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Problem solving forms part of thinking. It occurs if an
organism or an artificial intelligence system does
not know how to proceed from a given state to a desired goal state.
The nature of human problem solving has been studied by psychologists over the past hundred years. Beginning with the early
experimental work of the Gestaltists in Germany (e.g. Duncker, 1935), and continuing through the 1960s and early 1970s, research on problem solving
typically conducted relatively simple, laboratory tasks (e.g. Duncker's "X-ray" problem; Ewert & Lambert's 1932 "disk"
problem, later known as Tower of Hanoi) that appeared novel to subjects
(e.g. Mayer, 1992). Various reasons account for the choice of simple novel tasks: they had clearly defined optimal solutions,
they were solvable within a relatively short time frame, researchers could trace subjects' problem-solving steps, and so on. The
researchers made the underlying assumption, of course, that simple tasks such as the Tower of Hanoi captured the main properties
of "real world" problems, and that the cognitive processes underlying subjects' attempts to solve simple problems were
representative of the processes engaged in when solving "real world" problems. Thus researcherts used simple problems for reasons
of convenience, and thought generalizations to more complex problems would become possible. Perhaps the best-known and most
impressive example of this line of research remains the work by Newell and Simon (1972).
However, beginning in the 1970s, researchers became increasingly convinced that empirical findings and theoretical concepts
derived from simple laboratory tasks did not necessarily generalize to more complex, real-life problems. Even worse, it appeared
that the processes underlying creative problem solving in different domains differed from each other (Sternberg, 1995). These
realizations have led to rather different responses in North America and in Europe.
In North America, initiated by the work of Herbert Simon on learning
by doing in semantically rich domains (e.g. Anzai & Simon, 1979; Bhaskar & Simon, 1977), researchers began to investigate
problem solving separately in different natural knowledge domains - such as physics, writing, or chess playing - thus
relinquishing their attempts to extract a global theory of problem solving (e.g. Sternberg & Frensch, 1991). Instead, these
researchers have frequently focused on the development of problem solving within a certain domain, that is on the development of
expertise (e.g. Anderson, Boyle & Reiser, 1985; Chase & Simon, 1973; Chi,
Feltovich & Glaser, 1981). Areas that have attracted rather intensive attention in North America include such diverse fields
as reading (Stanovich & Cunningham, 1991), writing (Bryson, Bereiter, Scardamalia & Joram, 1991), calculation (Sokol
& McCloskey, 1991), political decision making (Voss, Wolfe, Lawrence & Engle, 1991), managerial problem solving (Wagner,
1991), lawyers' reasoning (Amsel, Langer & Loutzenhiser, 1991), mechanical problem solving (Hegarty, 1991), problem solving
in electronics (Lesgold & Lajoie, 1991), computer skills (Kay, 1991), game playing (Frensch & Sternberg, 1991), and
personal problem solving (Heppner & Krauskopf, 1987).
In Europe, two main approaches have surfaced, one initiated by Donald Broadbent (1977; see Berry & Broadbent, 1995) in the United Kingdom and the
other one by Dietrich Dörner (1975, 1985; see Dörner & Wearing,
1995) in Germany. The two approaches have in common an emphasis on relatively complex, semantically rich, computerized laboratory
tasks, constructed to resemble to real-life problems. The approaches differ somewhat in their theoretical goals and methodology,
however. The tradition initiated by Broadbent emphasizes the distinction between cognitive problem-solving processes that operate
under awareness versus outside of awareness, and typically employs mathematically well-defined computerized systems. The
tradition initiated by Dörner, on the other hand, has an interest in the interplay of the cognitive, motivational, and social
components of problem solving, and utilizes very complex computerized scenarios that contain up to 2,000 highly interconnected
variables (e.g., Dörner, Kreuzig, Reither & Stäudel's 1983 LOHHAUSEN project; Ringelband, Misiak & Kluwe, 1990). Buchner
(1995) describes the two traditions in detail.
To sum up, researchers' realization that problem-solving processes differ across knowledge domains and across levels of
expertise (e.g. Sternberg, 1995) and that, consequently, findings obtained in the laboratory cannot necessarily generalize to
problem-solving situations outside the laboratory, has during the past two decades, led to an emphasis on real-world problem
solving. This emphasis has been expressed quite differently in North America and Europe, however. Whereas North American research
has typically concentrated on studying problem solving in separate, natural knowledge domains, much of the European research has
focused on novel, complex problems, and has been performed with computerized scenarios (see Funke, 1991, for an overview).
See also
- TRIZ, the Theory of inventive problem-solving developed from the analysis of 200,000
Russian patents.
External links
References
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