Students' engagement and learning effectiveness during procedural learning

Abstract

With the growing importance of STEM (science, technology, engineering, and mathematics) subjects, it is imperative to consider how one can effectively learn complex concepts in these fields. Worked examples (where one is presented with the worked-out solution to a problem) and problem-solving (where one attempts to solve a given question) are both suggested for effective learning. Worked examples have been found to be less engaging than problem-solving, though engagement is a prerequisite for the cognitive learning theory which underlies the worked example effect. If engagement with worked examples is low, then differences between the two learning activities might be due to differential engagement in the activities rather than between the mediums themselves. In order to clarify differences in the effectiveness of learning activities while considering engagement, this study uses three different learning activities: problem-solving, static worked examples (where the full solution is shown at once), and sequential worked examples (where the learner can incrementally show the steps of the solution). It was hypothesized that sequential worked examples allow for similar engagement and thus similar performance as problem-solving on a delayed test, more accurate judgements of learning, with lower mental effort. It was found that engagement with problem-solving trials was higher than both worked example conditions, but performance, estimated judgements of learning, ratings of mental effort, difficulty, and interestingness, did not differ between the three groups. The results suggests that sequential worked examples might be utilized in a variety of ways that result in differential engagement.