🤖 AI Summary
This work addresses the inefficiencies inherent in manual construction of reference and influence models within Design Research Methodology (DRM), including poor readability, difficulty in modification, and challenges in tracing evidential support. To overcome these limitations, the paper introduces DREAMS, a novel modeling environment that, for the first time, articulates DRM-specific modeling support requirements. DREAMS incorporates typed causal modeling and symbolic relationship representation, directly anchoring hypotheses, empirical inputs, and literature citations to causal links. It further integrates interactive layout optimization and efficient retrieval mechanisms. Preliminary user evaluations demonstrate that DREAMS significantly reduces model creation and revision time, minimizes node reordering and edge crossings, and enhances both evidential traceability and overall model maintainability.
📝 Abstract
Design Research Methodology (DRM) supports systematic design research through representations such as Reference Models and Impact Models. However, the practical construction and maintenance of these models often remains manual, requiring repeated redrawing, layout adjustment, and separate handling of assumptions, references, and supporting evidence. This can make DRM modelling time-consuming, visually cluttered, and difficult to revise as models increase in complexity. This paper presents DREAMS, an early-stage prototype modelling environment developed to support the creation and maintenance of DRM Reference Models and Impact Models. The tool enables users to construct typed causal models using DRM-relevant elements, define signed causal relationships, and attach assumptions, experiential inputs, and references directly to causal links. It also provides layout support and search functions to improve readability, modifiability, and retrieval of supporting information. A preliminary comparative evaluation with four DRM users was conducted against manual modelling practice. The results indicate reductions in model creation time, revision time, repositioning effort, edge crossings, and evidence retrieval time when using DREAMS. These findings are interpreted as early evidence of practical potential rather than full validation. The contribution of the paper lies in identifying requirements for DRM-aligned modelling support, presenting the design and implementation of DREAMS, and demonstrating its potential to reduce modelling effort and improve traceability in DRM-based research.