Studies of scientific discovery: Complementary approaches and convergent findings.

Abstract

This review integrates 4 major approaches to the study of science-historical accounts of scientific discoveries, psychological experiments with nonscientists working on tasks related to scientific discoveries, direct observation of ongoing scientific laboratories, and computational modeling of scientific discovery processes-by viewing them through the lens of the theory of human problem solving. The authors provide a brief justification for the study of scientific discovery, a summary of the major approaches, and criteria for comparing and contrasting them. Then, they apply these criteria to the different approaches and indicate their complementarities. Finally, they provide several examples of convergent principles of the process of scientific discovery.The central thesis of this article is that although research on scientific discovery has taken many different paths, these paths show remarkable convergence on key aspects of the discovery processes, allowing one to aspire to a general theory of scientific discovery. This convergence is often obscured by the disparate cultures, research methodologies, and theoretical foundations of the various disciplines that study scientific discovery, including history and sociology as well as those within the cognitive sciences (e.g., psychology, philosophy, and artificial intelligence).Despite these disciplinary differences, common concepts and terminology can express the central ideas and findings about scientific discovery from the various disciplines, treating discovery as a particular species of human problem solving. Moreover, we may be able to use these concepts and this vocabulary over an even broader domain to converge toward a common account of discovery in many areas of human endeavor: practical, scientific, and artistic, occurring both in everyday life and in specialized technical and professional domains.The doing of science has long attracted the attention of philosophers, historians, anthropologists, and sociologists. More recently, psychologists also have begun to turn their attention to the phenomena of scientific thinking, and there is now a large and rapidly growing literature on the psychology of science. (A good description of the field in its infancy can be found in Tweney, Doherty, & Mynatt, 1981, and a recent summary of topics and findings from investigations of the developmental, personality, cognitive, and social psychology of science can be found in Feist & Gorman, 1998).Our review links four major approaches to the study of science-historical accounts of scientific discoveries, laboratory experiments with nonscientists working on tasks related to scientific discoveries, direct observation of ongoing scientific laboratories, and computational modeling of scientific discovery processes-by

Taking Nothing for Granted in Management Education: A Systemic Perspective on the Role of Reflective Questioning

“…The literature suggests that major challenges and problems, for example in the form of knowledge gaps, provoke cognitive processing (Klahr & Simon, 1999;Ng et al, 2009) and possibly also cognitive change (VanLehn, 1996). Rather than assuming that major challenges directly affect or drive questioning activity, we argue that the underlying mechanism here is the generation of doubt.…”

Computer-Based Scaffolding Strategy

“…However, there is a strong evidence that problem-solving involves a mix of domain-specific and generic skills (Klahr & Simon, 1999;Molnár, Greiff, & Csapó, 2013;Perkins & Salomon, 1989;Schunn & Anderson, 1999). In this way, it is important to consider the nature of the subskill that one wishes to support through scaffolding in order to decide whether to use context-specific or generic scaffolding (Belland, Gu, et al, 2013).…”

Conclusion

“…Much evidence indicates that scientific problem-solving in fact incorporates a mix of domain-specific and generic processes (Klahr & Simon, 1999;Molnár, Greiff, & Csapó, 2013;Perkins & Salomon, 1989;Schunn & Anderson, 1999). For example, evaluating sources can involve domain-specific knowledge, but the underlying strategy can be considered generic (Smith, 2002).…”