This research describes a tool based on subjective well-being, value, and practical design. We present a Value-Driven Ladder Canvas and 78 Value Insight Cards to support SWB-oriented practice. Studies 1 and 2 focus on discovering insights based on the user’s product experience and converting them into toolkits. Study 3 evaluates and verifies toolkits with SUS, UEQ, PANAS, etc. This research highlights the connection between Needs and positive experiences, providing actionable guidance. Our findings demonstrate that Canvas and Insight cards are designed to improve SWB sufficiently to be useful.

AM enables the design of compliant mechanisms that encode functions directly into geometry. Existing DfAM frameworks rarely address microscale AM, such as two-photon polymerisation (2PP). We present the design process of an airtight, monolithic bellows structure in rigid 2PP resin that serves both as a sensor and an actuator. Through co-evolution of problem and solution, we identify 2PP-specific design considerations and opportunities, including fabrication uncertainties, cross-scale iteration, and design for post-processing, contributing to a case-based DfAM framework for microscale AM.

As digital mental health interventions expand, integrating EU regulations into the design process remains essential but challenging due to their complexity. This study explores how the GDPR, AI Act, EHDS, HTA, MDR, and IVDR influence the design of AI-based mental health chatbots by mapping them onto a framework. The proposed mapping approach provides an overview of the regulatory landscape at each stage, revealing tensions between innovation and compliance as well as opportunities to use regulatory principles as structured checkpoints that guide responsible digital mental health design.

User-product-environment interaction is a dynamics reflected in the concept of affordance and, consequently, in the user experience. The study of these three concepts is indeed evidently interconnected and mutually dependent. Accordingly, this study presents a tool developed for coding the user experience, namely UX grammar (Dabouis et al., 2024a, 2024b), as a suitable framework for further capturing affordances and their characteristics. An application of the UX grammar model, along with affordances evaluations derived from the coding output, is presented to validate the proposed methodology.

Design Space Exploration (DSE) supports the comparison of alternatives in complex, multi-objective problems. Despite advances in human-in-the-loop and visual analytics, most frameworks still assume a predefined design space. This paper reviews DSE and design cognition literature to reveal this conceptual gap and proposes a dynamic cognitive structure of the design space through an extended DSE framework, framing exploration as a co-evolution between cognition and representation.

Requirements quality shapes engineering design, yet natural language specifications remain vulnerable to ambiguity. We investigate how LLMs support ambiguity detection using a hybrid dataset combining NASA JWST requirements with systematically injected defects. Using auto-extracted domain knowledge, we compare a domain-agnostic baseline with a context-aware approach. Incorporating domain knowledge helps LLMs better distinguish genuinely ambiguous requirements from acceptable ones, highlighting the potential of context-aware AI assistants for requirements engineering and early-stage design.

Why do all design acts begin by explicating a bounded frame of work? In design ontology, framing is the selection and representation of components and features in a system to guide perception and decision of designers but remains implicit. As a structural abstraction it becomes an explicit principle, formalised by a computational methodology that parameterises bounds and projects elements of a design having weighted attributes, in a relational context. Thus, the cognitive act becomes epistemic to compute for generating and evaluating frames, aligning design reasoning with scientific discourse.

Collaborative design futuring has gained attention as an inclusive approach for envisioning future societies where external stimuli play a crucial role in stimulating imagination. Building on literature on design stimuli, psychological distance, and co-design, we propose and evaluate a five-layer framework through a multiple-case analysis of fifteen workshops and exhibitions. Through comparative analysis of different workshops, we explored how stimulus characteristics, such as modality, richness, and scenario, influence participant engagement and perceived psychological distance.

Learning MBSE is hindered by abstraction and complex tools. This paper identifies barriers via literature review and interviews to design a RAG-based chatbot acting as a “smart view” for contextual guidance. Evaluated through a semester-long field study and a controlled experiment, the prototype shows high usability and reduces cognitive load. While performance is comparable to traditional e-books, the RAG-enabled system effectively mitigates entry-level barriers and aids authentic project work through stepwise tutoring, offering a scalable, interactive complement to MBSE education.

This paper draws on Method Content Theory and the Method Teaching framework to analyze the User Testing Toolkit, in its dual role as a design and a teaching tool. The paper shows how the toolkit, by supporting the contextualization of user testing in a broader design context, not only support design activities, but also the critical reflection on design context and actions, necessary for development of appropriate design practices. As such, the paper sheds light on how design methods can be developed to support both effective design action and the development of appropriate design practices.

This literature review paper analyses recurring challenges associated with products designed for remanufacturing and links them to areas in which Model-Based Systems Engineering (MBSE) can provide targeted support through the utilisation of SysML models. The paper proposes SysML-based strategies for enhancing requirement traceability, improving lifecycle data and simulation support, enabling compatibility assessment, and facilitating stakeholder data exchange. The conclusion highlights the implications of these insights for future research on MBSE supported Circular Economy (CE) strategies.

Data-driven design increasingly relies on sensor data, yet these thin measurements often lack the experiential context needed to explain why events occur or what users feel and need. This limits their value for human-centred design. Passive and active contextualisation are introduced to describe how meaning is produced through inference and user participation. A real-world case study using See.Sense cycling data from Melbourne shows how combining thin and thick data produces more situated understanding and actionable design insight.

Early integration of circularity into complex system architectures remains ad hoc and weakly verifiable. Model-based systems engineering (MBSE) can address this issue with precise modeling and early verification. This paper presents an artificial intelligence supported MBSE method to integrate circular strategies based on SysML v2 models, highlighting potential changes and enhancements. Generative suggestions are integrated via a regulated workflow with traceable justifications and context-enhanced queries. A use case modeling the print head of a 3D printer illustrates this approach.

This study proposes a new design for a knowledge audit, focusing on human-AI knowledge augmentation within a consulting firm’s setting. It adopts a mixed-method paradigm, including interviews, quantitative surveys and Social Network Analysis, to identify obstacles, facilitators, and AI-mediated flows within a Community of Practice. Findings show strong motivations and AI readiness coexist with poor documentation and codification. The paper reframes the audit as a design-oriented tool for mapping how human–AI collaboration shapes organisational knowledge maturity.

In north-east Scotland the stereotype ‘White-doctor–non-White patients’ is almost reversed, as international medical graduates join the workforce. Psychiatrists from culturally diverse backgrounds in a psychotherapy supervision group explored the benefits of cultural curiosity between clinicians and patients, and among colleagues. The group acknowledges the barriers, obstacles and hurt posed by cultural difference, and at the same time rejoices in the developmental advances that can be achieved for both patient and clinician when these aspects are examined and addressed with curiosity.

Engineer-to-Order (ETO) companies often grow around ad-hoc know-how, and when they scale, usually they must standardize and choose a BOM setup, yet literature offers options but little guidance on how to decide. We propose a Focus Identification Model, a lightweight, tool-agnostic method that profiles context drivers, asks weighted decision questions, and links answers to a go-to setup with explicit governance. Calibrated on two industry cases, it yields a driver heatmap, decision matrix, and governance card to establish a common language and identify fit-for-purpose BOMs with less friction.