Additive Manufacturing (AM) design projects often fail when feasibility and practicality are unclear during product development. To address this, we developed a dual design for additive manufacturing (dual DfAM) worksheet to support users with novice to intermediate DfAM competence. The worksheet incorporates restrictive and opportunistic criteria and calculates a feasibility and practicality index for quick evaluations. Verified through a workshop with 73 engineering students, all participants found the worksheet helpful, and 71 expressed willingness to reuse it in future design projects. Furthermore, we found indications that repeated use of the worksheet could enhance dual DfAM competence, as designs became more feasible and practical. These results highlight the worksheet’s potential as a structured tool for improving dual DfAM assessment and decision-making in product development.

This study investigates the relationship between MBTI personality type diversity and team performance in the first-year “Introduction to Design” course at SUTD. Analysis reveals a statistically significant yet weak correlation between greater MBTI diversity and higher final project grades. Additionally, teams with more introverted (I) and intuitive (N) members tended to perform better, consistent with research linking introverts to deep reflection and structured decision-making, and intuitives to creative problem-solving and future-oriented thinking. Result also shows that teams with INTJ and ISTP members performed better, while those with ISFP members showed lower performance. While these findings suggest personality composition influences team performances, measured in terms of grades, further research is needed to establish causation and underlying mechanisms.

The Sustainable Product Development (SPD) module bridges sustainability concepts into higher education, equipping Master’s students with theoretical knowledge, practical skills, and critical thinking to address sustainability challenges. Combining lectures with hands-on exercises and a flipped classroom, it engages students with tools like Life Cycle Assessment (LCA) and Material Flow Analysis (MFA) to apply sustainability principles in real-world scenarios. Topics such as circular economy, sustainable business models, and ecolabels provide a comprehensive understanding of sustainability across the product lifecycle. The course progresses from foundational principles to advanced applications, linking theory and practice. This prepares students to assess environmental impacts, develop sustainable solutions, and balance competing requirements, meeting industry and societal needs.

This paper aims to assist learners in effectively documenting, transforming, and managing natural language-based information during the Design thinking (DT) process. Further, it seeks to aid evaluators in ensuring traceability and capturing design rationale when assessing the process and outcomes of DT. To achieve this, it presents templates that facilitate documentation and assessment. The effectiveness of these templates was evaluated through an empirical study involving 20 undergraduate students in a design thinking workshop. Analysis of documented templates, questionnaires, and interviews reveals the positive effects of templates on documentation and assessment activities and justifies using proposed documentation templates. The templates can be used as a support tool for process-based documentation as well as assessment activities during the early stages of the DT process.

Engineering design is inherently a collaborative process that requires active engagement and effective communication. Project-based Learning (PBL) is increasingly recognized for fostering these essential skills. However, instructors face challenges in objectively monitoring interactions and providing process-oriented feedback, particularly in large-scale settings where free-riders and disengaged participants affect team dynamics. This study introduces a generative AI approach to deliver real-time, scalable, and empathetic feedback that enhances team collaboration. Findings highlight the potential of AI-driven systems to improve student engagement and learning outcomes, though limitations remain in providing context-specific advice. A secure framework for AI integration in collaborative learning environments is also proposed.

Due to rising product and system complexities, design and engineering have become a team effort that requires well planned and synchronized activities to achieve a high degree of process efficiency and effectiveness. Inspiring high school children to pursue a carreer in this field and preparing undergraduate as well as graduate students for what they will face in practice remains a challenge for societies and institutions worldwide. To overcome this situation, in this paper we present our experience from conducting two courses for Master students and one workshop for high school children based on an online collaboration platform and the digital LEGO framework. We provide insights into the organization of the different formats, the various backgrounds and profiles of their participants, the work results produced by the individual teams, as well as the participants’ learning experience.

