Public buildings play a critical role in national decarbonization strategies and green energy transitions due to their high energy consumption densities, large occupant capacities, and potential to drive public awareness. Optimizing energy efficiency in these structures not only alleviates the financial burden on public budgets but also serves as a benchmark for sustainable urban development. To investigate the energy-saving potentials, thermal comfort dynamics, and financial feasibilities within this sector, this study selects two university buildings from two different countries with distinct climatic, structural, and operational profiles as comparative case studies: university buildings in Türkiye (TR) and Italy (IT), respectively. A total of seven tailored retrofitting scenarios were developed based on country-specific legislative frameworks and subsidy mechanisms: the Minimum Environmental Criteria (CAM) and Conto Termico 3.0 for Italy, and the Public Buildings Energy Efficiency Project (KABEV), Energy Performance Contracting (EPC), and Nearly Zero Energy Buildings (NSEB) mandates for Türkiye. The scenarios evaluate deep building envelope insulation, high-efficiency window replacements, lighting automation (LED with daylighting controls), mechanical ventilation with heat recovery units (HRV), air-to-water heat pump integrations, and rooftop photovoltaic (PV) installations using calibrated DesignBuilder simulation models. The quantitative results demonstrate that country-specific green building incentives drastically enhance both the energy performance and financial viability of deep retrofits. For the Turkish case study, the comprehensive near-zero energy building (nZEB) retrofitting package (TR-4) successfully reduced annual primary energy consumption by 75% (from 284 to 71 kWh/m2·year) and cut annual thermal comfort discomfort hours by 72% (from 3147 to 880 h), yielding a Subsidized Net Present Value (NPV) of +310,600 €. Similarly, for the Italian case study, the holistic retrofit combined with rooftop photovoltaic integration (IT-4) achieved an 80% energy reduction (dropping from 128 to 25.6 kWh/m2·year), minimized annual discomfort hours to 45 h, and generated a Subsidized NPV of +425,500 €. Furthermore, national incentive mechanisms shortened simple payback periods by more than half, establishing that targeted public policy is vital to accelerate public sector building decarbonization while ensuring long-term fiscal profitability.
The use of photovoltaic technologies in building envelopes has attracted more and more interest as a promising solution to building sustainability by considering energy efficiency, economic feasibility, and environmental impact issues altogether. This paper will provide an overall comparative analysis on Building-Integrated Photovoltaic (BIPV) systems versus traditional building envelope materials based on a multi-dimensional analysis model. It is demonstrated in the analysis of energy performance that BIPV systems contribute greatly to building energy performance by capturing on-site renewable energy and reducing cooling loads through shading and regulated solar heat gain, in contrast to traditional materials, which only provide passive thermal insulation and energy conservation. Life cycle-based economic analysis shows that despite the higher initial costs of BIPV systems, thematic savings in long-run operations and lower requirements of electricity mean BIPV systems have better economic performance during the life of building services as compared to traditional envelopes, which offer lower upfront costs but have greater cumulative energy costs associated with their application. Environmental performance scorecard BIPV systems are shown to lead to significant reductions in greenhouse gas emissions through the replacement of grid-based electricity, and even though greater energy use is involved in the manufacturing and installation of BIPV systems, the operational carbon savings outweigh these effects in a relatively short time, leading to a net-positive lifecycle environmental impact. The overall multi-criteria comparison established an integrated viewpoint to demonstrate that BIPV systems generally outperform traditional envelope materials in energy, economical, and environmental aspects. The results underline the significance of lifecycle and context-related design approaches to building envelope solution choices in assisting the achievement of energy efficiency, economic stability, and environmental sustainability in the long term.
