## 1 Introduction
By combining subjective evaluations with machine learning validation (e.g., Naive Bayes model) and expert assessments, the study ensures robust and reliable results, reducing biases associated with single-author evaluations. The inclusion of participants from diverse academic and cultural backgrounds further enhances the generalizability of the findings, making the study relevant to a broader range of engineering contexts. Additionally, this research integrates the assessment of the Big Five personality traits alongside both self-assessed and test-assessed knowledge, providing a nuanced understanding of how these factors influence decision-making quality and confidence. This dual focus enables a more precise evaluation of the relationship between dispositional characteristics, knowledge, and decision outcomes. This study's practical implications make it particularly valuable. By identifying actionable strategies, such as tailoring educational interventions to align with individual personality traits and emphasizing test-assessed knowledge, this research offers concrete pathways for improving decision-making quality and confidence. Furthermore, the use of simulation games creates a realistic decision-making environment, enhancing the ecological validity of the findings and ensuring their applicability to real-world engineering challenges. In addressing critical gaps in the literature, this study not only contributes to theoretical advancements in the field but also provides practical insights that can be utilized in academic curricula and organizational training programs, thereby establishing its significance and relevance. The primary objective of our research is \"to quantify the impact of designers' domain knowledge on quality of decision within the context of engineering design\". Furthermore, as a supplementary study, we will also assess confidence in decisions as a secondary objective. This study seeks to explore the relationship between personality traits, domain knowledge, and decision-making outcomes in engineering contexts. Specifically, it addresses the following research questions:  
1. How do individual personality traits influence the quality and confidence of decisions made by engineering students? 2. What is the impact of domain knowledge, both self-assessed and test-assessed, on decision-making quality and confidence? 3. How do personality traits and domain knowledge interact to affect decision-making outcomes in engineering tasks? This paper is organized in the following manner. The introductory section of this study emphasizes the importance of personality traits and the competence of decision-makers in the domain of engineering design decision-making. Afterward, the research model and hypotheses will be presented. Following that, the data sources employed, and the methodology utilized for data analysis are outlined. The following part summarizes the results of the effects of various personality traits, as well as self-reported and test-assessed knowledge, in the field of engineering design. The discussion section offers a comprehensive analysis of the theoretical improvements and practical implications. The study concludes by proposing potential avenues for future research. A distinguishing feature of this study is its comprehensive approach to examining personality traits in the context of engineering design. Unlike previous research that primarily addressed personality traits in general contexts, this study specifically evaluates their impact on decision-making quality and confidence within the complex and task-specific environment of engineering design. By integrating the Big Five personality model with both self-assessed and test-assessed knowledge, this research offers a deeper and more precise understanding of how dispositional factors and knowledge interact to influence decision outcomes.