Keywords: design science, framework, maturity assessment, MBSE adoption
Astract: As engineering systems become increasingly complex, organizations must adopt strategic approaches to manage the interdependencies of their processes, tools, and teams. Model-Based Systems Engineering (MBSE) offers a promising solution, but transitioning from a traditional SE approach to MBSE is a complex endeavor that requires significant organizational change. This paper addresses the need for structured guidance in this process by proposing a maturity assessment framework that supports organizations in navigating this transition. The proposed framework is developed using a design science based approach and identifies key challenges, pitfalls, and best practices that are organized into several maturity levels of MBSE adoption. This structured, high-level approach provides organizations with the tools to understand their current maturity level, prioritize efforts, and avoid common missteps. The framework allows organizations to tailor the insights to their unique context, ensuring practical applicability. It emphasizes the importance of leadership, cultural readiness, technical tools, workforce development, and modeling practices for successful MBSE implementation.

Keywords: Conceptual Modeling Education, Learning Analytics Dashboards, Social Comparison
Astract: Conceptual modeling education benefits from technological support due to the complex nature of the learning processes required to master modeling skills. Along with existing modeling and prototyping tools, providing feedback to students using Learning Analytics Dashboards (LADs) can enhance their learning experience. To interpret LADs, students are provided with a frame of reference, often peer comparison, although its effectiveness is debated. This study presents two LADs used to provide feedback to students from diverse backgrounds enrolled in a conceptual modeling course: a default-LAD with mastery and progress reference frames, and an extended peer-LAD that also includes a performance reference frame. We examine students’ preferences for LAD visuals, the relationship between their study activity and performance, and the relationship between the use patterns of different LAD versions and student activity and performance. The results show that most of the relationships are significant only for the peer-enhanced LAD and are stronger for students with less modeling experience, underscoring the value of peer LADs for novice modelers.