Transforming concepts into architectural designs is challenging, as it requires clear ideas and the ability to visualise them. AI-powered text-to-image tools help designers quickly convert concepts into visual representations, enabling faster exploration of design alternatives. This study introduces a proposed ten-step numerical procedure for assessing the richness of textual prompts submitted to text-to-image generative AI tools within an architectural design studio. Twenty-three architecture students were enrolled in the design studio; twenty-two submitted analyzable text prompts as part of a design assignment requiring AI-assisted conceptual visualisation. Each prompt was scored across seven weighted dimensions (subject specificity, style and medium, composition and framing, lighting and atmosphere, colour and palette, quality modifiers, and negative clauses) to produce a composite Prompt Richness Index (R, scale 0–100). Corresponding AI-generated images were independently scored using a parallel Output Richness Index (O, scale 0–100). Pearson’s r between per-student average R and O yielded r = 0.940 (p < 0.001, 95% confidence interval [0.86, 0.98]), confirming a nearly perfect positive linear relationship. Rich-tier prompts were produced by two students and yielded the most architecturally coherent and visually distinctive outputs. Two students produced Sparse-tier prompts (average R < 30) and consistently received undifferentiated, generically rendered outputs. Two further students scored just above the Sparse threshold but showed similarly limited output differentiation. Class-wide deficits were identified in lighting/atmosphere description and negative clause usage. Eight pedagogical recommendations are derived from the findings to guide prompt learning instruction in AI-integrated design studios.
Urban public spaces matter for young people, yet how youth visually engage with the spatial elements of Indian cities remains largely unstudied. This exploratory study uses screen-based eye tracking to examine how 43 design-discipline students (aged 18–29) allocate visual attention across urban public space scenes in Jaipur, India. Thirty photographic stimuli sampling five Lynch-derived spatial elements—edge, landmark, path, plaza, and transit node—across six public spaces were each analyzed through four semantic areas of interest (built form, human and vehicular activity, natural elements, and circulation), using fixation count, total fixation duration, time to first fixation, and visit count. Attention was allocated unevenly: built form and human activity dominated the youth gaze, while natural elements consistently drew less focal attention—interpreted as restorative background rather than low importance. Landmarks anchored attention most strongly and transit nodes least. Notably, socially active and visually complex elements did not capture the gaze earliest but held it longest, suggesting that what sustains youth attention is dissociable from what initially attracts it. Inferential tests are treated as exploratory given the repeated-measures design. As the first AOI-based account of youth visual attention in Indian heritage public space, this study offers a transferable protocol and preliminary, exploratory directions for youth-responsive design—including visual anchoring at neglected transit nodes and the use of greenery for ambient comfort rather than focal emphasis.
Early-stage architectural design is characterized by high decision uncertainty, ill-defined requirements, and limited opportunities to elicit reliable user feedback, despite the disproportionate impact of early decisions on downstream outcomes. While recent AI-enabled design tools increasingly support generative exploration and performance-driven optimization, they largely rely on static models trained on aggregated data, thereby producing “average-user” responses that fail to capture pronounced inter-individual variation in architectural preferences. This conceptual framework paper, developed through critical narrative synthesis of interdisciplinary literature, argues that meta-learning—i.e., learning-to-learn—offers a conceptually appropriate mechanism to address this personalization gap by enabling rapid adaptation to a new user’s preference structure from limited interactions, while leveraging transferable knowledge learned across many users. Drawing on a structured, PRISMA-informed literature identification process complemented by purposive theoretical sampling across user-centered design traditions in architecture, computational preference-elicitation methods, and contemporary meta-learning research, the paper develops a theoretically grounded conceptual framework for adaptive user preference modeling in early-stage design workflows. The framework articulates four interdependent constructs—(1) Preference Representation, (2) Adaptation Engine, (3) Design Space Navigator, and (4) Feedback Loop—describing how iterative preference refinement can co-evolve with design-space exploration without displacing architectural agency. An illustrative application scenario is also presented to demonstrate the operational logic of the framework in a realistic early-stage design context. The paper further formulates a set of testable propositions and evaluation pathways to guide future empirical investigation, alongside a discussion of implications for practice and education and key ethical considerations (bias, privacy, and digital equity). The proposed framework provides conceptual scaffolding for developing AI-augmented, user-responsive design systems that are aligned with the epistemic conditions of early-stage architectural design.
