ASC 2026: Papers with Abstracts

Abstract. This study examines the perceptions and preparedness of construction faculty in the USA regarding the transition to Online Learning Environments (OLE) in response to exogenous disruptions such as pandemics, natural disasters, and extreme weather events using an online survey method. The survey instrument collected respondent (construction faculty) demographics and perceptions about the current state of OLE implementation should another transition be imposed by exogenous circumstances, like influenza, volcanos, wildfires, and other events. These exogenous circumstances can be happening in one location or worldwide. Descriptive statistics were used to describe demographics and construction courses unsuitable for OLE. A comparison to 2020 data was made to determine changes in OLE implementation post-pandemic, which found laboratory courses, computer labs, and studio-type courses. The current findings highlight specific instructional challenges related to course types. The laboratory type courses continue to be identified as being the most difficult to offer online. Guidance is provided for universities seeking to strengthen faculty resilience and instructional adaptability in the face of future disruptions.

Abstract. The growth of the US construction industry is constrained by persistent labor shortages, an aging workforce, and competition for skilled workers across neighboring regions. These challenges are intensified by misconceptions about construction careers, fluctuating economic conditions, and barriers that limit the entry and retention of new workers. In response, the Oklahoma Workforce Commission adopted a sector-based approach to workforce development that emphasizes collaboration among employers, educators, workforce organizations, and policymakers. This study analyzes data from the Commission’s Construction Sector meeting to identify current initiatives, skill gaps, stakeholder perspectives, and actionable recommendations for strengthening the state’s construction workforce pipeline. Findings reveal that employers view soft skills, such as communication, work ethic, and professionalism, as greater deficits than technical competencies, signaling a need for adjustment within construction education programs. Participants also emphasized the importance of early career exposure, stronger partnerships between industry and academia, and active employer participation in program development. Systemic policy barriers, including low-bid procurement, funding instability, and academic counseling biases, were also identified as impediments to workforce growth. The study concludes that coordinated efforts across education, industry, and policy domains are essential for building a resilient and competitive construction workforce in Oklahoma.

Abstract. Construction educators often come from diverse academic and professional backgrounds, spanning multiple disciplines, which is challenging for institutions (Colleges, Schools, and Departments) to develop a systematic metric to evaluate, promote, and tenure (EPT) construction faculty. This study presents a systematic literature review to identify differences in construction faculty research, teaching, and service activities based on department affiliations, i.e., Architecture, Business, Building Science/Construction Management, or Engineering. Using a modified PRISMA methodology, the review draws from publications in the ASC Conference Proceedings, ASC International Journal of Construction Education and Research (IJCER), ASCE Journal of Construction Engineering and Management (JCEM), ASCE Journal of Professional Issues in Engineering Education and Practice (JPIEEP), ASEE Conference Proceedings, and ASEE Journal of Engineering Education (JEE) databases. To strengthen the dataset, additional ASCE journals were incorporated in a second review phase to increase the number of instances. This research is important as Construction Management is just one faculty type that can overlap with social sciences, business, humanities, and engineering. Engineering-based faculty may have a strong research background, while construction-based faculty may not. Therefore, it is impractical to apply the same evaluation criteria. The need to determine applicable metrics to be used is of utmost importance.

Abstract. This study identifies twenty key elements that can enhance construction management education facilities, based on a Delphi survey conducted with 41 graduating seniors. The findings emphasize the critical importance of technological infrastructure, including sufficient power outlets, docking stations, and large monitors, as well as immersive learning tools such as BIM labs, analog MEP systems, and simulators. These features support experiential, industry-aligned training, fostering greater engagement and practical skills among students. Additionally, the research highlights the significance of social and well-being spaces, like study lounges, coffee bars, and quiet zones, which are essential for promoting student mental health and community building. It underscores the value of participatory design approaches that involve students and stakeholders in tailoring learning environments to meet actual needs. Overall, the integration of technology, hands-on experiential opportunities, and supportive social spaces contributes to enhanced student satisfaction, engagement, and readiness for the construction industry. The study provides actionable insights for faculty and administrators looking to optimize future construction education facilities by balancing innovation, functionality, and community support.

Abstract. The construction industry faces a critical shortage of skilled professionals, making student persistence and on-time graduation within construction management programs a vital concern. The objective of this research was to identify and map critical student characteristics associated with four-year graduation within a university-level construction workforce pathway program. The study employed a quantitative research methodology to analyze fourteen years of institutional research data from n=613 undergraduate student records. Specifically, a transparent and interpretable Artificial Intelligence (AI) Decision Tree model was utilized to analyze this extensive dataset and classify it into the likelihood of graduating, or not, within four years based on factors influencing the students. The results show a significant disparity in students graduating within four years based on certain student characteristics. Similarly, there are other characteristics that make the students less likely to graduate. This second finding, in the authors’ opinion, is the most important as it allows universities to use their limited resources to assist these students in increasing their graduation rate to join the construction industry with their degrees. The intellectual merit of this research lies in its enhanced understanding of students’ characteristics who do not graduate within four years. This study's broader impact is that it provides data-driven, actionable insights for universities to implement targeted interventions, potentially mitigating the critical shortage of skilled construction professionals.

Abstract. Humans need to be well-prepared for the new revolutionary technological era of generative artificial intelligence (AI) tools. Furthermore, humans in general, and students in particular, will rely on these AI tools in their daily activities, and consequently it is crucial to study the effect of these tools on students' competencies. Since the construction industry is critical for the economic growth of the United States, the construction management (CM) educational systems must adapt to integrate AI tools within their curricula and pedagogies to better prepare students for the future. In this study, the objective was to design and conduct a survey to collect perceptions of nine CM faculty members within a single CM undergraduate program to determine the impact of AI on CM students' competencies and skills. Based on the results, it may be concluded that the critical and logical thinking, in addition to communication competencies may be negatively affected. On the other hand, the results showed that the technical and professional competencies might be positively affected. In summary, the results were indicative and conclusive, and hence it is highly recommended to gather more data from CM professionals (educators and practitioners) for validation.

Abstract. This research investigates the integration of digital construction technologies specifically two-dimensional (2D) prints, three dimensional (3D) modeling, and immersive visualization using Virtual Reality (VR) to enhance learning outcomes in construction management education. Traditional pedagogical methods that rely on static 2D drawings often fail to effectively convey the spatial and functional complexities of architectural, structural, and Mechanical, Electrical, and Plumbing (MEP) systems. To address this limitation, the study introduces a multi-phase methodology that guides students from interpreting 2D plans to engaging with dynamic 3D models and immersive environments. Utilizing platforms such as Autodesk Navisworks and Workshop XR, students gain hands-on experience navigating virtual building projects, thereby fostering deeper comprehension, critical thinking, and problem-solving skills. The implementation centers on a selected building project, through which students participate in structured visualization exercises and collaborative activities. Anticipated outcomes include increased student engagement, enhanced interdisciplinary understanding of architectural and MEP systems, and strengthened partnerships with industry stakeholders. This approach bridges the gap between theoretical instruction and practical application, equipping students with the digital literacy and analytical capabilities required to meet the evolving demands of the construction industry.

Abstract. Lean Construction (LC) has been taught in academic and professional settings over the past 30 years. However, it is still not considered a mainstream topic in Construction-related programs. This paper reports on a collaborative initiative where academics are incorporating LC across the construction curriculum offered through their institutions using a structured method in different courses. Specific examples show how different construction courses have used serious games (simulations) to explain and anchor LC concepts into activities students can relate to. Such examples also demonstrate the integration of LC in multiple construction engineering and management courses at SDSU. It is envisioned that by sharing these examples, the construction education community is informed about the different mechanisms associated with embedding LC education as part of mainstream construction degree programs.

Abstract. This pilot study investigates the intersection of learning theories and construction site safety awareness among undergraduate students in a construction management program. A survey, developed through interdisciplinary collaboration between the Departments of Civil Engineering and Construction Management and Child and Adolescent Development, was administered to 22 students enrolled in the construction management program and specifically in a construction site safety-focused laboratory course. In the context of post-pandemic conditions and emerging technologies, the study aims to identify key factors influencing students’ perceptions of effective safety education. Additionally, the survey captured students’ perspectives on the role of digital technologies like mobile phone applications, multiplayer game environments, and Artificial Intelligence (AI) in enhancing construction safety, revealing a divide between optimism and skepticism. Preliminary results suggest that students' achievement goals influenced how they interpret safety training methods and content as future construction professionals. This study lays the foundation for future research on comprehensive, technology-informed safety education strategies in construction and project management programs for a variety of learners.

Abstract. Students entering higher education in 2026 have grown up in an era defined by social media, online learning, and now artificial intelligence (AI)—powerful technologies that have advanced global connections more than in any other time. However, these same advancements may have had certain inadvertent side effects at the personal level, including the erosion of soft skills—the fundamental interpersonal skills that facilitate effective social connections. This paper reports the results of a three-phase futures workshop held at the Royal Institute of Chartered Surveyors (RICS) in London, UK, in the fall of 2025, in which participants were asked to provide their insights about the lack of soft skills in the current generation of CM students and recommendations on how to correct it. Many of the participants in the workshop were optimistic that AI would be different from previous technologies, believing it could be used to support the development of certain soft skills. Other participants disagreed, expressing skepticism that any technology has ever or can ever substitute for authentic human engagement. Key takeaways for CM teachers include basic guidance on how and when to use AI in the classroom and recommendations to explore alternatives to technology-dependent pedagogies.

Abstract. This study examines the outcomes of a faculty externship program at Purdue University’s Bowen School of Construction, emphasizing faculty and curriculum enhancement through an experiential learning framework. Initiated with the encouragement of the department’s Industry Advisory Council, the externship program connects faculty with industry partners each summer to strengthen academia-industry collaboration while translating industry practices into classroom applications. The study employed a qualitative methodology integrating observational research, reflective journals and guided debrief exchanges to document observations and insights. Data was analyzed using content analysis informed by Kolb’s experiential learning framework and the American Council for Construction Education’s student learning outcomes. The findings were synthesized into teaching units focusing on (i) electrical contracting workflows, (ii) digital technologies and project coordination, (iii) innovation and prefabrication (iv) career pathways, and (v) project delivery dynamics within specialty contracting environments. Beyond units’ development, the program deepened faculty understanding of industry methods, technologies, and workforce expectations, thereby enhancing teaching effectiveness and fostering research collaboration. As an ongoing initiative, the next phase will include pre- and post-assessments of the developed units to evaluate their impact on student learning and to refine the externship model for continuous improvement and sustained academia-industry engagement.

Abstract. This study investigates the extent to which undergraduate Construction Management (CM) programs in the United States are becoming more engineering and math intensive over time or less. Using catalogs, flowcharts, and accreditation directories, the authors compiled curriculum data from 130 programs across two accrediting bodies: the American Council for Construction Education (ACCE), and the Accreditation Board for Engineering and Technology (ABET). Non-accredited bodies associated with the Associated Schools of Construction (ASC) were also studied. Each program was examined at two points in time (2015 and 2025) for the highest required level of mathematics and highest required level of engineering coursework. Results indicate a national trend toward higher mathematics rigor, with most CM programs now requiring at least Calculus I, while engineering requirements have increased more modestly, with Statics emerging as the most common addition. Compared to ABET-accredited Construction Engineering programs, ACCE and non-accredited Construction Management programs remain less engineering and math intensive, but the gap is narrowing. These findings highlight the evolving identity of CM curricula and their relationship to engineering standards. These findings may help program administrators make decisions relating to math and engineering curriculum by using national trends as a measure.