Virtual reality (VR) based product evaluation is a growing area of research, but has not yet been studied in the context of design education. In this study, participants evaluated four pairs of product design student models in physical and VR form using a custom VR application. The models included a variety of product types and a variety of prototyping materials. Participants rated the physical and VR models using a rubric adapted from a study of design student prototyping. Significant differences were found in VR versus physical ratings of some model evaluation categories, but only for certain products. The majority of participants preferred the physical model evaluation over the VR evaluation. Our findings suggest that VR product evaluation may be suitable for use in design education contexts, especially when budget or time for physical prototyping is limited.

This paper presents a systematic method and coding scheme to convert concept maps into bi-partite graphs that can be computationally evaluated for topological complexity measurements. The coding scheme is focused on splitting concepts with multiple elements embedded and linking these objectively. The guidance for this is established and the method presented with examples. The motivation for this work is to establish a means to objectively compare concept maps generated by individuals at the beginning and the end of an intervention to measure the impact of the intervention. The reliability of the coding scheme is presented in separate work.

This paper investigates the role of generative Artificial Intelligence (AI) in academic settings, focusing on its effectiveness in providing feedback during the brainstorming phase of the design process. A controlled study with 25 students (n=25) compared feedback from Generative AI (GPT-4) to that from six human educators. Findings reveal that AI-generated feedback enhances student motivation during ideation and facilitates iterative idea refinement. Generative AI’s ability to deliver rapid, scalable feedback proves advantageous in resource-constrained contexts, supporting more effective design processes. This research highlights the potential for AI-driven feedback mechanisms to transform human-AI collaboration in design education, addressing key challenges in personalized and scalable feedback delivery.

Previous studies found ChatGPT-assisted ideation produced lower fluency, flexibility, and originality with shorter ideation sessions. This research hypothesized that a longer 24-minute session would improve ideation outcomes for the ChatGPT-assisted approach and enhance team engagement. Undergraduate students participated in two design workshops: one using a ChatGPT-assisted approach (n=22), the other using only analogue methods (n=17). Results showed that while the analogue group slightly outperformed the ChatGPT group in flexibility and originality, the fluency difference was larger, with the analogue group producing over twice the number of ideas. Evidence suggests team-based ideation behavior has more impact on ideation outcomes. Future research will explore a hybrid individual-to-team approach that combines individual contributions with team collaboration.

This paper presents and experimental study that compares the performance of teams of one, three, and six in terms of generation of requirements from given design prompts. Team size has not been fully explored in the literature in comparative experimental studies for requirements generation. The study was conducted with 116 teams of one, 86 teams of three, and 92 teams of six composed of pre-service engineers in an introductory engineering course. Two prompts were used for the in-class activity. Results indicate that the size of the team did not have significant influence on the number of requirements generated. However, this suggests that there is a difference in efficiency of generating requirements. Analyzing the variety, novelty, and completeness of the requirements generated is reserved for future work. This work helps to lay the foundation for justifying team size.

The diverse knowledge levels among first-year mechanical engineering students lead to significant disparities in individual learning. Intelligent tutoring systems (ITS) offer a solution by providing tailored digital one-to-one instruction, bridging knowledge gaps, and equalizing learning outcomes. This thesis develops an ITS for design theory based on a knowledge-based engineering system, presenting an innovative model that integrates key features of ITS and knowledge-based systems. Implemented in a specialized environment, the system’s application and validation demonstrate its ability to meet context-sensitive design teaching requirements and provide adaptive tutoring.

The power, speed and sophistication of software for computer-aided design (CAD) drafting has revolutionized the design process and the productivity of experienced users. Assessment and mark-up of student drawings in a university class is still time-consuming and requires teaching assistants to be well-versed and proficient. This bottleneck can slow the learning of students if they are not provided with timely and proficient feedback. Software can be developed that uses the quantitative information stored in electronic files for direct comparison with a solution. This however requires an appropriate learning/teaching approach that is complementary with the assessment approach. A learning approach with complementary assessment is outlined along with the developed software for the assessment of large numbers of student submissions in a university level engineering course on drafting.