Design studio education requires sustained attention and prolonged occupancy of a shared workspace, making environmental opportunities for brief recovery potentially relevant to students’ well-being. This exploratory study used affordance theory as an interpretive lens to examine the environmental modifications students proposed from their assigned desk positions and the extent to which sketch content was associated with academic year, studio location, and desk-level window view access. The dataset comprised 71 structured sketches, geometric view metrics for 85 workstations that were linked to the 71 sketch participants for inferential analyses, and a nonmatched lighting survey administered to the same cohorts one year later (n = 57). Sketches were coded into 17 modification categories. Water and Collaborative/Social Space were retained descriptively but excluded from inferential interpretation because of quasi-complete separation. Fifteen ordinary logistic regression models were evaluated with Benjamini–Hochberg false-discovery-rate correction, together with a complementary specification omitting studio location. Plants (73.2%), natural shapes/patterns (52.1%), and electric light quality (52.1%) were the most frequent modifications. In the primary models, Technology (q = 0.033) and Plants (q = 0.047) retained FDR-supported omnibus fit; only the academic-year coefficient for Technology retained FDR support (OR = 0.17, 95% CI [0.06, 0.50], q = 0.021). The study identifies environmental preferences and hypotheses for future intervention in restorative learning environments research.
This essay complicates the distinction between of “North” and “South” as spaces of knowledge production—which usually entails the privileging of the South as an emancipatory space—by directing attention to Southern actors’ imbrication with forms of colonialism. It calls for situating both Northern and Southern actors within networks of global knowledge exchanges by critically examining their positionality vis-à-vis colonial relations domestically and internationally. More specifically, it asks how interstitial colonial positions gave rise to new centers of knowledge production and expertise in the postcolonial world. It considers these positions not as static identities but as strategic, adaptative, dynamic, relational, and contingent upon geopolitically determined itineraries of global exchange.
Imperial and colonial history has mostly been founded on the tradition of writing biographies of great men, and more rarely, great women. These lean inherently towards the aggrandizement or hagiography of individuals who, particularly in the early decades of life, may deserve no such attention. Yet for postcolonial and decolonial progression, the unattractive necessity of revising the lives of such influential individuals remains. We cannot now change or eliminate the archive’s overwhelming propensity to amplify (and thereby value and embolden) elite voices and experiences, but we can turn down the volume by placing key episodes firmly within an individual’s relevant or entire life experience, by reading the other less explicit motives for travel or collecting and by focusing on silent absences rather than noisy presences. Sara E. Johnson’s 2023 book ‘Encyclopédie Noire: The making of Moreau de Saint-Méry’s intellectual world’, is presented as a ‘communal biography’ of one such great imperialist, by intentionally, and sometimes creatively, adding in the actors, voices and narratives missing from the sources and archives of European colonial history. In trying to methodologically undermine how imperial biography has traditionally sidestepped complicity or guilt, Johnson attempted to paint a more complete picture of the societies, enslaved or not, in which such elite men operated. Landscape history and architectural history play important roles in such essential revisionism because they can add provocatively spatial dimensions to colonial lives and experiences. As people are profoundly affected by the environment(s) in which they operate, particularly at key tipping points in their lives, spatial and environmental analysis can undermine traditional biography by focusing on where key life decisions were made, leading to a broader cognizance of why they were made. An individual’s spatial position, whether resident or absentee, at home or abroad, with family or without, reveals nuances in mentality that traditional analysis can miss. Taking the life and letters of Pierce Butler, Irishman, US Senator, signatory of the US constitution and the owner of a substantial estate of land and enslaved people in Georgia, as a case study, this article argues for the creative reimagining of biography as a fundamental postcolonial corrective to colonial and imperial history. Butler’s transnational identity, sometimes Irish, sometimes not, collapses any neat mapping of a grand national narrative onto one man’s life. The extraordinary level of detail provided by the correspondence also demands a more conventional or traditional history, one focused on individual identity, motive and relationships, that cannot be effectively discounted because of a landscape or architectural focus.