Abstract. Despite increased enrollment of women in construction education programs, women remain underrepresented in the construction industry, particularly in field and project management roles. This exploratory qualitative study examines the experiences of women working in field and project management positions within the Mechanical, Electrical, and Plumbing (MEP) construction sector. Semi-structured interviews were conducted with women at different career stages to gain insight into workplace climate, professional expectations, and support structures in MEP construction. Interview data were analyzed using reflexive thematic analysis to identify recurring patterns across participants’ accounts. Three primary themes were identified: (1) women described contributing to improved communication, empathy, and team synthesis within project teams; (2) participants reported relative isolation due to limited female representation, mentorship, and support networks; and (3) women described heightened performance expectations, collectively characterized in this study as the construction superwoman pattern. Participants reported feeling pressure to consistently exceed expectations in order to be perceived as competent, often without corresponding increases in compensation, advancement, or leadership representation. These findings suggest that while women bring valuable interpersonal and leadership strengths to MEP field and project management roles, structural and cultural conditions continue to impose disproportionate burdens on their success and retention.

Abstract. A student’s perceived sense of belonging within a university community is a predictor of higher education degree attainment. As such, an increased understanding of the factors that support sense of belonging among students is important to increasing the number of university graduates in high-demand professions such as construction management. This manuscript focuses on differences in construction and construction education sense of belonging between undergraduate construction students with more than 480 hours (approximately 3 months) of construction industry work experience and undergraduate students with less than 480 hours of construction industry work experience. Overall, students with more than three months of construction work experience reported higher levels of sense of belonging than their less experienced peers. Preliminary results suggest that further research and analysis to understand the correlation between work experience and sense of belonging is warranted.

Abstract. Resilience theory is central to the planning and operation of critical infrastructure, but its concepts are difficult to teach and assess in practice. This study presents an experimental VR-based instructional framework that makes resilience design concrete for metro emergency response. The study details the scenario design, logging scheme, and analysis pipeline. The framework develops a chain from observation indicators to outcome evaluation. Aligned with National Fire Protection Association 130 (NFPA 130) procedures, records a set of task times, operational accuracy, sequence adherence, and critical-error flags in a two-space scenario. These indicators are normalized to fixed criteria, mapped to resilience attributes, and aggregated into capability outcomes. The method is designed for facility and equipment management education and for workforce training. It provides objective grading, transparent feedback, and cohort performance.

Abstract. This study investigates faculty perceptions of the drivers and challenges to HyFlex (HybridFlexible) delivery in post-secondary education. Based on responses from 106 faculty members across several academic schools and credential programs at a polytechnic institute in North America, the study outlines key challenges associated with HyFlex delivery. The results indicate that faculty generally recognize that students value this delivery model for its flexibility and ability to accommodate diverse learning preferences. Respondents ranked academic integrity, effective assessment practices, and accommodating diverse learning needs as the three most significant challenges in HyFlex delivery. In contrast, access to technology and workforce readiness were identified as the least significant challenges. Overall, the findings suggest that successful implementation of HyFlex requires a balanced approach that promotes flexibility while maintaining pedagogical integrity and supporting both faculty and student success in multi-access learning environments.

Abstract. This paper examines the DUET Program at the University of Oklahoma, a student-faculty pedagogical partnership designed to transform teaching and learning in higher education. Inspired by collaborative models from Bryn Mawr and Haverford Colleges, the program challenges traditional hierarchies by positioning students and faculty as equal pedagogical partners. Through qualitative analysis of three case examples, the authors explored how the DUET Program enhances classroom engagement, promotes participation equity, and improves instructional practices. Findings reveal that the iterative partnership process enables sustainable pedagogical innovation through collaborative inquiry and mutual learning. The analysis demonstrates that while student-faculty partnerships offer valuable pathways for pedagogical development, sustaining such initiatives requires ongoing institutional commitment, dedicated resources, and integration with faculty development infrastructures.

Abstract. Blended learning (BL) is the purposeful integration of face-to-face and technology-mediated instruction and has become central to higher education. BL aligns closely with the hands-on, collaborative nature of construction education. While BL is widely recognized for promoting active learning and engagement, most existing research in construction management (CM) education emphasizes student outcomes rather than faculty experience. This research addresses that gap by performing a systematic literature review and synthesizing 35 publications that examine how CM faculty design, perceive, and implement BL. Analysis revealed that faculty primarily use BL to enable active, applied, and team-based learning but face persistent challenges related to time, technological proficiency, and limited instructional design support. Faculty generally report positive perceptions once BL is implemented, though adoption remains inconsistent and often under-supported institutionally. This review contributes to the body of knowledge by centering the faculty perspective and identifying critical gaps in understanding BL’s adoption and sustainability within CM education. Future research should pursue longitudinal, comparative, and faculty-focused studies to develop discipline-specific models for effective blended instruction in construction education.

Abstract. The Mass Timber Interdisciplinary Studio at Cal Poly’s College of Architectural and Environmental Design originated as an innovative approach to bridge the gap between traditional disciplinary silos and the collaborative demands of modern architecture, engineering, and construction (AEC) practice. The studio evolved from the Integrated Project, Design, and Program Management course in Construction Management and was restructured to serve as a college-wide interdisciplinary experience that included Construction Management, Architecture, Landscape Architecture, and Architectural Engineering faculty and students. Together, these disciplines and their roles in the Mass Timber Interdisciplinary Studio simulated professional collaboration and negotiation in a project-based learning environment. This paper discusses the stakeholders, course design, and project-based learning strategies undertaken in the course, offering lessons for AEC professional and academic parties who may be interested in educational partnerships. Through a shared design project, field work, lectures by mass timber construction industry partners, and collaboration skill-building, the Mass Timber Interdisciplinary Studio provided students with an opportunity to learn together about a material that is both traditional and cutting-edge, a regional resource with global implications, and an exemplar of the interdisciplinary knowledge needed to pursue ambitious climate action goals.

Abstract. Current pedagogies in sustainable construction education often emphasize theoretical coverage of numerous topics under the motto “breadth as strength”, a pattern that can reduce student engagement and limit the development of practical competence. Addressing this gap, this study introduces a pedagogical shift that prioritizes student engagement by emphasizing “depth as strength” while still maintaining essential breadth. A teaching framework was developed using the Transformative Sustainability Learning (TSL) model as the foundation and enriched with Kolb’s Experiential Learning Theory and Keller’s ARCS motivational model. TSL integrates the cognitive (head), experiential (hands), and affective (heart) dimensions of learning, and the incorporation of Kolb and ARCS provided a strong pedagogical basis for intentional activity design and sequencing. The framework was applied to teach indoor air quality (IAQ) within a construction management sustainability course, combining traditional instruction with hands-on testing of pollutants from building and household materials, followed by guided discussions and reflective reporting on IAQ impacts and mitigation strategies. Implemented over five semesters, analysis of student reflections showed that most participants found the approach highly effective, describing it as thought-provoking, engaging, and emotionally meaningful. The results suggest that this framework can be adapted to other theory-based courses to enhance student engagement and support deeper learning.

Abstract. The Associated Schools of Construction (ASC) Annual International Conference is a primary venue for advancing construction-focused scholarships. This study updates and extends prior analyses with a descriptive bibliometric assessment of 1,502 ASC papers published from 2007 to 2025. We manually standardized metadata (authors, affiliations, keywords) and analyzed them with Biblioshiny and VOSviewer to examine three dimensions of ASC scholarship: authorship, institutional participation, and thematic trends. Findings show steady growth in annual output with a post-pandemic rebound to record levels; a distributed co-authorship network anchored by recurring contributors across leading programs; and institutional participation that includes both enduring and newly active universities. Keyword mapping highlight’s persistent themes, construction education, BIM, safety, sustainability, alongside recent emphasis on digitalization, immersive learning, and AI-integrated pedagogy. The study provides an updated longitudinal baseline that programs can be used to benchmark productivity, strengthen collaboration, and track evolving priorities in construction education.

Abstract. This study investigates student perceptions of preparation strategies used for the Associated Schools of Construction (ASC) Regions 6 and 7 student competition. A post competition survey was administered to 66 construction management students from a large public university. Students rated 15 preparation strategies using a 5-point Likert scale and selected the three they found most helpful and least helpful. Open-ended responses were also analyzed to identify missing resources and strategies for improving team performance. The highest-rated strategies were reviewing past competitions, completing practice presentations, and mock competitions. These were followed closely by mentorship from repeat team members and industry involvement. Students consistently valued preparation activities that simulated competition deliverables and included structured feedback. The lowest-rated strategies included stress management techniques, site visits, and general team-building activities. Faculty coaching appeared in both most and least helpful categories, indicating variability in implementation. Students recommended forming teams earlier, assigning clear deliverable roles, and increasing access to past materials and scoring criteria. These results provide useful insight for faculty advisors and ASC team members looking to improve preparation models, increase team readiness, and better align efforts with student needs.

Abstract. Early collaboration is fundamental to integrated project delivery, yet undergraduate programs often isolate disciplines and provide limited opportunities for students to practice effective teamwork. This study reports lessons from an Interdisciplinary Mass Timber Studio that brought together students from Construction Management, Architecture, Architectural Engineering, and Landscape Architecture to work collaboratively on a shared conceptual building project. Using a mixed-methods approach - including pre- and post-course surveys and a faculty interview - the researchers examined changes in students’ collaboration behaviors and disciplinary awareness. Findings revealed that students shifted from viewing teamwork as task division and deadline management to engaging in criteria-based decision-making and role ownership. Persistent challenges included uneven participation and misaligned schedules across departments. Faculty reflection underscored both the benefits of interdisciplinary engagement and the logistical and pedagogical challenges of aligning content, time, and expectations across multiple programs. Overall, the studio advanced students’ collaboration from cooperation toward integration and broadened their understanding of project delivery as a reciprocal, multi-stakeholder process. The findings suggest that mass timber’s authentic design and construction constraints, combined with intentional interdisciplinary practice, accelerate collaborative learning and clarify construction management’s early-stage value. Practical insights are offered for educators seeking to implement interdisciplinary, project-based learning in construction education.

Abstract. Professors, Teaching Assistants, and Graders in construction management courses regularly evaluate open-ended project reports, a task requiring substantial time investment and subjective judgment. This study evaluates whether AI-assisted feedback where TAs draft comments using AI, then review and validate them, improves quality compared to traditional TA-only comments. Using quantity takeoff reports (N = 21 traditional, N = 12 AI-assisted), from introductory BIM course feedback was compared on three dimensions: specificity, actionability, and rubric alignment. AI-assisted comments scored higher across all dimensions, with strongest gains in actionability (d = 1.98, p = .09). Notably, these gains concentrated among junior and non-CM students, groups that received sparser feedback in baseline data. A reversal of equity gaps suggests the human-in-the-loop model may democratize feedback quality. We discuss ethical guardrails: human accountability (TAs own all comments), no automated grading, and transparency with students. Findings indicate AI-assisted feedback can enhance construction education assessment while maintaining pedagogical integrity and advancing fairness.

Abstract. The advent of improved computer processing power and internet speed has allowed universities to increase the number of online courses. This capability to deliver classes online became very important during the recent pandemic to protect the well-being of educators and students when the gathering of individuals was restricted to try to slow down the spread of the virus. Although the delivery of online courses allowed the students to progress toward their degrees, concerns about this delivery method existed. Also, as the pandemic was getting under control and the universities were considering moving back to delivering courses in person, the educators also expressed concerns about the face-to-face classes. Thus, the focus of this paper is an approach to describe data collected from the educators regarding their concerns about course delivery methods during the transition to Online Learning during the pandemic. A qualitative research methodology was used for this research, where the data was collected using open-ended questions that allowed educators to fully describe their concerns without pre-established options (aka. Closed-end questions). The information collected was content-rich unstructured qualitative data, processed using text mining and sentiment analysis used in other areas but seldom used in construction education. The analysis using the proposed AI approach indicated equivocally that students are the foremost important consideration of the educators.

Abstract. Through a case study utilizing qualitative data, this paper investigates the challenges of remote construction administration and the communication barriers between the EWB-KSU student chapter, local contractors, and community stakeholders that led to structural non-conformance in a Malawi, Africa two-classroom school building project. The purpose of this study is to evaluate the specific technical failures, such as improper soil compaction, incorrect steel reinforcement placement, and faulty truss splicing, while demonstrating how navigating these setbacks provides essential professional and technical growth for future architecture, engineering, and construction (A/E/C) practitioners. The results of the case study indicate that these setbacks served as a critical source of lessons learned to improve the management of not only future EWB-KSU projects but also any international project in a developing country.

