AI-driven personalized support can help students learn from Open-Ended Learning Environments (OELEs). In this paper, we focus on how to effectively provide repeated hints in OELEs, when students repeat a sub-optimal behavior after receiving a hint on how to recover from the first occurrence of the behavior. We formally compare two repeated hint designs in UnityCT, an OELE that fosters Computational Thinking (CT) via free-form game design in K-6 education, with the long-term goal of providing AI-driven personalized hints.