Project-Based Learning (PjBL) is widely used in engineering education to promote authentic problem solving and learner agency, yet evidence regarding its role in fostering students' entrepreneurial intention (EI) remains inconclusive. Grounded in Self-Determination Theory (SDT), this study examines whether autonomy, competence, and relatedness mediate the effect of PjBL on entrepreneurial intention in a Microcontroller Systems course. Using a quasi-experimental pretest-posttest control group design, this study involved 64 undergraduate engineering students, divided into a PjBL group (n = 32) and a conventional instruction group (n = 32). Entrepreneurial intention was measured before and after the intervention, while psychological need satisfaction was assessed at the end of the learning process. Data were analyzed using ANCOVA and parallel multiple mediation analysis. The findings show that students in the PjBL group demonstrated higher entrepreneurial intention than those in the conventional instruction group. Although PjBL enhanced students' perceptions of autonomy, competence, and relatedness, these psychological needs did not mediate the relationship between PjBL and entrepreneurial intention. The results suggest that authentic, value-oriented engineering projects may foster entrepreneurial intention more directly through hands-on technical engagement than through general psychological need satisfaction.
Generative artificial intelligence (AI) algorithms have recently been applied to engineering design, particularly to explore design spaces which are too large for humans to feasibly comprehend. This paradigm shift from manual human-driven design to automated AI-driven design requires the designer to take a drastically different approach to design-objective space co-evolution during exploration following problem space definition. However, engineering curricula have not yet caught up to the recent rise of generative AI in design (i.e., Generative Design). This paper presents two sets of educational materials developed to teach Generative Design and reports their effectiveness in teaching undergraduate students. Study 1 investigated participant engineering design self-efficacy before and after completing a curriculum workbook developed to teach the fundamental concepts of human-driven and AI-driven design (using genetic algorithms) with CAD project-based learning activities to experience both design paradigms. Study 2 compared performance on a team design activity before (vs. after) students heard a lecture on AI-driven design and completed a topology optimization-based CAD activity. Studies 1 and 2 found beneficial effects of the curricula on students' engineering design self-efficacy and design artifact performance.
Graduate unemployment in Ghana has intensified national interest in entrepreneurship as a strategic pathway for economic transformation and healthcare resilience. Biomedical Engineering (BME) holds transformative potential for addressing context-specific health challenges, yet a significant gap exists between academic training and successful venture creation. This mixed-methods study investigates entrepreneurial readiness among 56 undergraduate BME students across seven Ghanaian universities. Guided by the Theory of Planned Behaviour (TPB) and the Entrepreneurial Event Model (EEM), the research integrates quantitative indicators of interest and confidence with qualitative analysis of systemic barriers. Findings reveal high entrepreneurial desirability (45.5% reporting maximum interest) driven by a desire to solve local health problems. However, perceived behavioural control is suppressed by significant skill gaps in business model development (82%), intellectual property management (73%), and regulatory navigation (68%). Structural constraints, including a 71.4% lack of specialised mentorship and 64.3% curriculum misalignment, further diminish perceived feasibility. As one of the first empirical studies examining BME entrepre-neurial readiness in an African context, this pilot investigation provides early evidence to guide curriculum and policy reform. The study proposes a conceptual framework for strengthening the BME innovation pipeline in emerging ecosystems, emphasising that technical proficiency must be paired with discipline-specific entrepreneurial scaffolding. These insights inform national policy initiatives, such as Ghana's National Entrepreneurship and Innovation Programme (NEIP), and offer a scalable model for BME curriculum reform across Low-and Middle-Income Countries (LMICs).
Engineering education increasingly requires students to address sustainability in authentic design contexts. At the same time, generative artificial intelligence (AI) is changing how students retrieve information, generate ideas, evaluate solutions, and refine designs. However, there is still limited evidence on how different collaboration forms shape AI-supported design processes and outcomes. This study compared three types of two-person teams - design-only, engineering-only, and cross-disciplinary design and engineering teams (N = 90 students, 45 teams) - in a sustainable campus waste management project with unrestricted AI use. The study examined sustainability awareness, AI acceptance, AI-supported process behaviors, and design outcomes. All three groups showed significant gains in sustainability awareness and AI acceptance, with no significant between-group differences in post-test scores. Clear group differences emerged in process behavior. The Design group relied more on idea generation, the Engineering group relied most on information retrieval and showed the lowest adoption of AI-generated ideas, and the cross-disciplinary group showed a more balanced use of information retrieval and evaluation/optimization. In terms of outcomes, the Design group achieved the highest novelty ratings, whereas the Engineering group achieved the highest feasibility ratings. These findings indicate that collaboration form shapes how AI is adopted during design work and leads to different process configurations and learning outcomes in engineering education.
The engineering education research and practice community needs further understanding of important strategies to recruit underserved groups. Relationship recruiting is an effective recruitment strategy but has not been adopted widely by engineering bridge and success programs, possibly due to lack of awareness. As a part of a larger project based on the Diffusion of Innovations (DOI) theory, the purpose of this qualitative study was to increase understanding of the relationship recruiting with interpersonal communication strategy for engineering bridge and success programs by analyzing and comparing the perceptions of program leaders. We conducted interviews with a total of 8 program leaders from engineering bridge programs (n = 3) and engineering success programs (n = 5). We identified four positive open codes in the Effectiveness category and six negative codes in the Barriers and Challenges categories for implementing the relationship recruiting strategy. We then discovered four themes to represent those ten codes: (1) relationship recruiting and interpersonal communications are effective for recruitment; (2) use students as effective recruiters for relationship recruiting; (3) use a multifaceted approach for relationship recruiting communications; and (4) the external, systemic, structural barriers limit relationship recruiting with interpersonal communication practices in use. We also noted differences and similarities across programs. Our findings will assist engineering bridge and success programs implementing the effective relationship recruiting with interpersonal communication strategy while navigating barriers.