Abstract. This study evaluated a domain-tuned AI chatbot embedded in an asynchronous construction management course to examine whether students perceived it as meaningful learning support in the absence of real-time instructor interaction. Students reported that the chatbot helped them understand course content, clarified complex or multi-step topics, and supported preparation for assignments, quizzes, and exams. They also judged the responses to be relevant to course tasks, specific to their own work rather than generic, and generally accurate; most indicated that they would use the chatbot again. Interview findings contextualized these patterns: students used the chatbot mainly (1) as a study partner to generate practice and review materials and (2) as a cognitive scaffold to restate explanations in simpler or more detailed terms. Students also described checking important responses against instructor materials, which supports a human-in-the-loop model. Overall, this implementation study provides preliminary evidence that students perceived the chatbot as a helpful, course-aligned source of timely support in an asynchronous setting, highlighting design and evaluation considerations for broader adoption and future multi-course assessments.

Abstract. Construction education programs continuously translate fast-changing industry practices into classroom experiences. The Associated General Contractors of America (AGC) Education and Research Foundation created the Robert L. Bowen Industry Residency Initiative to place faculty in short, immersive residencies within AGC member firms. This paper reflects on a ten-week 2025 residency with Structure Tone Southwest in San Antonio, Texas, and what the placement exposed about project work and curriculum alignment. The reflective case study draws on structured observation journals and field notes, de-identified memos from staff conversations, and post-residency curriculum artifacts, including assignment prompts and curriculum maps. Inductive coding separated observed organizational practices from reflective interpretation. Four themes were identified: (1) AI-assisted information triage paired with human validation; (2) communication functioning as a project-control mechanism; (3) mentorship shaping early-career professional identity; and (4) market context (data centers and civic megaprojects) shaping operational decisions. Themes were interpreted using experiential learning and translated into curriculum revisions aligned with American Council for Construction Education (ACCE) student learning outcomes. Student learning impacts were not assessed, so reported outcomes are implementation-focused. The paper closes with recommendations for documenting faculty residencies as scholarship and for collecting assessment evidence across future cohorts.

Abstract. Building Information Modeling (BIM) has transformed the architecture, engineering, and construction (AEC) industry, creating new demands for integrative and experiential learning approaches in higher education. This paper presents an innovative classroom activity — the “Rex Project” — designed to introduce undergraduate construction management students to the historical evolution of design representation, from primitive methods to Building Information Modeling. Using tangible materials such as chalk, paper, Play-Doh, and LEGO, students simulate different eras of design technology, fostering critical reflection on how representative methods shape professional practice. Using project-based learning principles, the activity promotes collaboration, engagement, and conceptual understanding of BIM as an information-rich process rather than a software tool. Quantitative and qualitative results confirm that students grasped the progression of design technologies and their practical implications. The study suggests that experiential, team-based learning enhances conceptual understanding and prepares students for the construction industry's digital transformation.

Abstract. Artificial Intelligence has emerged as a transformative force in construction management, enabling new capabilities in prediction, automation, and data-driven decision-making. Despite these advances, the industry continues to face significant barriers to widespread AI adoption, largely stemming from limited awareness, inconsistent training, and uncertainty regarding AI’s perceived value. This study empirically examines the behavioral and perceptual factors that influence construction professionals’ intention to adopt AI technologies. A structured survey of professionals was administered, incorporating constructs from the Technology Acceptance Model, perceived usefulness, ease of use, attitude, and behavioral intention, augmented by an awareness dimension. A total of 54 complete responses were included in the final analysis. Statistical analyses, including correlation and multiple regression modeling, were conducted to identify key predictors of adoption readiness. The results indicate that perceived usefulness and awareness are the strongest predictors of behavioral intention (p < 0.01), explaining 56% of its variance (R² = 0.564). Attitude exerted a positive but non-significant effect. Correlation results further confirm strong associations between usefulness, attitude, and intention, suggesting that adoption is primarily driven by perceived performance benefits. The findings highlight the need for targeted educational interventions and experiential learning opportunities that strengthen awareness and demonstrate AI’s tangible value in CM practice.

Abstract. Incorporating sustainability concepts early and progressively in the civil engineering undergraduate curriculum is crucial to preparing students for the complex infrastructure challenges the modern construction industry faces. Early sustainability-focused interventions in the curriculum can facilitate the dissemination of more advanced sustainability concepts in later courses, thereby improving overall student outcomes. This study investigates the impact of sustainability-focused interventions on students’ familiarity, confidence, and intention to apply sustainability principles in practice in a first-year civil engineering technology course at a private higher education institution. Guided by the Engineering for One Planet Framework, the course integrated sustainability concepts into course content, activities, and assessments. Pre- and post-course survey responses were analyzed using the Wilcoxon signed-rank test to assess changes in selected variables following the intervention. Among the variables analyzed, students showed the greatest overall improvement in understanding the economic sustainability dimension. There was a 16% improvement in students’ confidence in applying sustainability in practice, although their perceived likelihood of future application remained steady. This study contributes to the development of evidence-based strategies to introduce sustainability into civil engineering courses, thereby preparing a future workforce capable of delivering sustainable solutions in the built environment.

Abstract. Over the past few years, Augmented Reality (AR) has garnered increasing attention in Science, Technology, Engineering, and Mathematics (STEM) education for its potential to enhance visualization, engagement, and experiential learning. By transforming abstract STEM concepts into tangible, interactive experiences, AR can foster deeper conceptual understanding and skill acquisition among students. However, to capitalize on these potential student perceptions of AR and its use in education, its use in education must be understood. Therefore, this research objective is to evaluate high school students' perceptions of AR use in STEM education. The study followed a quantitative methodology. The data was collected annually through online surveys administered via Qualtrics over the past three years and analyzed using chi-square. The study population consisted of high school students who participated in STEM summer camps. The survey assessed students' perceived challenges/difficulties and interest in extended use of AR technologies. The intellectual merit of this study lies in its exploration of how students’ exposure to and acceptance of AR evolve over time and across multiple cohorts. By exploring students’ change in perceptions, this study helps us understand how students accept new/novel technology within the realms of education. The broader impact of the research relates to how high school students perceive technology, with particular attention to ease of use and motivation levels.

Abstract. This study examines construction students’ perceptions, familiarity, and interest in participating in major national competitions as experiential learning platforms. In this paper, questionnaire survey data collected from 213 construction students indicate that most participants have limited prior exposure to competitions but view them as valuable for enhancing knowledge, teamwork, and professional networks. Descriptive analysis revealed that while general awareness and past experience are low, students widely recognize competitions as useful learning and engagement opportunities. Correlation analyses found no significant relationship between students’ GPA or work experience and interest in competitions, suggesting that academic achievement and professional background do not influence motivation to participate. However, students’ perception of competition usefulness showed a significant positive relationship with their interest in the two main construction student competitions. Furthermore, the two competitions were strongly correlated, suggesting they appeal to similar student groups. Qualitative responses supported these findings, emphasizing construction knowledge, industry connections, teamwork, and leadership as key benefits. The results highlight that awareness and perceived value, rather than academic or experiential factors, are the strongest motivators for participation, underscoring the critical role of educators in promoting, integrating, and demonstrating the educational and professional relevance of construction student competitions.

Abstract. In developing an academic curriculum, a range of methods for identifying the knowledge and skills of graduates are used. Several approaches rely on the subjective perception of future employers using panels, focus groups, or surveys. However, a more objective method involves the analysis of entry-level job postings. An analysis of 125 entry-level job postings obtained from 58 companies recruiting from a large construction management program in the southeast USA was conducted. Results from a textual analysis of position announcements identified lists of job duties. A total of 1689 job duties were analyzed using qualitative data analysis to identify duties that included Bloom’s action verbs at the “create” level. The most frequently used were prepare, develop, create, and plan. The most frequently used phenomena that entry-level graduates are expected to create are reports, schedules, costs, logs, estimates, change orders, and meeting minutes. The results provide helpful information for identifying the knowledge and skills construction management graduates need upon graduation.

Abstract. Educational Escape Rooms (EERs) are content-specific, cooperative, team-based learning activities designed to be completed within a defined timeframe. They can be complex or simple and can be created using readily available tools such as Google Forms. EER pedagogy blends the thrill of problem solving against a clock with the complexities of teamwork and skill acquisition. Typically driven by an engaging narrative and situational relevance, EERs are well suited to delivering educational content in a coherent theme that is motivating, scalable, and equitable. This mixed-methods study was born from the researchers’ concern that post-pandemic, students were disconnected with each other, the instructor, and the content, and sought methods to integrate social engagement with academic learning. The study includes results from the implementation of EERs in construction management and liberal studies courses taught by two different instructors. Forty-six students completed a paired pre and post-survey regarding their learning experiences with this pedagogy and interviews with eight student volunteers were conducted to add depth to the survey data. Exploratory findings indicate that participating in well-designed EERs both enhances academic engagement and deepens inter-student and professor relationships and indicates that the design of EERs may be the most critical aspect of this developing pedagogy.

Abstract. The Highway Construction Workforce Partnership (HCWP) was launched in 2023 through collaboration between the Texas Department of Transportation (TxDOT), the Texas A&M Transportation Institute (TTI), Blinn College District, and the Texas Asphalt Pavement Association (TXAPA). Designed to address skilled labor shortages in Texas’s heavy highway industry, the program provided short-term training and certification to low-income and non-college-bound participants, funded through partner scholarships. Despite early success and strong industry support from firms such as Knife River and Big Creek Construction, the program faced declining employment outcomes with only about 20 percent of graduates securing long-term positions in the industry. This post-mortem analysis examines the program’s structure, cohort data, recruitment challenges, and industry engagement to understand barriers to workforce entry and retention. Findings reveal that cultural mismatches, limited job availability, and inconsistent employer participation hindered program success. Lessons learned provide actionable recommendations for future workforce initiatives seeking to align training design, participant selection, and employer demand in the heavy civil sector.

Abstract. Construction estimating courses play a vital role in preparing students for professional practice in the construction industry. However, students often face challenges when learning bridge estimating concepts due to the complexity of structural elements and limited opportunities for field exposure. This study evaluates the effectiveness of integrating a 3D bridge model as an instructional tool in a construction estimating course for undergraduate students at Washington State University (WSU). The objective is to assess how a 3D model enhances students’ understanding across four key dimensions: visualization and structural comprehension, conceptual learning, efficiency and productivity, and overall satisfaction. Survey data (45 responses) collected from WSU students between 2020 and 2023 through paper-based surveys distributed in class. The results reveal overwhelmingly positive perceptions of the 3D model’s usefulness; 69 percent of students were satisfied, and 31 percent were very satisfied. Students particularly valued the model’s ability to support visualization of complex bridge elements. Overall, the findings suggest that 3D modeling is a valuable instructional tool for enhancing student engagement and perceived understanding in construction estimating education. Future studies should involve multiple universities, diverse project types, and more advanced analytical methods to strengthen the robustness and generalizability of the findings.

Abstract. Science, Technology, Engineering, and Mathematics (STEM) education is critical as it equips students with the skills needed to succeed in a rapidly evolving, technology-driven workforce. Central to this effort are K-12 educators, who play a pivotal role by translating complex STEM concepts into engaging, accessible learning experiences that inspire curiosity and critical thinking among students. The K-12 educators' ability to connect STEM content to real-world applications is essential for preparing them to thrive in future academic and career pathways. Therefore, the objective of this study is to examine the instructional value and quality of various STEM engagement activities designed for K–12 educators as a part of a one-week workshop. Through structured feedback from participants (K-12 educators), the study evaluated multiple hands-on and experiential learning activities across two key dimensions: Instructional Value (IV) and Instructional Quality (IQ). Data were collected using a standardized online evaluation instrument, enabling comparative analysis of educator perspectives across twelve distinct STEM activities. Findings indicate that activities were well received, perhaps because they were directly linked to real-world STEM careers, such as job shadowing and site visits. Additionally, K-12 educators who participated in the study rated the activities that emphasized teamwork and problem-solving very highly.

