There are no stupid questions, only ones we think are stupid: The accuracy of self-assessed question asking ability

Question-asking is a crucial yet understudied skill with significant implications for learning and information-seeking. Prior research identifies question complexity as a predictor of question creativity and problem-solving ability. However, little is known about how accurately individuals assess their own question complexity. Across three studies, participants generated questions and self-rated their complexity and creativity. We then compared their self-ratings to objective computational model scores. In Study 1 ( N = 100), self-rated question complexity showed a weak correlation with model ratings ( r = 0.151). Study 2 ( N = 100) replicated and strengthened this relation ( r = 0.296), also revealing a positive correlation for question creativity ( r = 0.254). We also found bias effects for complexity: participants underestimated the complexity of their high-level complexity questions and overestimated their low-level ones. In Study 3 ( N = 101), participants read a training brief before rating, which significantly improved accuracy in self-assessing complexity ( r = 0.453) and creativity ( r = 0.487) and eliminated complexity overestimation. Our study highlights the challenges in self-assessment of questions and prominent cognitive biases. Crucially, our study shows that brief explanations of question complexity substantially improve self-assessment accuracy, highlighting practical implications for educational strategies aimed at enhancing metacognitive awareness of question-asking ability. • Participants' accuracy in judging the complexity and creativity of their own questions is low. • Participants show systematic biases in self-assessing the complexity and creativity of their questions. • Participants underestimated the complexity of their high-level questions and overestimated their low-level ones. • Brief instruction on question complexity improves self-assessment accuracy. • Brief instruction on question complexity improves over-estimation biases.