Thomas W. Malone

The interdisciplinary study of coordination

This survey characterizes an emerging research area, sometimes called coordination theory, that focuses on the interdisciplinary study of coordination. Research in this area uses and extends ideas about coordination from disciplines such as computer science, organization theory, operations research, economics, linguistics, and psychology. A key insight of the framework presented here is that coordination can be seen as the process of managing dependencies among activities. Further progress, therefore, should be possible by characterizing different kinds of dependencies and identifying the coordination processes that can be used to manage them. A variety of processes are analyzed from this perspective, and commonalities across disciplines are identified. Processes analyzed include those for managing shared resources, producer/consumer relationships, simultaneity constraints, and task/subtask dependencies. Section 3 summarizes ways of applying a coordination perspective in three different domains:(1) understanding the effects of information technology on human organizations and markets, (2) designing cooperative work tools, and (3) designing distributed and parallel computer systems. In the final section, elements of a research agenda in this new area are briefly outlined.

Toward a Theory of Intrinsically Motivating Instruction

First, a number of previous theories of intrinsic motivation are reviewed. Then, several studies of highly motivating computer games are described. These studies focus on what makes the games fun, not on what makes them educational. Finally, with this background, a rudimentary theory of intrinsically motivating instruction is developed, based on three categories: challenge, fantasy, and curiosity. Challenge is hypothesized to depend on goals with uncertain outcomes. Several ways of making outcomes uncertain are discussed, including variable difficulty level, multiple level goals, hidden information, and randomness. Fantasy is claimed to have both cognitive and emotional advantages in designing instructional environments. A distinction is made between extrinsic fantasies that depend only weakly on the skill used in a game, and intrinsic fantasies that are intimately related to the use of the skill. Curiosity is separated into sensory and cognitive components, and it is suggested that cognitive curiosity can be aroused by making learners believe their knowledge structures are incomplete, inconsistent, or unparsimonious.

Evidence for a Collective Intelligence Factor in the Performance of Human Groups

Meeting of Minds The performance of humans across a range of different kinds of cognitive tasks has been encapsulated as a common statistical factor called g or general intelligence factor. What intelligence actually is, is unclear and hotly debated, yet there is a reproducible association of g with performance outcomes, such as income and academic achievement. Woolley et al. (p. 686, published online 30 September) report a psychometric methodology for quantifying a factor termed “collective intelligence” (c), which reflects how well groups perform on a similarly diverse set of group problem-solving tasks. The primary contributors to c appear to be the g factors of the group members, along with a propensity toward social sensitivity—in essence, how well individuals work with others. A metric for group performance on a battery of cognitive tasks yields a group intelligence quantity: collective intelligence. Psychologists have repeatedly shown that a single statistical factor—often called “general intelligence”—emerges from the correlations among people’s performance on a wide variety of cognitive tasks. But no one has systematically examined whether a similar kind of “collective intelligence” exists for groups of people. In two studies with 699 people, working in groups of two to five, we find converging evidence of a general collective intelligence factor that explains a group’s performance on a wide variety of tasks. This “c factor” is not strongly correlated with the average or maximum individual intelligence of group members but is correlated with the average social sensitivity of group members, the equality in distribution of conversational turn-taking, and the proportion of females in the group.

What is coordination theory and how can it help design cooperative work systems

It is possible to design cooperative work tools based only on “common sense” and good intuitions. But the history of technology is replete with examples of good theories greatly aiding the development of useful technology. Where, then, might we look for theories to help us design computer-supported cooperative work tools? In this paper, we will describe one possible perspective—the interdisciplinary study of coordination—that focuses, in part, on how people work together now and how they might do so differently with new information technologies. In one sense, there is little that is new about the study of coordination. Many different disciplines—including computer science, sociology, political science, management science, systems theory, economics, linguistics, and psychology—have all dealt, in one way or another, with fundamental questions about coordination. Furthermore, several previous writers have suggested that theories about coordination are likely to be important for designing cooperative work tools (e.g., [Holt88], [Wino86]). We hope to suggest here, however, that the potential for fruitful interdisciplinary connections concerning coordination is much greater than has as yet been widely appreciated. For instance, we believe that fundamentally similar coordination phenomena arise—unrecognized as such—in many of the fields listed above. Though a single coherent body of theory about coordination does not yet exist, many different disciplines could both contribute to and benefit from more general theories of coordination. Of particular interest to researchers in the field of computer-supported cooperative work is the prospect of drawing on a much richer body of existing and future work in these fields than has previously been suggested. In this paper, we will first describe what we mean by “coordination theory” and give examples of how previous research on computer-supported cooperative work can be interpreted from this perspective. We will then suggest one way of developing this perspective further by proposing tentative definitions of coordination and analyzing its components in more detail.