Abstract. Effective communication in the Architectural, Engineering, and Construction (AEC) domain relies on both verbal and nonverbal modalities to convey complex spatial information and support collaborative tasks. While virtual collaborative learning environments create new opportunities for online and hybrid AEC education, they often rely on avatars and provide limited support for embodied cues, such as natural hand gestures and facial expressions, that are central to face-to-face collaboration. This study explores AEC students’ attitudes toward gesture and facial expression perception and examines their learning experiences in a gesture- and facial-expression–enabled virtual collaborative environment. A pilot study was conducted using FrameVR, a web-based virtual platform in which students collaboratively completed an HVAC air duct installation task while communicating through voice, text chat, and real-time webcam-based visualization of gestures and facial expressions. Post-activity surveys measured gesture perception, self-efficacy and motivation, and system usability. In addition, recorded session videos were reviewed to provide exploratory qualitative insights into students’ use of facial expressions during collaboration. Results indicate positive student attitudes toward gesture- and facial-expression–supported communication and suggest that the platform effectively supported collaborative learning. These findings highlight the potential of integrating embodied cues to enhance social presence and engagement in virtual AEC learning environments.

Abstract. Mixed Reality Learning Environments (MRLEs) are increasingly used in construction education to provide hands-on experiences that enhance engagement and skill development. However, their influence on learners’ anxiety remains underexplored. While moderate levels can enhance engagement, excessive strain or tension may hinder performance. This study investigates how anxiety influences learning in an MRLE designed to teach sensing technologies on a virtual construction site. Twenty-two construction engineering and management students participated, completing pre- and post-knowledge tests and the State-Trait Anxiety Inventory to assess anxiety levels across different MRLE scenes. Data were analyzed using descriptive statistics, Friedman, and Wilcoxon signed-rank tests. Results showed that participants initially exhibited low anxiety levels and positive anxiety states before interacting with the MRLE. Although anxiety states like tension, dizziness, strain, and nervousness increased during MRLE, the MRLE experience did not lead to overwhelming negative anxiety responses. Also, MRLE participation improved knowledge of sensing technologies. The study highlights the importance of integrating affective design considerations in MRLE development to balance cognitive and anxiety-related demands and optimize learning outcomes in construction education.

Abstract. Grit, mettle, drive and work ethic are essential skills for success in the professional workplace, but not all new graduates have these skills. This paper highlights results from a qualitative research study about work ethic in the construction industry. Both student and employer perspectives are shared. Strategies about how to teach work ethic in academic curricula at higher education institutions are also discussed.

Abstract. Traditional structural design education often struggles to engage students in applying abstract engineering concepts to practical problem-solving contexts. This study presents a proof of concept of a gamified learning tool for timber beam design, integrating constructivist principles and structural design standards into an interactive educational experience. The tool incorporates seven core gamification elements, problem-solving, goal clarity, adaptive challenges, user control, feedback, uncertainty, and sensory design, to enhance engagement and learning outcomes. The present work focuses on the design rationale, implementation, and formative evaluation of the prototype rather than on summative measurement of learning gains. Preliminary user feedback and expert review indicate that the tool is computationally robust, pedagogically aligned, and perceived as useful for practicing structural design procedures. As proof of concept, this study demonstrates the feasibility of embedding constructivist game mechanics within technically rigorous structural engineering workflows and establishes a foundation for ongoing research involving large-scale classroom deployment and controlled assessment of learning outcomes.

Abstract. This study examines the effectiveness of Construction Engineering programs in preparing students to obtain Professional Engineering (PE) Licensure. While ABET-accredited programs are required to demonstrate compliance with established student outcomes, they are not always aligned with the technical content emphasized in the Fundamentals of Engineering (FE) and Principles and Practice of Engineering (PE) Exams. Using public curriculum data from the 24 U.S. ABET-accredited Construction Engineering Bachelor's Degrees, this study examines the required coursework and the topic areas specified for the relevant FE and PE examinations. The analysis highlights discrepancies between required coursework and exam coverage. National data on FE and PE participation and licensure are also reviewed to highlight the importance of these findings. The results suggest that while Construction Engineering programs provide students with adequate engineering problem-solving and managerial skills, additional emphasis on FE/PE-aligned fundamentals could strengthen professional licensure readiness and career success among Construction Engineering graduates.

Abstract. As the construction industry becomes increasingly aware of the environmental of building activities and material consumption throughout the project lifecycle, efforts to integrate sustainable practices have intensified. From remotely controlled drones surveying sites to large-scale 3D printers fabricating wall and slab modules, and robotic arms for precise assembly, the industry is cutting significantly on material waste and embodied energy. Yet, there are challenges to the adoption of these technologies, such as zoning regulations, insurance policies, and the continued need for codified professional expertise in programming and mechanics. Because the industry remains one of the world's largest emitters of greenhouse gases, the durability of low-carbon materials, smart design software, and modular optimization of energy consumption are just as much a product of smart design as disciplinary legislation. Inscribing such devices is only achievable with ongoing advocacy by policy makers, private organizations, and a continuous supply of expertise. Starting all projects with a circular metrics mindset is the strongest top-line revenue stream and most uniform climate plan in the same blueprints.

Abstract. The Midwest is experiencing a rapid surge in hyperscale data-center development, largely driven by the growing computational demands of artificial intelligence (AI) workloads. Centering on Indiana while incorporating regional comparisons, this study compiles a verified public dataset of active and announced projects, models their annual electricity consumption across load-factor scenarios, and estimates direct on-site water requirements under alternative Water Usage Effectiveness (WUE) assumptions. Results reveal that a single multi-gigawatt campus can contribute tens of terawatt-hours (TWh) of additional annual electricity demand, while water impacts depend heavily on the choice of cooling technology, ranging from evaporative to dry or hybrid systems. Even when direct on-site water use is minimized, the indirect water footprint embedded in electricity generation remains significant, highlighting the urgent need for integrated energy-water nexus accounting within utility Integrated Resource Plans (IRPs), municipal infrastructure planning, and corporate sustainability reporting. Recent studies converge on projections of exponential load growth from AI operations: global data-center electricity use, estimated at approximately 415 TWh in 2024, is expected to nearly double to 900-1,000 TWh by 2030, with AI emerging as the dominant driver (Takci, 2025). Although many hyperscale operators are adopting dry or hybrid cooling systems that nearly eliminate direct water withdrawals, the indirect consumption associated with thermally based electricity generation continues to pose major sustainability challenges, particularly within grids characterized by high fossil or nuclear generation shares. These findings reinforce the need to couple WUE disclosure with transparent reporting of grid composition and to accelerate the transition toward 24×7 clean-energy procurement strategies.

Abstract. The construction industry significantly contributes to material waste and greenhouse gas emissions, making sustainability essential. Artificial intelligence (AI), especially Generative AI (GenAI), offers new opportunities to improve efficiency and reduce waste in the Architecture, Engineering, and Construction (AEC) sector. This study conducts a systematic literature review (SLR) of GenAI applications in construction waste management from 2020–2025. Using PRISMA 2020 guidelines, 29 peer-reviewed studies from databases such as Web of Science, Scopus, Engineering Village, and Google Scholar were analysed. Results show GenAI is advancing in design optimization to prevent waste, robotic sorting of demolition debris, and lean construction workflows. Key benefits include enhanced design accuracy, real-time decision support, and material reuse. However, challenges like data scarcity, computational costs, model hallucination, and lack of regulations persist. The study proposes future research on hybrid AI-human collaboration, model validation, and natural language interfaces for efficient waste management.

Abstract. Bayesian calibration has been increasingly used for improving the accuracy of building energy models, but its performance strongly depends on the selection of prior distributions. Large language models (LLMs) provide a new potential way to generate prior distributions by extracting domain knowledge. However, prompt design during LLM execution is critical to the reliability of priors generated by LLMs. The quality and structure of prompts determine how LLMs interpret domain knowledge and translate it into priors, which in turn could influence both prior characteristics and calibration performance. This study investigates how different prompt designs affect the statistical characteristics of LLM-generated priors in building energy simulation calibration. Using three years of monthly electricity data from a campus building, three levels of prompt information (low, medium, and high) were applied to generate priors for four typical parameters. In this study, results show that prompts with lower information levels produced more balanced priors, leading to faster convergence and higher calibration accuracy. These findings suggest that prompt design should balance informativeness and generality to achieve effective LLM-assisted Bayesian calibration, providing a new perspective for integrating LLMs into building energy simulation and modeling.

Abstract. Green Infrastructure (GI) is increasingly adopted in urban environments as a sustainable stormwater management strategy to reduce flooding risk, enhance resilience, and improve ecological performance. However, the continued adoption of GI also depends on public awareness, recognition, and engagement, particularly in shared community environments such as university campuses. Universities are uniquely positioned to adopt and advance GI technologies. Therefore, this ongoing study assessed levels of awareness, spatial knowledge, interaction, and perception with GI features among students at a large public research university in the southern US using a three-phase online survey. Complete survey responses from 85 participants (undergraduate and graduate students) were analyzed to evaluate familiarity with GI, recognition of three existing campus GI installations (an above-ground cistern, a bioswale, and a sand filtration basin), and interest in learning more about GI functions. Preliminary results indicate that while many respondents spend substantial time on the campus, GI features remain largely under-recognized, particularly lower-visibility systems. However, a strong interest in learning more suggests that awareness barriers are informational rather than attitudinal. The findings highlight opportunities to enhance campus flood resilience and sustainability literacy by improving GI visibility, adding interpretive signage, integrating curricula, and implementing campus engagement strategies.

Abstract. The electrical industry plays a central role in advancing global sustainability, yet its Environmental, Social, and Governance (ESG) practices remain unevenly developed across the supply chain. This study examines ESG adoption within the U.S. electrical construction industry through a cross-sectional qualitative analysis, using manual coding, of 19 corporate ESG and sustainability reports, 10 from major electrical suppliers and 9 from top electrical contractors. Using a qualitative content analysis approach, 400 discrete ESG actions were identified and categorized into 24 sustainability themes adapted from prior ESG literature. Results reveal that suppliers exhibit greater reporting maturity, emphasizing emissions reduction, renewable energy investment, and policy-driven environmental management, while contractors focus primarily on workforce safety, inclusion, and project-based sustainability implementation. Despite differing motivations, both groups share common priorities such as emission reduction goals, safety training, and governance transparency. These findings highlight contrasting ESG reporting approaches between suppliers and contractors. Suppliers generally institutionalize sustainability through formalized, metric-based actions, while contractors emphasize project-embedded and workforce-centered practices. Bridging these approaches through clearer reporting guidance and capacity building will help lead to cohesive, industry-wide sustainability integration.

Abstract. This study evaluates the relationship between credit-category importance and achieved performance in LEED v4 New Construction (NC) certified projects using a comprehensive Importance–Performance Analysis (IPA). A dataset of 1,344 certified projects was analyzed to assess how major LEED credit categories align with their relative weighting and market-level achievement. The results reveal that Location & Transportation (LT), Energy & Atmosphere (EA), and Indoor Environmental Quality (EQ) are positioned in the “Concentrate Here” quadrant, indicating high importance but below-average performance. Sustainable Sites (SS), Water Efficiency (WE), and Materials & Resources (MR) were classified as low importance and low performance, while Innovation (IN) and Regional Priority (RP) achieved above-average performance despite lower importance. A robustness test comparing mean- and median-based thresholds confirmed the stability of the quadrant assignments, with only EA shifting to “Keep Up the Good Work”. These findings identify key opportunities to improve strategic performance in the most influential LEED categories. The study contributes a robust, data-driven framework for assessing market-level certification dynamics and demonstrates the analytical reliability of IPA as a diagnostic tool for green-building evaluation. The results provide actionable insights for optimizing resource allocation and advancing performance-driven sustainability practices in the construction industry.

