Publication detailsBeckmann, J. F. & Goode, N. (2014). The benefit of being naïve and knowing it: the unfavourable impact of perceived context familiarity on learning in complex problem solving tasks. Instructional Science 42(2): 271-290.
- Publication type: Journal Article
- ISSN/ISBN: 0020-4277 (print), 1573-1952 (electronic)
- DOI: 10.1007/s11251-013-9280-7
- Keywords: Complex problem solving, dynamic systems, knowledge acquisition, semanticity, semantic effect
- Further publication details on publisher web site
- Durham Research Online (DRO) - may include full text
Author(s) from Durham
Previous research has found that embedding a problem into a familiar context does not necessarily confer an advantage over a novel context in the acquisition of new knowledge about a complex, dynamic system. In fact, it has been shown that a semantically familiar context can be detrimental to knowledge acquisition. This has been described as the “semantic effect” (Beckmann, Learning and complex problem solving, Bonn, Holos, 1994). The aim of this study was to test two competing explanations that might account for the semantic effect: goal adoption versus assumptions. Participants were asked to learn about the causal structure of a linear system presented on a computer containing three outputs by changing three inputs through goal free exploration. Across four conditions the level of familiarity was experimentally varied through the use of different variable labels. There was no evidence that goal adoption can account for poor knowledge acquisition under familiar conditions. Rather, it appears that a semantically familiar problem context invites a high number of a priori assumptions regarding the interdependency of system variables. These assumptions tend not to be systematically tested during the knowledge acquisition phase. The lack of systematicity in testing a priori assumptions is the main barrier to the acquisition of new knowledge. The semantic effect is in fact an effect of untested presumptions. Implications for research in problem solving, knowledge acquisition and the design of computer-based learning environments are discussed.