Using subgoal learning and self-explanation to improve programming education

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Margulieux, Lauren Elizabeth
Catrambone, Richard
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The present study combined subgoal learning and self-explanation frameworks to improve problem solving performance. Subgoal learning has been used to promote retention and transfer in procedural domains, such as programming. The primary method for learning subgoals, however, has been through passive learning methods, and passive learning methods are typically less effective than constructive learning methods. To promote constructive methods of learning subgoals, a subgoal learning framework was used to guide self-explanation. Self-explanation is an effective method for engaging learners to make sense of new information based on prior knowledge and logical reasoning. Self-explanation is typically more effective when learners receive some guidance, especially if they are novices, because it helps them to focus their attention on relevant information. In the present study, only some of the constructive learning methods produced better problem solving performance than passive learning methods. Learners performed best when they learned constructively and either received hints about the subgoals of the procedure or received feedback on the self-explanations that they constructed, but not when they received both hints and feedback. When students received both types of guidance, they did not perform better than those who learned subgoals through passive learning methods. These findings suggest that constructive learning of subgoals can further improve the benefits of learning subgoals, but there is an optimal level of guidance for students engaging in constructive learning. Providing too much guidance can be as detrimental as providing too little. This nuance is important for educators who engage their students in constructive learning and self-explanation to recognize and promote the best results.
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