Al-Wehdat open market, originating in a mid-20th-century Palestinian refugee camp in Amman, Jordan, has evolved into a vital urban common and a paradigmatic case of Everyday Architecture of Compromise. It demonstrates significant economic, social, political, and cultural dynamism, leveraging the relational and solidary capacities of a disenfranchised migrant community to build resilience and assert their Right to the (negated) City. This paper examines how the market’s mode of production responds to intersecting geopolitical, economic, and democratic crises. Employing a constructivist, conjunctural urbanism approach and scene-based analysis, we situate Al-Wehdat market within discourses on urban commons and relationality. Our theoretical framework draws on Hannah Arendt, Gilbert Simondon, and Ash Amin to reconceptualise the Right to the City as the Right to the Open Urban Market. We foreground customary territorial communing as a counterforce to corporative commodification, as essential in the struggle for urban justice, differential individuation, and immanent re-enchantment. Findings, presented through vivid market scenes, show how everyday interactions, creative material arrangements, and rich collaborative imagination sustain these commons. Thematic analysis identifies patterns in community relations, materiality, infrastructure, and acts of repair that sustain the regenerative capacity of key everyday relational, political, techno-material and convivial practices. We conclude by advocating for community empowerment policies that recognise the centrality of everyday relational individuation in shaping inclusive cities amidst polycrisis in the Global South.
Generative AI has reached the early, ideational phase of architectural design, the stage most tightly bound to conceptual creativity, yet its effect on student creativity remains unevenly investigated. This study examines the transfer of creativity from handmade concept to AI refinement. In a first-year studio, 45 students developed a bus-stop design and then reworked it using AI visualisation tools. Pre-AI and post-AI designs were rated by experts using the same nine-dimensional Consensual Assessment Technique (CAT) rubric; the prompt log was text-mined; and the two streams were linked for each student and analysed. Results suggest a modest rise in total creativity (3.38 to 3.71; Wilcoxon p = 0.022, dz = 0.38), yet concentrated in appropriateness; functional adequacy (+0.80), structural feasibility (+0.78), and environmental response (+0.56) increased significantly, while novelty dimensions remained unaltered. The cohort suggested a reordering: weaker starters gained most and several strong starters declined. Although baseline input creativity dominated the prediction of output quality and prompt behaviour added no significant variance once it was controlled, gains were largest when students let AI transform their original concepts. Results indicate that in the context of this study, generative AI acts as a leveller and redirector of creativity, strengthening the buildability of weaker designs without raising originality, with direct implications for how studios deploy and teach the tool. As results are based on a single first-year cohort, institution, design brief, and an observational within-student design, the findings are limited to exploratory evidence of conditional creativity transfer rather than causal evidence.
The early design courses engage and hone students’ visual, spatial, and communicative skills so that first-year design students begin to understand composition, abstraction, hierarchy, development of process, and representation through experimental, process-driven exercises. Exhibitions have traditionally presented the students’ final work; however, virtual exhibitions allow one to push past the physical studio and present student work as a sustained pedagogical experience. A case study was presented of the development and curation of a speculative gallery-style virtual exhibition for process work by first-year students undertaking Basic Design and a Design Communication course. Rather than falling into the pitfall of functioning as a “digital stand-in for the gallery” approaches were considered where virtual curation becomes an educative space for being literate in the visual, mindful learning, and observer witnessing peer students enculturating themselves into identity. Using a practice-based reflective approach, to examine curatorial decisions (visual sequencing, categorisation, representation, and navigational design), exploring how exhibition design frames beginner work and communicates thinking and process rather than simply “polished” outcomes. It is argued that virtual exhibition, by allowing for prolonged engagement with works, scaling access, and encouraging a visual dialogue among peers, may extend the foundation of design learning. The study contributes to discourse on design pedagogy, digital curation, and the shifting educational place of exhibitions in foundation-level design education.
