![]() According to the latter view, such flashes of insight are typically characterized as involving a major change in the representation of a problem, arising from largely tacit processes of problem elaboration, recoding or constraint relaxation (e.g., Ohlsson, 1992, 2011 Knoblich et al., 1999 see also Bowden et al., 2005). Research on creative problem solving has burgeoned over the past 20 years, with a traditional assumption being that people solve such problems in one of two different ways, that is, either (i) through analytic processes, which involve conscious, explicit thinking that takes the solver closer to a solution in a slow, step-by-step manner (e.g., Fleck and Weisberg, 2004 Ball and Stevens, 2009) or (ii) through insight processes, which involve non-conscious, implicit thinking that gives rise to a sudden and clear realization of how to make progress toward a solution (e.g., Sternberg and Davidson, 1995 Bowden and Jung-Beeman, 1998, 2003a Jung-Beeman et al., 2004). Not surprisingly, creative problem solving is held in especially high regard in all areas of real-world practice. This latter kind of “creative problem solving” is distinguished from other types of problem solving in that it involves the generation of solutions that are both original and effective, with the sole presence of either attribute being insufficient for a solution to be deemed creative (see Runco, 2018). Although problem solving can be fairly mundane (e.g., deciding what to make for your evening meal) it can also lead to solutions that are highly creative (e.g., a delicious new dish prepared by a master chef). It is a central aspect of human cognition that arises across a range of contexts, from everyday activities to the attainment of major scientific advancements and the achievement of important technological, cultural, and artistic developments. Problem solving involves thinking activity that is directed toward the achievement of goals that are not immediately attainable (e.g., Newell and Simon, 1972). The resulting normative data yield solution rates, error rates, solution times, confidence ratings, self-reported strategies and familiarity ratings for 84 rebus puzzles, providing valuable information for the selection and matching of problems in future research. Participants (N = 170 85 for Set A and 85 for Set B) were given 30 s to solve each item, subsequently indicating their confidence in their solution and self-reporting the process used to solve the problem (analysis or insight), followed by the provision of ratings of the familiarity of the solution phrases. The 84 selected problems were thence divided into two sets of 42 items (Set A and Set B), with rebus structure evenly balanced between each set. Eighty-four rebus puzzles were selected from a larger stimulus set of 168 such puzzles and were categorized into six types in relation to the similarity of their structures. ![]() All of the puzzles relate to commonplace English sayings and phrases in the United Kingdom. The current study sought to validate a pool of 84 rebus puzzles in terms of their solution rates, solution times, error rates, solution confidence, self-reported solution strategies, and solution phrase familiarity. Recent investigations have established the value of using rebus puzzles in studying the insight and analytic processes that underpin problem solving. ![]() ![]() ![]() 2Department of Building, Energy and Environmental Engineering, University of Gävle, Gävle, Sweden.1School of Psychology, University of Central Lancashire, Preston, United Kingdom. ![]()
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