Problem solving

Problem solving is part of thinking and occurs if an organism or an artificial intelligence system does not know how to proceed from a given state to a desired goal state.

Beginning with the early experimental work of the Gestaltists in Germany (e.g., Duncker, 1935), and continuing through the sixties and early seventies, research on problem solving was typically conducted with relatively simple, laboratory tasks (e.g., Duncker’s "X-ray" problem; Ewert & Lambert’s 1932 "disk" problem, later known as Tower of Hanoi) that were novel to subjects (e.g., Mayer, 1992). Simple novel tasks were used for various reasons: they had clearly defined optimal solutions, they were solvable within a relatively short time frame, subjects’ problem solving steps could be traced, and so on. The underlying assumption was, of course, that simple tasks, such as the Tower of Hanoi, captured the main properties of "real" problems, and that the cognitive processes underlying subjects’ solution attempts on simple problems were representative of the processes engaged in when solving "real" problems. Thus, simple problems were used for reasons of convenience, and generalizations to more complex problems were thought possible. Perhaps the best known and most impressive example of this line of research is the work by Newell and Simon (1972).

However, beginning in the seventies, researchers became increasingly convinced that empirical findings and theoretical concepts derived from simple laboratory tasks were not generalizable to more complex, real-life problems. Even worse, it appeared that the processes underlying CPS in different domains were different from each other (Sternberg, 1995). These realizations have led to rather different responses in North America and 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 (e.g., physics, writing, chess playing) thus relinquishing on 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 Great Britain 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 that are constructed to be similar 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, is interested 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). The two traditions are described in detail by Buchner (1995).

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 be generalized 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).

References

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