The integration of sustainability into higher education architectural curricula and student Diploma Projects (DPs) remains limited, necessitating further investigation to improve overall outcomes. This study aims to identify, characterise, and compare existing keyword sources to determine their efficacy in detecting sustainability-related solutions within DPs and to define the characteristics of the most suitable datasets for this purpose. A total of 132 academic, professional, and policy-related Keyword Databases (KDs) were identified and analysed through a multi-stage process. Nine of the best-performing KDs were selected for further development into Keyword Search Lists (KSLs), and their effectiveness in identifying sustainability-related solutions in DPs’ descriptions was tested, confirming the correlation of the results with expert assessments. As a result, a method for identifying, developing, and analysing KSLs was developed, titled Mapping the Linguistic Landscape of Architectural Sustainability (MLLAS). This framework provides a practical tool for the large-scale analysis of how sustainable development is linguistically represented within architectural theses, as well as a theoretical basis for understanding the level of sustainability’s incorporation in architectural education. The results indicate that keyword search constitutes an effective identification method within DPs, regardless of KSL size. The future implementation of the MLLAS framework has been proposed.
Kazanecka-Olejnik et al. (Sun,) studied this question.