Uncertainty is intrinsic to human nature, and in many real world scenarios it is unavoidable. On a daily basis, humans interact with a multitude of different devices, and the importance of uncertainty in data increases steadily. To name just a few, uncertainty can be found in machine learning or weather forecasts, but also in user inputs like calorie intake. While previous work has shown that people prefer the communication of uncertainty on output, it is still unclear if the same holds true for user input. Furthermore, the means of uncertain input communication is a field that has scarcely been explored yet. Nevertheless, to produce valid outputs containing uncertainty, the input uncertainty has to be quantified first. In this thesis we propose nine shape-changing tangible interfaces that support uncertain input. Based on the results of a preliminary study in form of a focus group, we have determined the most promising design and present an implementation of a shape-changing slider. In order to evaluate this design, we conducted an explorative user study. Results of the study show that users prefer to have the possibility of uncertain input. In addition, the prototype was rated to be very suitable for uncertain input with an average rating of 6.83 on a 7 point Likert scale. On a higher level, this provides evidence that shape-changing tangible interfaces fit the task of communicating uncertainty. Overall, the predominantly positive user feedback shows promise in uncertain input communication and encourages future exploration.