a lack of awareness of the important role that they have played in the history of our discipline, and a lack of knowledge about how to make them. Four types of conceptual graphs are presented here: mathematical graphs (e.g., Fechner's law), geometric models (e.g., Henning's smell prism), networks (e.g., Atkinson and Shiffrin's STM-LTM model), and Euler-Venn graphs (e.g., Shiffrin and Schneider's model of control and automatic processes). Suggestions are offered for heuristics that can be used to facilitate the perception of conceptual relations in these graphs. It is argued that appropriate conceptual graphs can help researchers and theorists communicate the "big picture" relevant to their ideas, can help educators more effectively communicate with students, and may help clinical psychologists communicate their ideas to clients better. Once when I returned from a trip, a friend who had never been to the place I had visited asked me what it was like. I told him that it was so big, it filled my eyes in every direction and made me weak with awe. The colors-the oranges, browns, and yellows-were far more intense than I had ever expected. I kept trying to describe it. I made the best comparisons I could by pointing out how different it was from the places we had both been to. But in the end, I could tell that my friend had only the vaguest idea about what the Grand Canyon was like. He simply needed to see it himself. Recently, Glenberg and McDaniel (1992) argued that human communication "really requires an admixture of language and visuospatial formats." According to Glenberg and McDaniel, language cannot be an accurate surrogate for experience. Humans need the organized, detailed representations made available by their perceptual apparatuses. Although Glenberg and McDaniel may have slightly overstated their case, they are not alone in I would like to thank my wife, LeahRuth-Butler, who provided insights and encouragement as I worked on this project. I would also like to thank several colleagues at Ball State who provided feedback on various ideas presented in this paper, as well as some of the characteristics of the graphics: Carl Summers, William Clark, and Paul Biner. Thanks also to the anonymous individual at the SCIP conference who recommended that I refer to the last type of conceptual graphic as Euler graphs, not Venn diagrams. Correspondence should besent to D. Butler, Depart

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Window size preferences were studied in two experiments using a 1/12 scale model. In the first experiment, subjects viewed small-to medium-sized offices. The experiment showed that window preferences are affected by room size. Preferred window size is not a constant proportion of wall size. Rather, a larger proportion is preferred for smaller rooms. Second, the experiment showed that scenes perceived as more beautiful lead to larger preferred windows. Third, office work experience of subjects had no effect on preferences. Experiment 2, which incorporated several changes, confirmed all three of these findings. In addition, this experiment showed that window size preferences are also affected by the type of the room. Subjects viewing the same model preferred smaller windows for a computer work room than for an office.