We developed Swarm Chemistry 1.2, a new version of the Swarm Chemistry simulator with an enhanced architecture of interactive evolutionary design for exploring heterogeneous self-propelled particle swarm dynamics. In the new version, each evolutionary operator acts locally and visually to part of the population of swarms on a screen, without causing entire generation changes that were used in earlier versions. This new architecture is intended to represent cognitive actions in human thinking and decision making processes more naturally. We tested the effectiveness of the new architecture through an in-class experiment with college students participating as designers as well as evaluators of swarms. We also measured the effects of mixing and mutation operators to the performance improvement of the design processes. The students' responses showed that the designs produced using the new version received significantly higher ratings from students than those produced using the old one, and also that each of the mixing and mutation operators contributed nearly independently to the improvement of the design quality. These results demonstrate the effectiveness of the new architecture of interactive evolutionary design, as well as the importance of having diverse options of action (i.e., multiple evolutionary operators in this context) in iterative design and decision making processes. This work also presents one of the few examples of human-involved experiments on the statistical evaluation of artificial lifeforms, whose quality (such as "livingness") would be hard to assess without using human cognition at this point.