Procedural problem solving is an important skill in most technical domains, like programming, but many students reach problem solving impasses and flounder. In most formal learning environments, instructors help students to overcome problem solving impasses by scaffolding initial problem solving. Relying on this type of personalized interaction, however, limits the scale of formal instruction in technical domains, or it limits the efficacy of learning environments without it, like many scalable online learning environments. The present experimental study explored whether learners’ self-explanations of worked examples could be used to provide personalized but non-adaptive scaffolding during initial problem solving to improve later performance. Participants who received their own self-explanations as scaffolding for practice problems performed better on a later problem-solving test than participants who did not receive scaffolding or who received expert’s explanations as scaffolding. These instructional materials were not adaptive, making them easy to distribute at scale, but the use of the learner’s own explanations as scaffolding made them effective.

在大多数技术领域（例如编程）中，过程式问题解决是一项重要技能，但是许多学生遇到了解决问题的僵局和困境。在大多数正式的学习环境中，讲师会通过搭建初始问题解决方案来帮助学生克服问题解决的僵局。但是，依赖于这种类型的个性化交互，限制了技术领域中正式教学的规模，或者像许多可扩展的在线学习环境一样，它限制了没有它的学习环境的效果。本实验研究探讨了学习者对工作示例的自我解释是否可用于在最初的问题解决过程中提供个性化但非自适应的脚手架，以提高以后的表现。接受自己的解释为练习问题的脚手架的参与者在以后的解决问题测验中的表现要好于未接受脚手架或接受专家的解释为脚手架的参与者。这些教学材料没有适应性，使它们易于按比例分配，但是使用学习者自己的解释作为脚手架使它们有效。