What is the Trouble with Transfer

What is the Trouble with Transfer? John E. Opfer (opfer.7@osu.edu) 245 Psychology Building, 1835 Neil Ave. Mall Columbus, OH 43210 Clarissa A. Thompson (thompson.1345@osu.edu) 125 Psychology Building, 1835 Neil Ave. Mall Columbus, OH 43210 To add to this already daunting list, we propose a novel (yet somewhat more optimistic) explanation for why transfer is difficult to elicit in microgenetic studies in particular and possibly other studies more generally—proactive interference from previous practice. The basic premise of our account is that when children have practice on a task without any feedback (e.g., when they complete a pretest for an experimenter), children must use some representation to complete that task, and the more they use that representation, the greater the strength of the representation, and the more likely children will continue using it (Siegler & Shipley, 1995). Under circumstances in which the representations used on the task are already appropriate, pretests can facilitate transfer (“practice makes perfect”) (Roediger & Karpicke, 2006; Gick & Holyoak, 1983). However, when representations are inappropriate, practice on a pretest makes imperfect because practice merely strengthens the inappropriate representation and thereby blocks transfer of the more optimal representations learned during training (Gick & Holyoak, 1980). If true, this explanation is not a trivial one: it suggests that the trouble with transfer is at least partly an experimental artifact of studies that pretest the treatment and control groups. To test our practice interference hypothesis, we used Solomon and Lessac’s (1968) four-group design to assess the independent and interactive effects of treatment (feedback) and pretesting on children’s judgments of numerical magnitude. The tasks we chose were ones where previous cross-sectional (Laski & Siegler, 2005; Siegler & Opfer, 2003) and microgenetic (Opfer & Siegler, in press) studies had shown that young children use an inappropriate (logarithmic) representation before using an appropriate (linear) one (e.g., younger children judge 150 to be closer to 1000 than to 1, whereas older children judge 150 to be closer to 1 than to 1000). In the first task, children were asked to make estimates of numerical quantity (e.g., where 150 would fall on a line flanked by 0 and 1000), and they were given feedback on their estimates so they would learn to use a linear representation (as in Opfer & Siegler, in press). In the second task, children were asked to categorize numerals by their magnitude (e.g., whether 150 is a small or big number in the context of the 0-1000 range); this is the task where we hoped children would transfer their learning. On the assumption that the two tasks tapped a common representation, we predicted that children’s learning of the linear representation on the number line estimation task would transfer to their category Abstract Spontaneous transfer of learning is widely reported to be difficult to elicit. We hypothesized that one reason this finding is so widespread is that pretests proactively interfere with performance on transfer. To test this hypothesis, we examined transfer of learning across two numerical tasks (number line estimation and categorization) in which similar representational changes have been observed. Children who were given feedback on the number line estimation task learned to use a linear representation of numerical quantity instead of a logarithmic one, but simply providing children with practice on the categorization pretest led them to continue using a logarithmic representation on the same task, which they otherwise abandoned with surprising frequency. Keywords: transfer of learning, representational change, proactive interference, numeric cognition, and pretests The Trouble with Transfer Despite the importance of transferring knowledge—whether from domain to domain, from school to everyday life, or from everyday life to school—spontaneous transfer is notoriously difficult to elicit, with learners typically generalizing new approaches to a much narrower set of problems than is optimal (Barnett & Ceci, 1992; Gick & Holyoak, 1983; Singley & Anderson, 1989; Thorndike, 1922). This difficulty is not simply because initial learning is incomplete or unstable; even in microgenetic studies of children’s learning, which allow the stability of new knowledge to be established by obtaining a dense sampling of children’s thinking over time by means of trial-to-trial assessments, children very often under-extend novel solutions (see Siegler, 2006, for a review of 105 microgenetic studies examining the issue). Numerous explanations have been proposed to identify why transfer is so difficult for learners to achieve. These explanations have included the degree of overlap in production rules between the base and transfer domain (Singley & Anderson, 1989), where attention is directed during learning (Anderson, Reder, & Simon, 1996), lack of structural similarity between the base domain and transfer domain (Gick & Holyoak, 1983), the stability and encoding of initial learning (Opfer & Siegler, 2004), and insufficient prior knowledge in the base domain (Brown, Kane, & Echols, 1986). Indeed, the many possible impediments to transfer have led some investigators to posit the somewhat pessimistic conclusion that learning is universally narrow and “situation specific” (Lave, 1988).