Abstract. Transitioning the construction industry towards circular economy (CE) requires reliable and interoperable material information systems. Despite growing attention to CE, existing research remains centered on waste management, resulting in fragmented and reactive practices. This paper presents a systematic literature review on the integration of material inventories and CE to promote proactive, data-driven circularity practices in construction. Following PRISMA guidelines, 28 studies were reviewed and included in the final analysis. The paper aims to synthesize existing research on material inventories and CE in construction, explore CE strategies enabled by material inventories, identify the data types used in material inventories, and highlight research gaps and future directions. Findings reveal that material inventories act as key enablers across four CE strategies material reuse, recycling, deconstruction planning, and circularity in design by providing structured information to identify and evaluate materials for recovery and reuse. However, current practices remain largely relying on textual data from audits and reports. This study contributes to the body of knowledge by systematically mapping how material inventories facilitate circularity across different strategies and linking diverse material data types with emerging technologies, while offering practical guidance on improving material data management to support a more sustainable and circular built environment.

Abstract. With all the efforts in placed to implement sustainability actions in construction industry, still huge hindrances are in the way in the form of Lack of Knowledge, Reluctant Behaviours and Economic Issues. Considering these important issues, this research is initiated to investigate the role of project management approaches towards sustainable practices adoption in the construction organisations, while tackling matters related to sustainability hindrances. The quantitative survey data was collected from the 205 construction professionals in the UK. Whereas the qualitative data was collected from the seven industry experts. To understand the statistical inferences of the data Bivariate Correlation and Hierarchical Multiple Regression (HMR) analysis are used for the survey data. Whereas the panel data was analysed through Interpretive Structural Modeling (ISM). The findings revealed that the project management approaches are significantly affecting the sustainable construction practices adoptions. It is reported that the moderating effects of knowledge gaps, economic issues and personal resistance are not significant consequences to the UK construction organizations when the project management approaches are involved. These findings were validated by Interpretive Structural Modeling (ISM). Thus, effective usage of the project management system can lead to a better understanding of the sustainability adoption in the construction industry.

Abstract. To evaluate the influence of calcium carbide residue (CCR) as a partial slag replacement in geopolymer mortar, binary mixes containing 0–20% CCR were prepared and tested to assess their early-age fresh properties, mechanical performance, microstructural characteristics, and sustainability metrics. Increasing CCR reduced flow (from 133.6 to 83.6 mm) and shortened setting times due to Ca(OH)₂ accelerating gel formation. Compressive strength decreased from 9.94 to 6.97 ksi as reactive aluminosilicates were diluted and partial crystallization occurred. XRD of the 20% mix showed C-S-H and portlandite peaks over the amorphous C-A-S-H hump, while SEM revealed a more porous, heterogeneous matrix consistent with strength loss. Environmental analysis showed embodied carbon decreased from 574.6 to 560.6 kg CO₂ e/m³ and material cost dropped ≈6% at 20% CCR. Despite reduced workability and strength, the mixes maintained acceptable performance and improved sustainability compared to OPC mortars. Our results identified an optimal CCR level that balances strength and sustainability, supporting the development of greener, resource-efficient materials.

Abstract. This paper benchmarks the global adoption of the ISO 59000 family of circular economy (CE) standards in the construction sector. This study develops a Circular Economy Standards Implementation Score (CESIS) that integrates ISO 59004 (principles and actions), ISO 59010 (business models and value networks), ISO 59020 (measurement and performance), ISO 59014 (traceability of secondary materials), and ISO 59040 (product circularity data sheets). Countries are assessed through a combination of policy review and quantitative resource-efficiency indicators, including material footprint (MF), domestic material consumption (DMC), and material productivity. To ensure comparability, CESIS values are normalized against socio-economic and environmental indicators rather than relying solely on Gross Domestic Product (GDP). Results reveal strong regional variation: EU countries score higher on measurement and reporting alignment, while non-EU high-income nations demonstrate mixed outcomes in material productivity and secondary materials traceability. The analysis identifies associations between CESIS and circularity indicators, offering a replicable benchmarking framework for policymakers, contractors, and educators. The study concludes with recommendations for integrating ISO 59020 indicators and ISO 59040 product data into construction project management and procurement practices to accelerate global circular economy transitions.

Abstract. As wildfires grow in frequency and intensity across California, understanding and mitigating residential fire risk has become a public safety priority. Communities in the wildland-urban interface (WUI), such as San Luis Obispo, face heightened exposure due to proximity to natural vegetation and the prevalence of older housing stock. While state and local agencies have introduced regulations and educational campaigns, there remains a need for accessible, scalable tools that help identify vulnerabilities at the individual home level. This project assessed wildfire vulnerability across 135 homes in San Luis Obispo using a visual grading rubric developed from peer-reviewed literature and expert input from a direct interview with Fire Chief Damon Pellegrini. The rubric evaluated ten observable factors, including roof and siding materials, window type, vent and eave protection, defensible space, vegetation contact, and overall property maintenance. Each home received a total score, where higher scores indicate lower wildfire vulnerability, and was categorized as Low, Moderate, High, or Extreme Risk. Results showed clear differences across neighborhoods. Neighborhood 5 had the highest (safest) average score and the fewest High/Extreme-risk homes, while Neighborhood 1 had the lowest average score and the highest concentration of High/Extreme-risk homes. Citywide, over one-third of homes fell into the High or Extreme categories. Common vulnerabilities included wood siding, single-pane windows, and vegetation in direct contact with the structure. These neighborhood-level patterns suggest that observed mitigation features and maintenance vary across San Luis Obispo and may relate to broader neighborhood context, although socioeconomic variables were not directly measured. Overall, the rubric proved effective as a simple, repeatable tool for identifying common structure-level vulnerabilities that can help guide homeowner action and support wildfire preparedness efforts.

Abstract. Building façade condition plays a critical role in shaping how buildings are perceived, maintained, and valued, yet its relationship to rental pricing remains understudied. While real estate firms cite façade improvements as a strategy to attract tenants and increase revenue, little empirical research has tested whether these upgrades impact rents charged. This question is particularly relevant in cities like Milwaukee, where local code requires regular façade inspections for larger buildings and rising rents have intensified affordability concerns. Poorly maintained façades also may contribute to urban decay, decrease surrounding property values, and pose safety risks. To explore whether façade maintenance affects rent, the research team surveyed building owners, property managers, and real estate professionals in Milwaukee. Respondents were asked a series of questions about façade maintenance and rental prices for their buildings. The survey results provide evidence that building owners and property managers perceive an association between façade maintenance and rent-setting decisions. The main contributions of this research are that it provides new evidence on the relationship between façade condition and rent determination, an area not well covered in existing literature, and highlights how the costs of maintaining façades may be passed through to tenants in the form of higher rents.

Abstract. The social vulnerability of the Gulf Coast states—Texas, Louisiana, Mississippi, Alabama, and Florida—is rapidly increasing due to a complex interplay of social, environmental, and economic factors. These include climate change, extreme weather events, sea level rise, land subsidence, social inequalities, aging infrastructure, urbanization, population growth, and economic shifts. This paper aims to assess the social vulnerability of these states through a comprehensive analysis of socio-economic and demographic factors, utilizing the Social Vulnerability Index (SVI) as a framework. Key indicators for the SVI encompass population, age, race, education, housing structure, income, and disability. To evaluate the relative significance of these indicators, the Principal Component Analysis (PCA) method was implemented, and the variables were categorized into distinct groups for a more nuanced assessment of vulnerability. Subsequently, the SVI for each of the five states adjacent to the Gulf of Mexico was calculated, and their vulnerabilities were analyzed and compared. The results will assist decision-makers in effectively planning for both pre-disaster preparedness and post-disaster recovery in these disaster-prone regions.

Abstract. The construction sector is a significant contributor to energy consumption and greenhouse gas emissions. This paper examines green building practices that reduce carbon emissions and enhance sustainability in the construction of South African housing. The study adopts a sequential exploratory, qualitative-dominant mixed-methods research approach, comprising semi-structured interviews and an online questionnaire survey, to obtain practitioner perspectives. The study found that passive and active energy-efficiency measures, renewable energy integration, the use of low-emission carbon and recycled materials, water-sensitive design, and waste minimization are effective in reducing operational and embodied CO2. At the same time, the barriers to implementing energy-efficient measures include perceived and real upfront costs, limited local data on performance and returns, weak policy enforcement, and limited skills and awareness among stakeholders. Based on the findings, the study concludes that policy and industry actions involving regulation, incentives for using energy-efficient technologies, and capacity-building/training initiatives can substantially reduce carbon emissions in housing construction, while delivering social and economic co-benefits in line with the Sustainable Development Goals. The study is exploratory and based on a small, practitioner-focused sample, and therefore generates indicative insights rather than statistically generalizable results.

Abstract. This study explores the activities, benefits, and challenges associated with combined implementation of Lean Construction (Lean) and Building Information Modeling (BIM) at project-level by conducting a traditional literature review using a representative sample of 37 journal articles. Such activities were categorized by project phase, i.e., planning, design, and construction, to understand the nuances of Lean-BIM throughout the project delivery process. Benefits were categorized by the Lean principles such as waste reduction, flow improvement, and value generation. Challenges were categorized by the different aspects of implementation such as cultural, technical, and organizational. The results show that during project planning, Lean-BIM strengthens visualization, scheduling, and constraint identification; during design, enhances collaboration, model-based coordination, and accuracy; during construction, enables reduced rework, efficient resource management, and effective communication between office and site operations. By identifying the key activities, benefits, and challenges associated with Lean-BIM integration, this study contributes to understanding of components that support planning for a Lean-BIM combined implementation.

Abstract. Accurate 3D documentation of built environments is essential for renovation, verification, and coordination tasks in construction. However, terrestrial laser scanning (TLS) remains cost-prohibitive for many small and mid-size construction firms. This study investigates the feasibility of using affordable consumer-grade 360-degree cameras, Insta360 X2 and X4, as alternatives to high-end TLS systems, specifically the FARO Focus S350, for generating point clouds. A comparative analysis was conducted at an active healthcare construction site, where data from all three devices were captured, processed, and exported as E57 files. Point clouds were aligned and analyzed using CloudCompare through cloud-to-cloud (C2C) distance calculations, descriptive statistics, and visual deviation maps. Visual assessments included RGB renderings and framing plan overlays with the original design drawings. Results show that while the FARO scan achieved the highest accuracy and detail, the Insta360 X4 in particular produced point clouds with acceptable levels of deviation, averaging around 6 cm, and preserved key structural elements. The 360-camera workflow also significantly reduced on-site capture time and required no specialized training, making it practical for everyday field use. For general documentation and as-built applications, Insta360 cameras provide a viable low-cost alternative for firms with limited resources. Limitations include the single-site scope and reliance on one photogrammetry platform. Future work should explore broader use cases, additional processing tools, and integration of AI-driven workflows to enhance point cloud usability.

Abstract. Emerging technologies in the construction industry include Digital Twins (DTs), which are dynamic digital replicas of physical systems. While DTs are increasingly used in operations and maintenance, their application in preconstruction remains underutilized despite significant potential benefits such as design validation, risk mitigation, real-time estimating, change management, and sustainability assessments. This review synthesizes findings from peer-reviewed articles published between 2018 and 2025. Studies highlight the importance of early DT implementation, yet empirical evidence and standardized workflows for such integration are limited. Sensor cost modeling and lifecycle optimization are particularly underexplored, with very few frameworks providing economic assessments of DTs. Technological and organizational challenges persist, including data interoperability between BIM and DT systems, latency in sensor feedback loops, lack of standardized data and cybersecurity protocols, and cultural resistance to digital transformation. The review highlights the need for pilot projects to validate data, robust data-delivery systems, interoperability standards, and interdisciplinary collaboration to advance DT implementation in the preconstruction phase. Overall, this review underscores the importance of continued research to enable the adoption of Digital Twin technologies in early project phases.

