Generating own examples for previously encountered new concepts is a common and highly effective learning activity, at least when the examples are of high quality. Unfortunately, however, students are not able to accurately evaluate the quality of their own examples and instructional support measures such as idea unit standards that have been found to enhance the accuracy of self-evaluations in other learning activities, have turned out to be ineffective in example generation. Hence, at least when learners generate examples in self-regulated learning settings in which they scarcely receive instructor feedback, they cannot take beneficial regulation decisions concerning when to continue and when to stop investing effort in example generation. The present study aimed at investigating the benefits of a relatively parsimonious means to enhance judgment accuracy in example generation tasks, i.e. the provision of expert examples as external standards. For this purpose, in a 2x2 factorial experiment we varied whether N = 131 university students were supported by expert example standards (with vs. without) and idea unit standards (with vs. without) in evaluating the quality of self-generated examples that illustrated new declarative concepts. We found that the provision of expert example standards reduced bias and enhanced absolute judgment accuracy, whereas idea unit standards had no beneficial effects. We conclude that expert example standards are a promising means to enhance judgment accuracy in evaluating the quality of self-generated examples.