Cognitive Science versus Cognitive Ergonomics: A dynamic tension or an inevitable schism? Jean-Michel Hoc, Pietro C. Cacciabue, and Erik Hollnagel (Eds.)
Experti and technology: Cognition and human-computer cooperation. Hillsdale, NJ: Erlbaum, 1995. 289 pp. ISBN 0-8058-1511-2. $45 hardback.
Review by
Wayne D. Gray & Brian D. Ehret
In their foreword, the editors give a nod toward the “internationally bad human-computer interaction (HCI) community, at the level of rearch as well as at the level of application” (p. xi). This is the community to which the reviewers belong and as such we eagerly awaited this volume of chapters reporting on the work of the mainly European “large-system” cognitive ergonomics community. After witnessing first-hand the excitement and challenge of applying cognitive theory to HCI, we were more than a little curious as to the success of and challenges to cognitive theory when it is applied to larger scale applications. Alas, for the most part, we were disappointed. While this book contains veral excellent chapters, on the whole we came away with the impression of a community that has isolated itlf from mainstream cognitive theory and has little interest in testing or contributing to that th
英语国家概况eory. Indeed, it is not clear for whom, other than the large-systems community, this book is intended. It is heavily laden with jargon and makes little attempt to establish contact with any other tradition. In addition, the book is somewhat “ur-unfriendly” containing a meager 2.5 page subject index and no author index (references are listed only at the end of the chapter in which they are cited).befullof
Although our review of the book is primarily negative, veral of the chapters are quite good and would justify having your library buy it.
The book is organized into three ctions, the first pertains to cognition in dynamic environments, the cond address experti, and the third deals with human-computer cooperation. The ctions are preceded by an overview chapter and are followed by a conclusion chapter.
Chapter 1 by Hollnagel, Cacciabue, and Hoc organizes and summarizes the large-system perspective and provides pointers into the literature. Of particular note is the importance given to the role of models and simulations in understanding the complex interactions among humans, systems, and tasks.
Section 1 includes four chapters and ems intended to be the theoretical foundations ction. Chapter 2, by Hoc, Amalberti, and Boreham, provides a very high level discussion of diagnosis that c信念的英文
ould benefit from a lessor scope and concrete examples. Chapter 3, by Kjaer-Hann, is a largely out of date review of “Unitary Theories of Cognitive Architectures.”
The two chapters by Caccibue & Hollnagel (ch. 4) and Woods & Roth (ch 5) would like to distinguish between their u of computational cognitive modeling and everyone el’s. The nub of the distinction ems to be between models of “toy tasks” that the authors claim are bad in cognitive theory and models of important, real-world tasks that the authors claim must eschew cognitive theory.宾语从句引导词
It is interesting that computational cognitive modeling has flourished in the HCI community by taking an approach opposite to that advocated here. In a tradition going back at least to Card, Moran, & Newell (1983), the HCI community has paid clo attention to theories of what Caccibue and Hollnagel refer to as “micro-”cognition with the successful goal of applying such
theories to real-world HCI tasks. In recent years the HCI community has embraced cognitive architectures such as Soar, ACT-R, and construction/integration with emerging success (Kirschenbaum, Gray, & Young, in press).
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Although we do not like the distinctions made in the two chapters, we understand the authors’ moti
limited是什么意思vations and offer some distinctions of our own. It is important to distinguish between modeling done for scientific or theoretical purpos versus that done for engineering purpos (the latter has been referred to in the HCI literature as “approximate modeling," Card, et al., 1983). However, we maintain that approximate models can be built upon the foundations established by scientific or theoretical modeling. Modeling not bad upon cognitive theory may work well for complex tasks as long as the tasks involve relatively simple cognition (such as much of expert systems where the complexity is in the task not in the head). However, there are dangers to this approach. The entire infrastructure is arbitrary and less constrained than one bad upon a cognitive architecture. Also, if more than one cognitive mechanism is required (complex cognition) it is not clear whether the various mechanisms will be able to interact correctly. That degree of coordination would require an architecture. While we do not disagree with their goals, we wish our “large-systems” colleagues were more interested in drawing from and contributing to cognitive theory.
Section 2 looks at the development of competence and experti. The ction begins with a clearly written chapter by Boreham on expert-novice differences in medical diagnosis. The remaining chapters are less successful, tending to share three negative characteristics. First, they em largely out of touch with the mainstream rearch on experti as reprented, for
plea try again later example, by the Ericsson & Smith (1991) collection of chapters. Second, many em intent on developing domain-specific theories that make little contact with existing cognitive theory. Third, in their attempt to make theory-bad, taxonomic distinctions they neglect to include ca studies and examples that would make the distinctions concrete.
Section 3 turns to “Cooperation between humans and computers” and contains the best and worst chapters in the book. In chapter 10, Benchekroun, Pavard, & Salembier prent an interesting u of cognitive modeling to predict the influence of a new software system on the communication efficiency of an emergency center. Chapter 11 by Moray, Hiskes, Lee, & Muir is a lovely chapter that shows the application of the social psychology construct of “trust” to human-machine interaction. We left this chapter inspired to read more of the literature on process control.
Chapter 12, by Rizzo, Ferrante, & Bagnara prents a collection of categories and anecdotes on human error. Chapter 13, by Millot & Mandiau promis to compare the distributed AI (DAI) approach and the “more pragmatic human engineering approach” (p. 215) to “implementing a cooperative organization” (p 215). The experiment prented to this end ems poorly motivated or maybe just poorly explained.
Hollnagel’s chapter 14 sheds much heat and smoke but little light on a number of tangential issues while demonstrating a lack of understanding for much of contemporary cognitive theory. For example, on page 230 he talks about “the uless automaton analogy” and “A particular ca is the u of the information processing metaphor (Newell & Simon, 1972) - or even wor,
assuming that a human being is an information processing system (as exemplified by Simon, 1972; Newell, 1990).” Later on the same page he says,
I will not argue that the automaton analogy is ineffectual as a basis for
describing human performance per ; I simply take that for granted. (This point
of view is certainly not always generally accepted and often not even explicitly
stated, for instance, by the mainstream of American Cognitive Science; it is
nevertheless a view which is fairly easy to support.)
On page 240 we are subjected to a rather glib and unmotivated, “the lack of proven theories or methods is deplorable. . . . There are many practitioners, and they all have their little flock of faithful followers” and another, in a similar vein, about AI work on adaptive systems.
While we believe that theories exist to be challenged, we also believe that in the scientific community challengers need to substantiate their asrtions. Indeed, not only is such substance missing, but in the pages that follow Hollnagel propos a theoretical explanation that sounds in keeping with the Newell and Simon account.
picturebox>sleWe had a better time with the next two chapters. Both Boy in chapter 15 and Lind & Larn in chapter 16 embrace contemporary cognitive theory with interesting results. While clearly discusd, Boy’s theory nevertheless remains vague due to the lack of a worked example. Lind and Larn work us through a detailed example of one of their multilevel flow models.
themomentThe summary chapter is generally well written but, for us, Hollnagel’s smoke (for example, pp. 281-282 and his unmotivated attacks on Simon, page 284) obscures any light the chapter may have been intended to shed.