Abstract. Visual inspection and Red, Green, Blue (RGB) cameras remain the dominant method for assessing surface finish and quality in construction materials. However, this approach is inherently subjective and constrained by human color perception, particularly with visually similar coatings. Similarly, conventional RGB imaging also fails to capture the subtle spectral cues that distinguish surface finishes sharing similar color and texture, leading to potential inaccuracies when verifying completed work. Reliable differentiation of surface coatings is essential for automated progress tracking applications. To address these limitations, this pilot study investigates the use of Hyperspectral Imaging (HSI) for the non-destructive differentiation of coated and uncoated gypsum surfaces under controlled lighting. Experiments were conducted in a laboratory under controlled illumination as a pilot study, using a Kelvin Play LED source. The lighting temperature varied from 6000 K to 8000 K to improve spectral separability. Data was collected as hyperspectral files in JSON format and applied Min-max normalization. Two classifiers, Support Vector Machine (SVM) and Random Forest Classifier (RFC), were trained and evaluated using spectra. The RFC achieved over 95% accuracy in real-time classification under 8000 K illumination. The live system, implemented via the Living Optics SDK (v1.9.0), predicted surface types directly on a grayscale camera feed with OpenCV overlays. The results confirm that hyperspectral sensing, coupled with optimized lighting and machine learning, can enable reliable, real-time differentiation of construction surface materials. The findings establish a strong foundation for extending hyperspectral inspection to mobile robotic platforms for autonomous, on-site progress tracking.

Abstract. Artificial Intelligence (AI) is transforming construction management (CM), driving a demand for new forms of digital leadership and professional expertise. This study explores the skills and attributes construction employers expect from future CM professionals as AI adoption increases. Drawing on semi-structured interviews with 30 professionals from 22 U.S. construction firms, the research identifies three core competency domains: (1) AI-enabled workflow implementation, (2) reflexive learning and ethical reasoning, and (3) domain competence, interpersonal skills, and human-centered integration. Findings reveal that employers view AI literacy and adaptability as critical market differentiators. This signals an urgent need for educational reform and adaptation. The study contributes empirically grounded evidence for aligning CM education and professional development with the demands of an AI-driven industry.

Abstract. The integration of quadrotor technology in construction has enhanced traditional practices by improving efficiency, precision, and safety across surveying, monitoring, and inspection tasks. However, achieving reliable trajectory tracking under real-world environmental and site conditions, such as wind, weather variability, obstacles, and complex terrain, remains a challenge. This paper addresses this gap by developing a Proportional-Derivative (PD) control framework with optimized control parameters aimed at enhancing the efficiency and reliability of quadrotor operations. The effectiveness of the approach is demonstrated through simulation studies, showing accurate trajectory tracking and operational stability. The results highlight that the proposed optimized controller can be deployed on construction sites for surveying and inspection tasks, as it is capable of accurately following desired trajectories with efficiency and stability.

Abstract. Language barriers continue to pose a significant challenge to effective safety communication in the construction industry, particularly for Spanish-speaking workers, who comprise an increasingly large portion of the workforce. This study develops and examines Habla Seguro, a bilingual mobile application designed to improve real-time communication between English-speaking supervisors and Spanish-speaking craft workers. Through usability testing and comparative analysis, the app was evaluated in areas such as navigation, translation accuracy, cultural relevance, and audio clarity. The results indicate that Habla Seguro delivers faster and more precise translations than general-purpose tools, such as Google Translate, while providing context-specific and culturally appropriate safety phrases tailored to construction settings. Overall, the findings suggest that specialized, industry-focused digital tools can significantly improve communication, inclusion, and safety outcomes on multilingual job sites. Future development should focus on expanding trade-specific vocabulary, improving functionality in high-noise environments, and integrating visual aids to support workers with limited literacy skills, further strengthening communication across diverse construction teams.

Abstract. Despite a growing body of research on AI in construction, most studies remain limited in scope, concentrating on specific tools, tasks, or individual project phases. This fragmentation hinders a comprehensive understanding of AI’s role throughout the entire project lifecycle. This study addresses this gap through a systematic literature review of research published between 2010 and 2024, using the PRISMA methodology. A metadata-driven analysis was conducted to facilitate deeper pattern recognition and gain a holistic understanding of AI implementation across lifecycle phases, examined through the lens of AI techniques, functional roles, key business processes supported, and AI tools/models. The findings suggest that AI is increasingly applied in the planning, design, and construction phases, while it remains underrepresented during project conception, closeout, and post-construction phases. Machine Learning (ML) dominates as the underlying AI technique, with optimization as the top functional role and risk management as the key supported business process. This study contributes to the body of knowledge by offering metadata-supported evidence and practical value for both academics and practitioners, highlighting not only what has been achieved so far but also where future efforts should be directed to promote more connected and intelligent project delivery.

Abstract. The construction industry remains one of the most hazardous occupational sectors, with high rates of injuries and fatalities caused by heat stress, fatigue, and unsafe movements. Although wearable technologies have shown promise in improving worker safety, most existing devices store data locally and do not provide real-time access, limiting their usefulness for immediate intervention. This study was initiated to address that limitation through the development of a custom, low-power wearable device capable of streaming multi-sensor data continuously in real time. The prototype integrates a MAX30102 photoplethysmography (PPG) sensor for heart rate and blood oxygen saturation, an MLX90614 infrared temperature sensor for skin temperature, and a six-axis inertial measurement unit (IMU) for motion tracking. These components are embedded on a compact printed circuit board (PCB) centered on an nRF52840 microcontroller with Bluetooth Low Energy (BLE) for efficient data transmission. Firmware was developed to synchronize sensor sampling and structure BLE packets for stable streaming. Preliminary tests confirmed reliable real-time transmission, consistent signal quality, and low power consumption, demonstrating the feasibility of continuous physiological and motion monitoring. The system provides an accessible foundation for proactive, data-driven safety management in construction environments.

Abstract. The construction industry is undergoing a rapid digital transformation through technologies such as Building Information Modeling (BIM), Digital Twins, Artificial Intelligence (AI), robotics, and augmented and virtual reality (AR/VR), and wearable sensors. While these tools have improved coordination, safety, and productivity, their growing use is also creating unintended behavioral consequences. This study examines how increasing reliance on digital systems influences workers’ situational awareness, critical thinking, and sense of accountability in technology-driven construction settings. Survey data from professionals with varying levels of technology exposure reveal early signs of automation bias and cognitive complacency. Respondents showed moderate awareness and critical thinking but lower accountability, suggesting that digital tools may be reducing independent vigilance and ownership of decisions. Scenario-based results further indicated that those with stronger accountability were more likely to verify automated recommendations, whereas others displayed over-trust in system feedback. These findings show that Construction 4.0 tools, if adopted uncritically, can erode essential human skills and weaken professional responsibility, posing risks to safety and decision quality. The study calls for a human-centered digital strategy that restores awareness, reinforces ethical accountability, and ensures automation complements, rather than replaces human judgment in modern construction practice.

Abstract. The balanced cantilever construction method enables efficient erection of prestressed concrete box girder bridges in locations where falsework is impractical; however, maintaining geometric control and achieving accurate closure alignment during construction remain critical challenges due to time-dependent material behavior. This study examines construction stage challenges in balanced cantilever concrete box girder bridges by numerically evaluating time-dependent deformation and its influence on cantilever alignment and closure sensitivity. A step-by-step finite element simulation is employed to model the sequential erection of segments, prestress application, and material aging, incorporating the effects of concrete creep and shrinkage, prestressing steel relaxation, prestress losses, loading age, and construction sequence. The results show that concrete creep governs construction-stage and long-term deflection behavior, while shrinkage and tendon relaxation contribute secondary, but measurable, effects. Sensitivity analyses indicate that segment casting intervals and loading age significantly influence differential cantilever deflections and closure alignment. Model predictions are assessed by comparing them with real-world observations, as reported in the literature. The findings emphasize the importance of integrating time-dependent analysis into construction stage planning and erection control to support camber adjustment, reduce the risk of closure misalignment, and enhance the reliability of balanced cantilever bridge construction.

Abstract. Construction 4.0 (C4.0) represents the integration of advanced technologies in construction projects aimed at enhancing productivity, safety, and sustainability. Despite its potential, many professionals in the construction industry hesitate to adopt C4.0 technologies, largely due to challenges such as project complexity, external uncertainties, short-term focus, and cultural barriers. To address this reluctance, this study aims to identify and categorize the benefits of C4.0 technologies within the construction industry. A systematic literature review was conducted, and through a detailed review of 179 publications, a comprehensive classification system was developed, organizing the benefits into five key categories: operational aspects, communication and collaboration, innovation and creativity, human resources and workforce, and management. Among these categories, operational aspects contain a high number of benefits. The identified benefits were ranked by their frequency of citation in the reviewed publications, with increases in project efficiency and productivity taking the top two ranks. The findings of this study equip decision-makers and project managers with the insights necessary to make informed choices about adopting C4.0.

Abstract. Mechanical equipment needs periodical maintenance and replacement to sustain essential building functions. Due to the complex room layout and numerous existing equipment within the mechanical room, it presents unique challenges in efficiently and safely performing such maintenance and replacement tasks. This paper investigates the approach of using Augmented Reality (AR) technology to assist with mechanical equipment installation within existing facilities. With its capability to overlay digital information on top of the physical environment, AR technology can provide additional visual guidance with 3D models and spatial mapping, allowing navigation guides, real-time distance measurements, and safety alerts. A pilot case study is presented to compare the workflow between the traditional site plan approach and the AR assistance approach for mechanical equipment installation planning. The results suggested significant improvements in efficiency, accuracy, and safety. The findings of this study demonstrated the potential of AR technology in assisting mechanical equipment installation for existing facilities, improving efficiency, safety, and effectiveness.

Abstract. This study explores how artificial intelligence (AI) enabled workflows are reshaping employment criteria for entry-level construction management (CM) professionals and how these changes may inform future CM curricula. A quantitative survey was distributed to forty construction professionals in California who are directly involved in hiring, supervising, or evaluating project engineers. Descriptive statistics were used to summarize current and anticipated levels of AI adoption, perceived effects on entry-level training, and expectations for skill development. Results suggest that AI adoption across construction workflows remains moderate, indicating growing interest but limited implementation to date. Respondents noted that automation is beginning to replace certain repetitive estimating and scheduling tasks, which may reduce some traditional task-based training opportunities. At the same time, participants expressed cautious optimism that automation could create opportunities for higher-order analytical work. Overall, the findings highlight that while AI integration in construction is advancing gradually, its influence on workforce development remains uncertain, underscoring the need for CM programs to balance foundational technical instruction with emerging competencies in AI oversight, data literacy, and ethical decision-making.

Abstract. Emerging technologies are at the forefront of the ever-changing modern business environment, impacting industries in the US, including construction. Although the construction industry has made significant strides in adopting innovation over the last two decades, it has historically lagged in adopting technological innovations. This is because technological innovation adoption is not a straightforward process, and numerous barriers can affect it. Some of these barriers include the environments in which potential adopters operate, implementation costs, and the geographical locations in which construction businesses might operate. This study explores barriers to integrated technology adoption and implementation in the construction industry in states with poverty rates above the national average. An online survey was used to collect data, and descriptive statistics were used to analyze it. The study population included construction workers in three states with significant persistent poverty, measured by the percentage of counties with persistent poverty. The results indicate that a dual bottleneck fundamentally stalls technology adoption in construction: the initial cost burden and the internal inability to effectively utilize the investment. These findings from this study support the possible roles of vendors and academic institutions in helping the construction industry overcome barriers to integrating technology into its operations.

Abstract. Machine learning (ML) has become an increasingly important component of pavement management systems (PMS), where historical condition data are used to support maintenance and rehabilitation planning. However, these datasets frequently contain sensor noise and undocumented field activities, which can introduce abrupt and unrealistic improvements in condition scores. Such anomalies disrupt the expected gradual deterioration patterns and can reduce the predictive reliability of data-driven models. To address this, a trend-consistent adjustment method based on typical annual deterioration rates is applied to smooth the data and restore continuity. This study identifies the optimal degree of smoothing to apply during data preprocessing to maximize generalization accuracy when training data contain noise and unrecorded maintenance events. Model evaluation is performed using the original, uncorrected test data to reflect real-world prediction scenarios. Prediction performance improved significantly with correction, with the best model (Voting Classifier) reaching an F1-Score of 81.98% at the 10% correction level, representing a 7.35 percentage point increase over the raw data baseline. The optimal correction range was found to be 10-20% of imperfect sections corrected, confirming that light, selective smoothing balances trend fidelity with real-world variability better than raw or heavily smoothed data, producing a more reliable prediction of pavement deterioration.