Intelligent information-sharing systems

The Information Lens system is a prototype intelligent information-sharing system that is designed to include not only good user interfaces for supporting the problem-solving activity of individuals, but also good organizational interfaces for supporting the problem-solving activities of groups.

Does information technology lead to smaller firms

Many changes in the organization of work in the United States since 1975 have been attributed to the increased capabilities and use of information technology IT in business. However, few studies have attempted to empirically examine these relationships. The primary goal of this paper is to assess the hypothesis that investments in information technology are at least partially responsible for the important organizational change, the shift of economic activity to smaller firms. We examine this hypothesis using industry-level data on IT capital and four measures of firm size, including employees and sales per firm. We find broad evidence that investment in IT is significantly associated with subsequent decreases in the average size of firms. We also find that these decreases in firm size are most pronounced two to three years after the IT investment is made.

Heuristics for designing enjoyable user interfaces: Lessons from computer games

In this paper, I will discuss two questions: (1) Why are computer games so captivating? and (2) How can the features that make computer games captivating be used to make other user interfaces interesting and enjoyable to use? After briefly summarizing several studies of what makes computer games fun, I will discuss some guidelines for designing enjoyable user interfaces. Even though I will focus primarily on what makes systems enjoyable, I will suggest how some of the same features that make systems enjoyable can also make them easier to learn and to use.

What makes things fun to learn? heuristics for designing instructional computer games

In this paper, I will describe my intuitions about what makes computer games fun. More detailed descriptions of the experiments and the theory on which this paper is based are given by Malone (1980a, 1980b). My primary goal here is to provide a set of heuristics or guidelines for designers of instructional computer games. I have articulated and organized common sense principles to spark the creativity of instructional designers (see Banet, 1979, for an unstructured list of similar principles). To demonstrate the usefulness of these principles, I have included several applications to actual or proposed instructional games. Throughout the paper I emphasize games with educational uses, but I focus on what makes the games fun, not on what makes them educational. Though I will not emphasize the point in this paper, these same ideas can be applied to other educational environments and life situations. In a sense, the categories I will describe constitute a general taxonomy of intrinsic motivation—of what makes an activity fun or rewarding for its own sake rather than for the sake of some external reward (See Lepper and Greene, 1979). I think the essential characteristics of good computer games and other intrinsically enjoyable situations can be organized into three categories: challenge, fantasy, and curiosity.

The dawn of the E-lance economy

Will the large industrial corporation dominate the twenty-first century as it did the twentieth? Maybe not. Drawing on their research at MITs Initiative on Inventing the Organizations of the 21st Century, Thomas Malone and Robert Laubacher postulate a world in which business is not controlled through a stable chain of management in a large, permanent company. Rather, it is carried out autonomously by independent contractors connected through personal computers and electronic networks. These electronically connected free-lancers-e-lancers-would join together into fluid and temporary networks to produce and sell goods and services. When the job is done--after a day, a month, a year--the network would dissolve and its members would again become independent agents. Far from being a wild hypothesis, the e-lance economy is, in many ways, already upon us. We see it in the rise of outsourcing and telecommuting, in the increasing importance within corporations of ad-hoc project teams, and in the evolution of the Internet. Most of the necessary building blocks of this type of business organization--efficient networks, data interchange standards, groupware, electronic currency, venture capital micromarkets--are either in place or under development. What is lagging behind is our imagination. But, the authors contend, it is important to consider sooner rather than later the profound implications of how such an e-lance economy might work. They examine the opportunities, and the problems, that may arise and anticipate how the role of managers may change fundamentally--or possibly even disappear altogether.

Modeling the Performance of Organizational Structures

We develop models for comparing the performance of coordination structures that appear in a wide variety of systems, including human organizations and computer systems. First, we define four generic structures: product hierarchies, functional hierarchies, centralized markets, and decentralized markets. Then, drawing primarily on queueing models, we rank these structures in terms of three performance measures: production costs, coordination costs, and vulnerability costs. The models show how changes in the values of these performance measures affect the desirabilities of the different structures. Then, we show how these simple relationships between performance measures and the desirabilities of structures are consistent with a surprising range of phenomena, including; 1 major historical shifts in the dominant organizational forms used by American businesses, and 2 the evolution of computing system architectures. Finally, we use the models to suggest the possible future evolution of both human and computer systems.