Developing effective design solutions requires successful idea generation, development and selection. Studies have demonstrated that engineering students face challenges in these idea phases and may struggle to implement recommended practices, hindering the potential for an innovative outcome. The first part of the study investigated student practices in idea generation, development and selection through think-aloud experimental sessions and post-session interviews. Data analysis from mechanical engineering students’ sessions, with think-aloud and interview data, revealed that students focused on existing ideas, assumed requirements that constrained their divergence, limited their development of ideas and did not engage much in idea selection. Then, in the second phase of the study, we implemented a learning intervention that leveraged research-based education practices to examine student adoption of recommended practices. After engaging with the learning blocks, students generated unconventional ideas, abstained from requirement assumptions early in ideation, generated a larger quantity of ideas, developed ideas intentionally and used more rigorous idea selection methods. These outcomes demonstrated that a relatively short and targeted intervention can support students in leveraging recommended approaches to idea generation, development and selection.

Idea selection is crucial in design as it impacts the outcome of a project. A collaborative design activity could be considered as a social process where the interactions and individual states (such as the importance in the team and self-efficacy level) could affect decision-making. It is often seen in design teams that some individuals, referred to as ‘influencers’ in the article have more capacity to influence than others, hence they govern the team process for better or worse. Due to the limited work done in the past to study the effect of these influencers on design outcomes, the work aims at increasing the understanding by presenting some insights from its agent-based simulation. The simulation results show how different influencer team compositions affect design outcomes in terms of quality and exploration of the solutions. The idea selection starts with the agents who are ready with their solution in their ‘mind’. The work presented in this article describes a framework for simulating decision-making during idea selection by considering the influencer and majority effect. The empirical study presented in the article verifies the model logic, that is, the presence of influencer and the majority during idea selection and supports the assumption that individuals’ agreement on solutions proposed by other team members depends on the degree of influence and past agreement. The results of the simulation show that teams with well-defined influencers produced solutions with higher variety and had more uniform contributions from team members, but also produced solutions of lower quality.