ABSTRACT
Students are often susceptible to surface features when learning to solve problems in a new domain. Providing example problems where salient surface features are spuriously correlated with the same problem type may encourage their use (Ben-Zeev & Star, 2001), whereas increasing the variability among superficial features during training may yield more robust knowledge (Schmidt & Bjork, 1992). To better understand the causes and consequences of this phenomenon, we compared the impact of two instructional regimens embodying these extremes and articulated detailed models of students’ surface and deep knowledge resulting from each training procedure, enabling us to distinguish between weak correct knowledge and strong incorrect knowledge.
