This paper raises the question, “What is an effective representation framework for organizational process design?” By combining our knowledge of existing process models with data from a field study, the paper develops criteria for an effective process representation. Using these criteria and the case study, the paper integrates the process redesign and information system literatures to develop a representation framework that captures a process' social context. The paper argues that this social context framework, which represents people's motivations, social relationships, and social constraints, gives redesigners a richer sense of the process and allows process redesigners to simultaneously change social and logistic systems. The paper demonstrates the framework and some of its benefits and limitations.

The god of this paper is to iden@ the communication tactics that tiow management teams to successtiy coordinate without becoming overloaded, and to see whether successti coordination and fidom from overload independently Muence team pefiormance.We found that how much teams comnumicatti, what they communicated abou~and the technologies they used to communicate prdlcted coordination and overload.Team coordination but not overload prdlcted team SUWSS.

This article investigates working-memory (WM) failure in phone-based interaction (PBI). We used a computational model of phone-based interaction (PBI USER) to generate predictions about the impact of three factors on WM failure:PBI features (i.e. menu structure), individual differences (i.e., WM capacity), and task characteristics (i.e., number of tasks). Our computational model stipulates that both the storage and the processing of information contribute to WM failure. In practical terms the model and the empirical results indicate that, contrary to guidelines for the design of phone-based interfaces, deep menu hierarchies (no more than three options per menu) do not reduce WM error rates in PBI. At a more theoretical level, the study shows that the use of a computational model in HCI research provides a systematic approach for explaining complex empirical results.

This article proposes a cognitive framework describing the software development process in object-oriented design (OOD) as building internal representations and developing rules. Rule development (method construction) is performed in two problem spaces: a rule space and an instance space. Rules are generated, refined, and evaluated in the rule space by using three main cognitive operations: Infer, Derive, and Evoke. Cognitive activities in the instance space are called mental simulations and are used in conjunction with the Infer operation in the rule space. In an empirical study with college students, we induced different representations to the same problem by using problem isomorphs. Initially, subjects built a representation based on the problem description. As rule development proceeded, the initial internal representation and designed objects were refined, or changed if necessary, to correspond to knowledge gained during rule development. Differences in rule development processes among groups created final designs that are radically different in terms of their level of abstraction and potential reusability. The article concludes by discussing the implications of these results for object-oriented design.

This study aims at developing and empirically testing hypotheses about professional designers' cognitive activities when using object-oriented methodology (OOD) versus using traditional functional decomposition methodologies (TFD). Our preliminary results indicate that OOD may achieve substantial time savings over TFD in logical design. The verbal protocols from a pilot study show that OOD may achieve these time savings: 1) by simplifying rule induction processes used in functional decomposition; 2) by guiding designers on how to build more effective problem spaces; and 3) by allowing designers to run mental simulation more efficiently and more effectively.

We use GOMS models to predict error rates and mental times for translating financial concepts into equations in two widely used interface representations. The first of these, common to spreadsheet packages, is characterized by non-mnemonic naming and absolute referencing of variables. The second, common to non-procedural command-driven software, is characterized by mnemonic naming conventions and relative referencing of variables. These predictions were tested in an experiment using experienced financial analysts. Although the interface that allows mnemonic and relative names (called keyword) takes longer overall, it produces seventy-five percent fewer simple errors and requires less mental effort. Given the overall serious cost of errors in financial models, we conclude that interfaces having the keyword representation are far superior.