Abstract. The emergence of cutting-edge technologies such as the Internet of Things (IoT) and Digital Twins (DTs) has transformed industries, including construction, by enabling real-time data monitoring and improving decision-making. Precast concrete components are widely used in construction due to their durability and quality. IoT and DT technologies can drastically reduce labor, material, and energy costs by detecting inefficiencies and streamlining production schedules. Despite the promising potential, the integration of IoT and DT technologies in precast concrete production remains to be explored to overcome the challenges associated with their implementation. This study explores the integration of IoT and DT technologies into the design and fabrication of precast elements. The specific objectives are to 1) conduct a systematic review to characterize the potential applications of Digital Twin and IoT in the design and fabrication of precast elements, and 2) develop a conceptual IoT-enabled Digital Twin framework to enhance the efficiency of the design and fabrication of precast elements. The findings of this study are expected to provide a basis for future studies and insights on how IoT and Digital Twin technologies can be effectively integrated to enhance quality control, optimize production processes, reduce costs, and improve the lifecycle management of precast components.

Abstract. Construction sites require effective security monitoring during non-operational hours to prevent theft, vandalism, and safety concerns. However, construction site security is often overlooked and limited to fencing and signage systems. Staffed security and multi-camera setups are vulnerable to human-error and often require continual adjustment over the life of a project, and many commercially available autonomous systems remain financially expensive. This research aims to develop and evaluate a low-cost, autonomous, moveable monitoring system that integrates 2D Light Detection and Ranging (LiDAR) and Passive Infrared (PIR) sensors to detect motion, identify unauthorized activity, and deter intrusions on construction sites. Experimental testing evaluated detection reliability, false alarm rates, and environmental performance in indoor and outdoor settings. Results showed that LiDAR was able to accurately detect motion with ranges exceeding 30 feet and demonstrated reliability in varying environmental conditions. PIR sensors did not demonstrate reliable motion detection, and additional research is needed to improve their performance in construction settings. These results demonstrate that combining LiDAR and PIR sensing offers a practical basis for affordable, autonomous construction site security. Future work will address PIR calibration, environmental hardening, and algorithm parameter tuning.

Abstract. This study explores how to automate the process of RFP reviews for specialty contractors in making their bid/no-bid decisions efficiently. Specialty contractors typically rely on their intuition and experience to make bidding decisions. Making such decisions when faced with choosing multiple project opportunities can be particularly taxing for small-sized specialty contractors who usually have few people assigned to do this task. They often have to rely on consultants for bid document preparation, which comes at a premium. This study addresses this challenge by prototyping and testing a web application that uses a Multi-Criteria Decision-Making method’s (MCDM) Weighted Sum Model (WSM), to make reviews faster and more objective. This enables users to assign weight values to each bidding factor, extracted from existing literature. The system then automatically calculates a WSM score for each RFP, then normalizes the score to the range of 0 to 100. The solution, deployed as a web app, provides specialty contractors with a low-cost, instantly deployable tool that reduces the time and effort needed to screen RFPs. This enables them to focus on core operations and respond quickly to opportunities, while advancing knowledge on automated RFP review using MCDM and natural language processing by computers.

Abstract. This study empirically evaluated the accuracy of an AI-based quantity takeoff (QTO) platform, Togal AI, by comparing its automated measurements against contractor-produced takeoffs for a live commercial construction project. The analysis included 29 line items spanning exterior, floor, and ceiling finishes, as well as windows and doors, quantified in square feet (SF), each (EA), and linear feet (FT). Using non-parametric statistical methods—including the Wilcoxon signed-rank and Kruskal–Wallis tests—the study examined whether systematic deviations existed between AI- and contractor-generated quantities. It was found Togal AI’s overall deviations were small but statistically significant, showing a consistent underestimation for area-based quantities while achieving near-perfect alignment for count-based items. Further analysis indicated that measurement accuracy varied significantly by finish type: ceiling finishes exhibited the highest consistency with contractor data, floor finishes demonstrated moderate agreement, and exterior finishes showed the greatest deviation. The results prove that AI performs best when quantifying repetitive, clearly bounded, and orthogonal elements but becomes less reliable when interpreting irregular geometries and complex façades. The study provides the first quantitative validation of Togal AI in professional practice and concludes that while AI can accelerate takeoff workflows, estimator oversight remains essential for accuracy assurance in complex building elements.

Abstract. This study presents an evidence map of AI-startup activity across the architecture, engineering, and construction (AEC) lifecycle in the post-ChatGPT period (2023–2025). Peer-reviewed literature and auditable public implementations were synthesized and coded by project phase, task, AI modality, integration touchpoint, and reported evaluation approach. Activity is concentrated in design and construction, with comparatively fewer offerings in feasibility and operations where data are sparse or heterogeneous. Reported use cases cluster around design optioneering and model checking, preconstruction quantity takeoff/estimating and schedule-risk analytics, and construction safety and progress monitoring. Across modalities, generative and language-model tools dominate design and document intelligence, computer vision dominates progress and safety workflows, and predictive analytics supports select operations use cases. The review identifies five recurring barriers, data readiness and integration, industry culture and trust, scalability versus customization, regulatory/liability posture, and workforce capability, and translates them into actionable evaluation guidance. Specifically, we provide phase-aligned decision aids for procurement and pilots, including a startup screening rubric and a pilot scorecard that pairs technical validity with operational KPIs and integration readiness. The findings inform practitioner adoption strategies and support research and education agendas emphasizing standardized reporting, reproducible evaluation protocols, and multi-site validation.

Abstract. Digital transformation is advancing in construction, yet evidence on how early-career professionals prioritize specific technologies and adoption conditions remains limited. This study surveyed alumni (2014-2024) from an undergraduate construction management program (58 complete responses) to examine perceived current importance of key digital technologies, expected five-year impact, and perceived barriers and deterrents to adoption, with comparisons by experience band and skill-acquisition pathways. A cross-sectional Qualtrics questionnaire collected Likert ratings of technology importance and barrier frequency, plus multi-select items on future high-impact technologies, sources of digital skills, and valued software features. Analyses included descriptive statistics, Relative Importance Index (RII) rankings, an exploratory Horizon Gap Index (HGI) contrasting normalized current importance with “top three” future salience, and point-biserial correlations linking barriers to discouraging factors. BIM/VDC ranked highest in current importance, while AI showed the largest positive horizon gap; most other technologies exhibited negative gaps, indicating stronger current embeddedness than future salience in the selection format. The most frequently reported constraints related to training, time, cost, and organizational support, with barrier–discouragement associations suggesting co-occurring resource and capability limitations. Alumni most often reported self-directed learning and prioritized integration and mobile accessibility, supporting implications for targeted training, mentorship, workflow standardization, and curriculum alignment with practice needs.

Abstract. Site visits are significant in Architecture, Engineering and Construction (AEC) education as they provide hands-on knowledge that bridges theory with practice. However, logistical, safety, and instructional constraints often limit their accessibility and effectiveness. While interactive virtual learning environments offer a promising alternative, most existing AEC virtual site visits rely on rigid, non-adaptive content with limited responsiveness to diverse learner needs. AI-based adaptive instructional support has the potential to address these limitations, yet its integration into AEC virtual site visits remains underexplored, leaving its feasibility and influence on learner experience insufficiently understood. This study presents the development and pilot evaluation of an AI-assisted virtual electrical systems site visit delivered through a desktop-based immersive virtual environment. By integrating AI models trained on domain-specific knowledge, the virtual environment provides context-aware and personalized instruction through real-time guidance, animations, and interaction via voice and text. The pilot study evaluated workload, motivation, usability, sense of presence, and engagement. Results indicated low workload, moderate motivation, acceptable usability, a moderate-to-high sense of presence, and active engagement among participants during the site visit. Overall, the findings demonstrate the feasibility of AI-assisted virtual environments for supporting practical AEC learning while highlighting the need for further refinement and investigation.

Abstract. Since collaboration with technology ventures has an important potential for the development and adoption of construction technology, identifying the barriers to this engagement is important. This study examines how mid-to large-sized U.S. construction firms engage with technology startups and the barriers that influence these collaborations. Results reveal that purchasing products and licenses represents the most prevalent form of engagement, with companies such as Drone Deploy, OpenSpace, and Join emerging as leading partners due to the maturity and demonstrated benefits of their technologies. The barriers related to these were clustered into four overarching themes: knowledge and fit, organizational/resource constraints, strategic/cultural misalignment, and risk/legal concerns. Among these, knowledge- and fit-related issues were found to be the most critical, particularly the challenges of identifying suitable startups and startups’ limited understanding of the construction sector. Conversely, concerns about intellectual property were less significant than in other industries, reflecting the sector’s preference for applied technological solutions over proprietary innovation ownership. Overall, the findings suggest that fostering effective corporate–startup partnerships in construction requires improving sector-specific knowledge exchange, enhancing organizational readiness, and developing trust-based mechanisms that enable long-term, strategic innovation collaboration.

Abstract. Point-cloud data have become central to digital construction workflows through technologies such as laser scanning and photogrammetry. However, current processing methods remain fragmented, time-consuming, and heavily dependent on expert supervision. This study aims to clarify how construction workflows handle point-cloud processing, compare traditional and deep-learning-based approaches for key processing tasks, and propose a more cohesive workflow. A focused literature-based data collection process (2023–2025) identifies common processing tasks, denoising, sampling, registration, semantic segmentation, and completion, along with representative deep-learning applications and their advantages. The study summarizes these findings in an evidence table that links processing tasks, construction use cases, and task-level benefits of deep learning. Building on this analysis, it presents a conceptual framework that connects preprocessing and semantic inference into an integrated deep-learning-driven pipeline for construction point-cloud processing. The paper concludes by outlining research priorities for task-specific benchmarking, standardized datasets, and integration with construction information systems to enable reproducible and scalable automation.

Abstract. Although best-value (BV) procurement has been increasingly adopted in design-build (DB) delivery, empirical evidence on the practical implementation of BV principles remains limited. This study examines the use of BV in DB projects by testing three hypotheses concerning (i) the extent of price dominance in BV evaluations, (ii) differences in schedule and cost outcomes across procurement methods, and (iii) variations in evaluator scoring patterns. Data from 42 highway construction projects (26 BV and 16 low-bid [LB]) were analyzed using Spearman’s rank correlation, independent-samples t tests, and Wilcoxon rank-sum tests. The key findings show that final evaluation rankings in most BV projects exhibited perfect alignment with bid price rankings, indicating that award decisions were largely price-driven. No statistically significant differences in schedule growth were observed between price-dominant BV and LB projects; however, price-dominant BV projects exhibited lower cost growth, which reflects a partial influence of non-price criteria during pre-award planning. Furthermore, evaluator scoring patterns did not differ significantly between price-dominant BV and LB methods, as reflected in award margins and evaluation score variability. This study provides empirical insights into how BV procurement operates in practice, revealing constraints that limit value-oriented decision-making and underscoring the need for more robust evaluation approaches.

Abstract. Technology has been a significant driver for decision risk analysis on construction projects. New and upcoming technologies, combining human experience and technological data output, introduce complexity when making decisions related to cost, time, quality, and safety. Evidence-based practices have traditionally been used within project delivery methods to manage these risks. Technology further influences project risk management by integrating expert knowledge with data analysis. Moreover, technology creates risks associated with projects using expert knowledge to assess and manage project risks. Evidence-based decision processes provide a problem-solving approach that bridges best practices and human expertise. Research has been conducted suggesting differences between the use of design-bid-build (DBB) and design-build (DB) methods in how technology affects risk management within and between them. A survey of industry practitioners collected and analyzed data using a two-way analysis of variance (ANOVA) to determine commonalities and differences related to technology in the DBB and DB approaches. The research supports findings that the DB method fosters greater communication through a more collaborative environment when using technology during the early stages of project delivery.