Indoor environmental quality (IEQ) strongly influences occupant well-being and teaching conditions in educational buildings. This study proposes the Predicted Probability of Dissatisfaction Index (PPDieq.prof), a probabilistic ordinal learning framework based on the Consistent Rank Logits (CORAL) architecture to estimate university professors’ dissatisfaction while preserving the ordinal structure of subjective perception. The framework integrates operative temperature, CO2 concentration, illuminance, and sound pressure level through the CORAL architecture. A dataset comprising 77 synchronized environmental and subjective observations collected during regular teaching activities was evaluated using a Nested Stratified Group Cross-Validation benchmark. The proposed framework achieved an Accuracy of 0.670±0.122, Balanced Accuracy of 0.715±0.164, Macro-F1 score of 0.618±0.166, and a Quadratic Weighted Cohen’s Kappa of 0.604±0.176. Benchmark comparisons with conventional statistical and machine learning models demonstrated competitive predictive performance while preserving ordinal consistency. The representative CORAL architecture selected during the benchmark was subsequently retrained using the complete dataset for model interpretability analyses. Predictor contribution analysis identified CO2 concentration as the most influential environmental variable (48.2%), followed by operative temperature (24.8%), sound pressure level (14.7%), and illuminance (12.4%). Complementary One-Factor-at-a-Time (OFAT) response analysis and exploratory latent-space visualization further enhanced the interpretation of environmental dissatisfaction, demonstrating the potential of the proposed framework as an interpretable virtual sensing approach for supporting IEQ assessment in educational buildings.
Restorative environments have been widely associated with stress reduction, psychological recovery, and improved well-being; however, evidence regarding cognitive performance remains methodologically fragmented, particularly across sensory modalities and neurophysiological assessment approaches. This systematic review examined the relationship between restorative environments and cognitive performance, with specific attention to sensory modality, cognitive domain, and the neuroscientific and physiological methods used to assess these effects. The review was conducted in accordance with PRISMA 2020. Peer-reviewed studies published in English from 2000 onward were identified through PubMed, Web of Science, Scopus, ScienceDirect, and PsycINFO, with the final search conducted on 31 March 2026. Eligible studies involved healthy human participants exposed to restorative environmental conditions in built, natural, or simulated settings and included at least one objective measure of cognitive performance together with at least one central nervous system or autonomic nervous system measure. Due to substantial methodological heterogeneity, findings were synthesized narratively. Of the 517 records identified, 26 studies met the inclusion criteria: visual (n = 13), auditory (n = 1), thermal (n = 8), olfactory (n = 1), and multisensory (n = 3). Across the 26 included studies, study-level effect directions were predominantly mixed, comprising 13 mixed, 6 positive, 4 neutral, and 3 negative classifications. Visual studies showed the clearest recurring favorable pattern, particularly for attention-related performance and selected working-memory outcomes. Thermal effects were condition-dependent, whereas evidence for auditory, olfactory, and multisensory modalities remained limited and mixed. Overall, the strength and consistency of the findings varied substantially according to sensory modality, exposure design, and assessment method. The evidence base was uneven across sensory modalities and showed considerable heterogeneity in intervention design, exposure characteristics, cognitive tasks, and neurophysiological outcomes. These findings provide a structured, modality-specific map of how restorative environments have been linked with cognitive performance while highlighting the need for more methodologically consistent research, particularly on underexplored non-visual, tactile, and multisensory pathways.
Cultural heritage management today faces the challenge of addressing increasingly complex realities. In this context, international organisations focus on identifying heritage attributes that consider not only physical and artistic values, but also symbolic, social and environmental dimensions, a task that has been implemented in recent years and in which significant progress has been made. The aim of this research is to develop a detailed protocol for identifying heritage attributes, using the Alcázar of Seville, a World Heritage Site, as an example. Based on a consolidated methodology, the aim is to outline the work process by identifying the sequence of tasks from the collection, selection and distribution of information to the formation of the transdisciplinary team, the analysis process and the selection of attributes. The result shows a sequenced process in which a wide range of material is reviewed in depth from various disciplines, allowing the identification of attributes beyond cultural significance. This methodological update involves increasing the size of the transdisciplinary team and taking a more social approach to the management of this heritage. The proposal takes the form of a useful working tool for heritage professionals and public administrations responsible for managing world heritage properties.