Requirements engineering is in the design process, translating stakeholder needs into actionable and well-defined specifications. While existing design enablers and tools provide partial solutions, they often fall short in addressing essential aspects such as real-time feedback, lifecycle management, and the use of controlled vocabularies. To bridge these gaps, the Requirements Authoring Design Enabler (RADE), a macro-enabled Excel tool, is presented to support requirement authoring, tracking, and management. RADE integrates features like automated feedback, a dual-mode interface, robust change tracking, and controlled vocabularies. The tool was tested with pre-service engineers with user feedback informing iterative refinements. RADE addresses key challenges in requirements engineering, demonstrating its potential to enhance design outcomes across various domains.

Humans, with their various social identities, form an important part of engineering design. Therefore, designers must reflect on the implications of social identity when designing products. However, little research has examined the quality and content of student designers’ reflections on the importance of social identity in design, and we aim to explore this research gap. The results of our study revealed higher frequencies of responses related to personal experiences and design/action among designers with minoritized social identities. Designers with minoritized identities also provided higher-quality reflections than those in the majority group. These results suggest that designers with different social identities may vary in their ability to critically reflect on the impact of social identity in design and call for the need for new reflective design tools and educational approaches.

This paper, positioned within two universities’ contexts on design education, explores the critical role of awareness in co-design with individuals who have lived experiences. The study introduces a SkillsLab designed to prepare students for managing awkward moments during co-design sessions. A SkillsLab is an intensive learning activity combining hands-on practice, theoretical insights, and practical exercises to bridge the gap between theoretical knowledge on a topic and the real-life application of this knowledge in a project-based setting. The learning activity aims to enhance students’ confidence and skills in navigating awkward moments in co-design. The findings suggest that such educational interventions can significantly improve students’ preparedness for real-world co-design challenges, fostering a more inclusive and empathetic approach to design.

Prototyping is an important component of the engineering design process and has become a frequently studied topic in engineering education. The iterative strategy of creating prototypes, where a single design is refined with repeated improvements, is widely taught and considered to be the default approach to prototyping. However, research has shown that a parallel approach to prototyping, where multiple concepts are tested simultaneously, has potential benefits when exploring a complex design space. Recent studies on parallel prototyping in first-year engineering classrooms have shown that students required to use a parallel strategy produced higher performing final designs than students who used an iterative strategy. This work places the parallel and iterative prototyping strategies in a typical classroom setting where first-year engineering students have control over their strategy.

The possibility of automatic evaluation in online exams offers the advantage of automatic evaluation compared to paper-based exams with manual assessment. Nevertheless, teachers and students have major concerns about digital exams e.g. students are afraid of getting worse grades due to reduced inputs and determined evaluation steps. To analyze these concerns for Engineering Design Education this paper investigates to what extent can be found differences in the results between digital and paper-based examination formats when assessing the same learning outcomes with the same tasks about dimensioning machine elements. The paper contains the transformation of existing paper-based exam tasks into digital automatic evaluable tasks and the data from students participating in a digital exam are compared with data from students with a paper-based exam.

In this research a study environment is presented that enables iterative design in large engineering lectures and show possibilities for investigations at two example lectures from German universities. The initial results show that it is possible for large lecture-hall-based courses to engage in in-depth tasks of engineering design. Design researchers can use the generated data to measure infuences, e.g. the applied methods on specifc design tasks. Two key insights include the potential for large courses to serve as large-scale research environments for design research and the observed effects of infuences on students’ decision-making processes. This approach offers a promising method to further explore the complexities of decision infuences and design optimization in educational settings.

Concept maps have been used to measure student learning and performance comparisons before and after interventions. However, these concept maps may vary in structure and content. The complexity of the maps are difficult to measure when multiple concepts are embedded within individuals nodes. A systematic coding scheme is evaluated for objectivity and reliability using 22 undergraduate researchers. The findings suggest that the coding scheme is suitable and will allow multiple different researchers to generate similar bi-partite graphs from the notional concept maps generated. Additional work is needed to ensure that the semantic content is not invalidated through the coding scheme.