One of the classic instructional effects associated with the Cognitive Load Theory (CLT) is the worked-example effect in cognitive skill acquisition (see Chapters 2 and 3, this volume; Paas & van Gog, 2006). Worked-out examples consist of a problem formulation, solution steps, and the final solution itself. They are commonplace in the instructional material pertaining to well-structured domains such as mathematics or physics (see Figure 5.1 for an exemplary worked-out example). When CLT researchers discuss “learning from worked-out examples,” they typically mean that after the introduction of one or more domain principles (e.g., mathematical theorem, physics law), learners should be presented with several examples rather than a single example, as it is commonly the case. Despite this emphasis on learning from examples, researchers working in this area acknowledge the importance of requiring learners to solve problems later on in cognitive skill acquisition so that they can reach proficiency in the domain they are studying.

In this chapter, we elaborate the theoretical assumptions and empirical findings involving the studying of worked-out examples and learning by problem solving in different phases of cognitive skill acquisition. Rather than summarizing the extensive literature on example-based learning and its implications for instructional design (for overviews, see Atkinson, Derry, Renkl, & Wortham, 2000, and Renkl, 2005), we instead focus on addressing the issues of: (a) when it is best to study worked-out solutions, (b) when it is best to solve problems, and (c) how the transition between these two learning methods should be structured.