The anthropogenic transformation of modern European cities over the past centuries has been characterized by a gradual transition from a natural defensive landscape to a dense modern urban structure. This study aims to reconstruct the historical urban landscape of Sumy (Ukraine) by integrating archival cartographic materials into a digital three-dimensional model to support heritage preservation and post-war urban planning. The proposed methodology combines retrospective source analysis, comparative cartographic assessment, and GIS-based georeferencing. These approaches are used to evaluate the accuracy, scale, and reliability of historical maps. The study analyzed 18 archival maps of the city of Sumy covering the period from the 1670s to 2025. A comparative assessment enabled the selection of 4 representative cartographic sources for reconstructing the historical urban landscape. A GIS-based methodology for georeferencing archival maps was developed and validated in QGIS v.3.44.11. It used the Google Hybrid basemap in the WGS 84/Pseudo-Mercator coordinate reference system (CRS) with identifier EPSG:3857. The methodology employed a first-order affine transformation, a cubic resampling kernel (4 × 4), and 15 stable ground control points (GCPs). This ensured spatial compatibility between historical cartographic materials, contemporary geospatial datasets, and topographic-geodetic reference frameworks. The proposed approach achieved an RMS georeferencing error of 2–9 m, depending on the historical period, the accuracy, and the scale of the original cartographic sources. Furthermore, the methodology enabled the identification of three classes of anthropogenic landscape transformation (minimal, moderate, and critical). As a result, it provided a comprehensive spatio-temporal representation of the historical evolution of the urban landscape. The resulting 3D model provides a reliable geospatial framework for documenting the historical morphology of Sumy and supports future interdisciplinary studies in heritage conservation, urban planning, and post-war reconstruction. The proposed methodology can also be applied to other historical cities where archival cartographic materials constitute the primary source for reconstructing long-term landscape evolution.
Rapid urbanization, automobile dependence, and declining public-space quality have increased interest in how street-level environments influence pedestrian activity and urban vitality. Although prior research has focused on macro-scale urban form and individual walking behavior, fewer studies have examined population-level pedestrian activity and micro-scale streetscape characteristics, particularly in socioeconomically segregated Latin American cities. This study explores the relationship between pedestrian activity and street-level built environment characteristics in middle-income neighborhoods of Santiago. The analysis included 514 street segments across seven neighborhoods using a modified Pedestrian Environment Data Scan (PEDS) audit instrument assessing destinations, street functionality, safety, aesthetics, and urban design qualities. Pedestrian activity was measured through repeated pedestrian counts conducted during two observation periods in 2025. Street segments were categorized into low, medium, and high activity levels, and multinomial logistic regression models were applied. Results showed that several micro-scale streetscape characteristics were significantly associated with pedestrian activity. Tree presence, sidewalk width, landmark visibility, and street-name visibility were consistently linked to higher pedestrian activity across both periods. Building height, enclosure, benches, segment monitoring, and on-street parking were also significant in at least one model. These findings highlight the importance of micro-scale urban design in promoting walkable and socially vibrant urban environments. Overall, greener, more legible, and pedestrian-oriented streets were consistently associated with higher levels of pedestrian activity.
In the wake of the Fifth Industrial Revolution, artificial intelligence (AI) has become a disruptive force in architectural design processes. One of its techniques is text-to-image, which generates visual representations from textual descriptions. This research questions how architects and students organise text-to-image prompts. Unfortunately, AI images have neglected the basic principles of architectural theories. The problem explored here is whether AI-generated images truly reflect architectural theory or replicate styles without deep understanding. This research aims to propose a chart of semantic textual models that employs selective keywords, inspired by the characteristics, ideas, and conceptual statements associated with theories of architecture, to organise text-to-image prompts. The study followed scientific methodology, began with a literature review, and then analysed previous readings that highlighted this gap and proposed solutions. It concluded by determining the components (variables) of the prompt structure. Using three AI platforms, the researcher conducted visual experiments, injecting five theories into the prompts to compare images before and after. The analysis of these images was transparently validated through a rubric-based evaluation distributed to independent evaluators. As a result, the (after) images were improved, expressing the theories’ characteristics and conveying symbolic meanings. The conclusion is that AI architectural images must have a maestro to organise prompts. This maestro is the ‘Theory of Architecture’, which is expected to bridge the gap between AI’s imagination and authentic design principles.
