This research investigated the influence of different levels of explanation (LoE) for resolving errors in human-robot interaction. We compared different LoEs for different error types in two user studies involving different robot types (manipulator and humanoid) performing different tasks (sorting and physical training). The LoEs were operationalized using two questions: “what” (verbosity) and “why” (justification) and combined to define four LoEs. Each robotic task was implemented with two LoEs, and different LoEs were compared for each task in a between-study design. The study, which included both younger and older adults, found that adding justification to verbosity did not significantly improve user perception or task performance in either robot/ task. Furthermore, the results showed that across both tasks, varying the LoEs did not have a significant effect on error resolution. Notably, most participants successfully resolved errors with the physical training robot, but error resolution was lower for the sorting task.