# Revisiting Problem-Solution Co-Evolution in the Context of Team Conceptual Design Activity
## 4 Discussion
### Implications, Limitations, and Future Work
Although the statistical analysis provided insight into significant correlations between ASE and problem/solution space exploration, as well as the differences between the probabilities of particular sequences of state transitions to appear, larger sample sizes and different design activity scenarios are preferable to validate the research findings. Moreover, some of the employed analyses rely on dividing the experiment protocols into multiple fragments, with an assumption of their independency. A better approach would be to conduct experiments with several subsequent conceptual design tasks, where each task would represent an individual datapoint for modelling the progress of the conceptual design phase. Additional studies are thus required to capture data sets sufficient for further in-depth analyses of team design activity. Besides, the presented research examined only the proportions and sequences of verbalised state transitions, neglecting both the possibly significant effects of non-verbalised acts and without investigating the rationale for the transitions to appearBy not taking into account the non-verbalised (e.g., [81]) as well as the non-observable processes, the research grasps only a single layer of a multi-layered phenomenon, such as team designing. Another missing layer is that of contextualisation; that is, the sequences of protocol strings were in no way linked to the design entities they refer to, nor the team members that performed the state transitions. It must also be noted the synthesis of entities in one space following the exploration of the other space has been interpreted as a proxy for the study of co-evolution. However, these are only potential co-evolution episodes [54], since it is not necessarily the case that all of these transitions concern the same context. Experimental studies encompassing more comprehensive observational approaches and focused strictly on the reasoning for particular state transitions could provide a further understanding of the identified patterns. Still, design research that is based on observation, such as the presented protocol study, is often limited in terms of analysis resources, since it typically involves manual data coding. Hence, future efforts should also take into account the possibilities of full or partial automatization of the coding process (see, e.g., [108; 109]). Besides the additional work required to address the research limitations, there also exist several possible directions for further developments and research extensions. Given the quantifiable process patterns identified using the state-transition model, future research may focus on predictive modelling of team design activity. The resulting models could, for example, be used to suggest particular state transitions and space exploration foci to maximise the co-evolution rate, based on sampled fragments of the team's design activity. In addition, future studies might test and extend the state-transition model beyond the conceptual phase and the engineering design domain. The model could also be used to investigate the effects of different types of prominent phenomena that interact with co-evolution during team design activities, such as uncertainty, fixation, framing, analogies, etc.