Many modern end-user development environments aim to be easier to learn and use by supporting one of two visual modalities: block-based programming or data-flow programming. In this work, we investigate the trade-offs between the two modalities in the context of robotics tasks. These often contain both aspects that are better solved with blocks and others that best fit data-flow programming. To address this style of task, we present and discuss two novel programming environment prototypes. One adapts blocks to better handle nested expressions, as they commonly occur in event and signal processing. The other design is a true hybrid that combines blocks and data-flow graphs within the same programming system. We compare the designs through a controlled experiment with 113 end-user participants, in which we asked them to solve programming and program comprehension tasks using one of the two environments. We find that participants preferred the hybrid environment in direct comparison, but performed better across all tasks and also reported higher usability ratings for blocks. Our findings suggest that block-based programming may have previously unused potential for end-users, which data-flow programming tools might be able to exploit as well.