Self-regulated learners strategically manage physical, technological, online, and social resources for learning—by selecting resources that could be useful, reflecting on how useful these resources have been, and adjusting resource use accordingly. We propose a model that conceptualizes resource management as learners’ intentional, self-reflective decisions to explore new resources, exploit (continue to use) previously useful resources, and prune (stop using) previously ineffective resources. We modeled 4,766 students’ reported exploration, exploitation, and pruning between three class exams among four cohorts of an organic chemistry class (i.e., more than 100,000 discrete data points of resource use). Each of these behavioral mechanisms of resource management predicted students’ academic achievement: The more students reported exploring, exploiting, and pruning between their exams, the higher they performed on their subsequent exams, controlling for prior performance. These findings enrich self-regulated learning theories by concretizing the behavioral mechanisms of resource management by which learners take control of their learning.

自我调节的学习者通过选择可能有用的资源，反思这些资源的有用程度并相应地调整资源使用，来战略性地管理用于学习的物理，技术，在线和社交资源。我们提出了一个模型，该模型将资源管理概念化为学习者的有意，自我反省的决策，以探索新资源，开发（继续使用）以前有用的资源，并修剪（停止使用）以前无效的资源。我们对有机化学课程的四个群组中的四个班级之间的三个班级考试之间的4766名学生报告的探索，开发和修剪进行了建模（即，超过100,000个离散的资源使用数据点）。资源管理的这些行为机制均可以预测学生的学业成绩：越来越多的学生报告说，在两次考试之间进行充分的开发和修剪，他们在后续考试中的表现就更高，可以控制先前的表现。这些发现通过具体化学习者控制学习的资源管理行为机制，丰富了自我调节的学习理论。