Spatial qualities are central to architectural reasoning; yet, in studio-based education, they often remain implicit rather than structured as a shared analytical framework. This study examines how a multi-scalar taxonomy of spatial qualities can function as a collaborative analytical language in studio-based architectural education. Situated in Ko & scaron;an & cacute;i & cacute;ev venac and Dor & cacute;ol, two historically layered areas of Belgrade's old town, this study integrates expert spatial analysis with a student questionnaire administered across bachelor and master study levels. Empirical testing was conducted to evaluate structural coherence, conceptual differentiation and the distribution of spatial qualities across detail, architectural and urban drawing scales. The findings indicate consistent internal stability, clear differentiation among constructs and statistically significant cross-scale articulation. Form- and composition-related qualities showed high usability, while interpretative constructs were more variable. Master-level students demonstrated greater engagement with cognitive and interpretative constructs, indicating a shift toward more conceptually grounded design reasoning without affecting overall structural coherence. These results suggest that spatial qualities can operate as a level-independent analytical language, supporting inclusive participation, shared interpretation and structured dialogue within the design studio. By positioning spatial qualities as a collaborative pedagogical framework, this study contributes to interdisciplinary communication and more equitable engagement in architectural education.
This article examines the evolution of computational paradigms in architecture through the articulation of a diachronic framework and a comparative analytical matrix. Moving beyond linear narratives centred on technological progress, the study proposes an interpretation of architectural computation as a layered ecology in which distinct regimes—symbolic, representational, informational, generative, and probabilistic— interact simultaneously. Based on a critical review of historical, theoretical, and technical sources, the study comparatively examines five major paradigmatic moments in the development of architectural computation. Instead of proposing these paradigms as discrete or sequential stages, the article interprets them as interdependent computational layers that continue to coexist within contemporary architectural practice. The findings indicate that the transition from rule-based deterministic systems to learning-based systems introduces a fundamental shift in the nature of architectural computation, moving design processes from controlled execution toward probabilistic exploration. In this context, artificial intelligence does not merely extend existing technical capabilities but reconfigures the relationships between designer, tool, and knowledge. The article concludes that contemporary architecture operates within a layered computational ecology in which multiple paradigms overlap and interact. This perspective allows computation to be understood not only as a set of tools but as an epistemological infrastructure that profoundly transforms architectural practice, its processes, and its critical frameworks.
Indoor environmental quality (IEQ) is increasingly recognized as a critical factor in shaping employee well-being, satisfaction, and work performance, particularly in hybrid workplace settings. This mixed-methods study examined how integrated IEQ conditions influence employee experience in a public-sector hybrid workplace through a case study of the WorkHub, a technology-enabled flexible workspace embedded within a large municipal utility. Quantitative data were collected from 93 valid survey responses using the Workplace Environment Satisfaction and Performance Questionnaire (WESP-Q (TM)), and qualitative insights were obtained from a 90-min participatory think tank session with 24 employees. Results showed that WorkHub users reported significantly higher satisfaction across 15 of 18 environmental and spatial dimensions, including layout, thermal comfort, air quality, lighting, furnishings, cleanliness, and overall building experience. They also reported significantly stronger outcomes in collaboration access, work transition, focus support, work efficiency, workspace productivity, pride in work, and job satisfaction. Qualitative findings reinforced these results, highlighting technology integration, daylight, and spatial flexibility as key strengths, while identifying acoustics, thermal discomfort, and limited privacy as persistent challenges. These findings support a systems-oriented, human-centered approach to workplace design, demonstrating that integrated IEQ can enhance employee experience, collaboration, and organizational performance in hybrid public-sector environments.