Abstract. Trade tariffs affecting construction materials, including increased tariffs on imported steel and aluminum to 50%, applying a 50% duty on semi-finished copper, and imposing 10–25% tariffs on softwood lumber and related derivatives, have intensified price instability and compliance risk for U.S. construction contractors. Existing research models price escalation and examines macroeconomic impacts; however, little empirical research explains how contractors respond to tariff-driven volatility in practice. Using Charmaz’s Constructivist Grounded Theory, this study develops an inductively derived explanation of contractor decision-making under the 2025 U.S. tariff regime. Ten semi-structured interviews were conducted with general contractors, specialty contractors, and residential builders across multiple U.S. states. Data collection and analysis occurred concurrently using initial, focused, and theoretical coding until theoretical saturation was reached. The core category—manufacturing stability in volatile markets—shows that contractors assume pricing instability and proactively contain exposure before volatility materializes. Contractors achieve this through accelerated procurement and price locking, contractual transfer of tariff-related risk, strategic substitution of tariff-sensitive materials, and relationship-driven market intelligence. The findings indicate that contractors are responding not to higher prices alone, but to unpredictability. Stability, rather than lowest price, has emerged as the new basis of competition, extending existing escalation research by explaining how contractors proactively contain tariff-driven uncertainty.

Abstract. Design-Bid-Build (DBB) remains the most common approach for building highways used by the State Department of Transportation (DOT). About 80% of highway projects are still built using this method. This study collected data on 140 DBB highway projects with total costs exceeding $10 million from five Texas DOTs: Austin, Dallas, Fort Worth, Houston, and San Antonio. The study analyzes cost- and schedule-related data from these projects and compares their performance across these five districts. Statistical test results show that projects completed under the Houston district had higher cost growth than those in Austin, Dallas, and San Antonio. However, the projects completed under the Houston district had significantly lower schedule growth than those completed under the Austin, Dallas, and Fort Worth districts. This study shows that the project owner also plays a key role in highway project performance and that the district management style is key to reducing cost and schedule growth. The study’s main contribution is that DOTs should identify effective working practices used across district offices to control highway project costs and schedules, so these practices can be applied in future projects to improve performance.

Abstract. Unbalanced bidding is a persistent problem in highway project contracts, especially with asphalt overlay projects where pay quantities are subject to significant variation. Under unit-price contracts, contractors can strategically inflate or deflate specific bid items to maximize cash flow, making it difficult to manage project costs. This research examines the frequency and trends of unbalanced bidding in the Texas Department of Transportation (TxDOT) overlay contracts within the Fort Worth and Houston districts. Using bid and engineer’s estimate records for 52 projects, the study quantifies item-level bid cost deviations and examines contractors’ bidding patterns to determine whether unbalanced bidding occurs in those contracts. Initial review indicates measurable unbalanced bidding in early-stage items such as Traffic Control. However, the study also found that the contractors are bidding higher on later-phase items, e.g., Asphalt Overlay and Pavement Marking. There is insufficient evidence to prove that systematic unbalanced bidding occurs in highway contracts executed by the Texas DOT. Further study is required, using more bid data points, to validate whether unbalanced bidding patterns occur in highway construction contracts.

Abstract. The construction industry is undergoing rapid digital transformation, driven by the demand for greater efficiency, cost control, and timely project delivery. This study evaluates the role of digital tools such as Building Information Modeling (BIM), artificial intelligence (AI), and machine learning in enhancing infrastructure project performance. Using a mixed-method approach that combines survey data and literature review, the research investigates how these technologies influence key performance metrics, including cost efficiency, resource allocation, and schedule adherence. Findings reveal that while digital tools are increasingly adopted, full integration remains limited due to barriers such as limited expertise, high implementation costs, and resistance to change. Technologies like BIM, AI, and 3D printing show significant promise in improving decision-making, stakeholder coordination, and real-time performance tracking. The study highlights actionable strategies for overcoming adoption challenges and optimizing technology integration. By addressing capability gaps and financial constraints, the research underscores the strategic importance of digitalization in achieving sustainable and efficient infrastructure development.

Abstract. The construction industry faces increasing pressures from climate change, resource constraints, and rapid urbanization, driving growing interest in digital practices to improve project delivery. Virtual Design and Construction (VDC) has emerged as a promising approach; however, literature remains fragmented, with limited synthesis of its applications, benefits, and challenges. This study conducts a literature review of 476 publications and an in-depth analysis of 20 influential studies spanning diverse project types and contexts to evaluate the current state of VDC practice and prospects. The review identifies dominant VDC application trends, implementation patterns, maturity trajectories, and shifting implementation priorities across project phases and organizational contexts. Findings indicate a clear shift from early visualization- and coordination-focused uses toward more integrated, platform-oriented implementations that support project control, data-driven decision-making, and lifecycle considerations. Reported benefits evolve accordingly, from error reduction and communication improvement to enhanced schedule reliability, safety planning, and cost transparency through 4D/5D modeling. Persistent challenges include inconsistent definitions, limited standardization, high upfront investment, insufficient long-term validation of return on investment, and workforce gaps. By synthesizing these trends, the study clarifies how VDC has matured as a project delivery methodology and provides evidence-informed insights for researchers and practitioners. The findings underscore the importance of aligning VDC with Lean practices and emerging digital ecosystems, such as digital twins, artificial intelligence, and mobile technologies, to support more effective, resilient, and sustainable digital transformation in construction.

Abstract. Despite decades of research, cost overruns in construction projects, especially large-scale infrastructure, remain a persistent global issue. Extensive literature has examined this topic, with most studies focusing on identifying the causes of cost overruns. However, significant disagreement remains among researchers regarding their root causes. This paper critically examines these divergent perspectives to work toward a common understanding through narrative synthesis and deductive reasoning. An exploratory literature review supported by Natural Language Processing (NLP) was then conducted to identify commonly overlooked themes in cost overrun research, clarify conceptual and methodological shortcomings, and outline directions for future inquiry. The review identified three recurring gaps: an overreliance on perception-based studies, insufficient attention to exogenous factors, and a limited examination of causal relationships and underlying root causes. This paper contributes by integrating perspectives on the debated root causes of cost overruns into a cohesive framework that articulates where and why, current understandings diverge. It calls for a transition toward empirically grounded, data-driven methodologies that capture the complex interdependencies among causes while incorporating both endogenous and exogenous factors, including political and institutional influences. These contributions strengthen theoretical development and promote more robust, evidence-based approaches to understanding and managing cost overruns.

Abstract. Electrical contractors are critical trade partners for construction projects, increasingly so with the electrification of transportation infrastructure, the proliferation of smart building technology, and the enormity of under-construction data centers. Profitable production by electrical contractors is challenged by schedule compression and out-of-sequence construction with 123 electrical contractors reporting that more than 60% of their projects incurred significant cost impacts due to these types of schedule change between 2020 to 2023. In the current market, electrical contractors are pushed to complete projects of increasing complexity within aggressive - commonly unrealistic - timeframes. Despite these operational demands, electrical contractors strive to maintain relationships of value and trust with their general contractor and owner clients. This research investigates and summarizes causes, implications and other topics related to third party-caused changes onto electrical contractors in their planned production. This research shares insights to support electrical contractors in identifying and mitigating the impacts of schedule change. This research uniquely provides data sourced from electrical contracting subject matter experts.

Abstract. Effective supervision is crucial for successful project execution, yet many construction projects encounter delays, cost overruns, and quality problems due to inadequate supervisory practices. Limited empirical evidence exists on which specific supervisory roles and competencies most influence project success. This study explores the impact of supervisory roles on project implementation and identifies key supervisory factors shaping overall effectiveness. A quantitative approach was used to assess supervision and project delivery in Kumasi, a major metropolitan city in Ghana. Data were collected through structured questionnaires from 235 construction professionals employing stratified, purposive, and convenience sampling. Descriptive statistics and Structural Equation Modelling (SEM) were employed, adhering to ethical standards. Results revealed five essential supervisory competencies: quality control vigilance, problem-solving and decision-making, motivational engagement, supervisory transparency, and effective communication. Exploratory Factor Analysis identified four supervisory dimensions explaining 69.8% of the total variance: Management and Motivation, Technical and Operational Competence, Leadership and Vision, and Accountability and Ethics. These findings demonstrate that effective supervision depends on both technical skills and leadership behaviors. Although focused on Ghana’s construction sector, the study offers a framework for targeted training, recruitment, and performance evaluation. Enhancing these competencies can improve project efficiency, quality, and stakeholder trust, fostering sustainable infrastructure and socio-economic development.

Abstract. Inclusive leadership style has demonstrated greater influence in determining the extent to which employees feel psychologically safe in the workplace environment. Inclusive leadership is believed to foster employee creative behaviour and improved psychological safety. Therefore, this study aims to assess the mediating factors of inclusive leadership and psychological safety relationship in the construction workplace due to scarce knowledge of these factors. The study obtained cross-sectional data through 179 (online) and 74 (hand-delivery) surveys from construction professionals in the Nigerian built environment. Firstly, the data were subjected to mean score testing, after which maximum likelihood factoring (MLF) with varimax rotation was used to establish three underlying factors that mediate inclusive leadership-psychological safety relationship. These factors include recognizing employee inputs and concerns, valuing an inclusive workplace culture, and supportive motivational climate. These findings could go a long way in guiding construction managers to lead inclusively, thereby fostering a psychologically safe workplace for improved creative behaviors in the Nigerian built environment.

Abstract. Commissioning and testing of electrical systems in power plants are critical processes that ensure safety, reliability, and compliance before operations begin. Traditional methods for commissioning are often paper-intensive, fragmented, and dependent on manual procedures that can compromise efficiency and safety. With increasing system complexity and digital integration in power generation facilities, conventional practices are no longer adequate to meet modern project demands. This study investigates how Virtual Design and Construction (VDC) technologies can transform electrical system commissioning in power plants. Through the combined use of Building Information Modeling (BIM), digital twins, augmented and virtual reality (AR/VR), Internet of Things (IoT) sensors, and cloud-based collaboration platforms, VDC enables data continuity, real-time coordination, and improved test accuracy. The research synthesizes industry case studies and technical literature to develop a structured implementation framework addressing pre-commissioning planning, virtual simulation, field testing, and digital handover. The proposed framework provides a practical roadmap for applying VDC to enhance efficiency, safety, and digital integration in electrical commissioning while establishing a foundation for long-term operational improvement.

Abstract. University students studying construction management participate in internships to gain practical experience, enhance their classroom knowledge, improve their communication skills, and get a glimpse of the industry’s work environment and culture. This study aimed to understand students’ internship experiences through a student-led, closed-door, moderated discussion with approximately 40 participants. This format encouraged participants to share their experiences openly and suggest ways to improve internship programs. During the session, participants responded to guided questions using sticky notes, collaborated in small groups, and then shared their answers with the larger group for additional discussion. The written notes were collected, transcribed, and analyzed, revealing themes related to the different interaction timelines companies have with students, from initial recruitment to the completion of the internship. Findings indicate that students desire diverse recruiters in the positions they will be hired for, improved communication prior to the internship, challenging work, greater exposure to the industry through a structured internship program, and regular feedback, including an exit interview. This study can serve as a resource for industry professionals to develop stronger internship programs, for faculty members to create classroom content that addresses industry culture, and for students preparing for internships to advocate for clear communication and feedback.

Abstract. This study addresses persistent challenges in Career and Technical Education (CTE) systems related to fragmented program information, limited visibility of training pathways, and insufficient integration of labor-market data. In Wyoming, these challenges are amplified by a dispersed population and a workforce heavily reliant on middle-skill occupations. To address this gap, the study presents the design and development of the Wyoming Career and Technical Education (CTE) Datahub, a centralized, web-based platform that consolidates postsecondary CTE program offerings and aligns them with workforce demand indicators. Using a descriptive, data-driven methodology, publicly available program data from community colleges were compiled, standardized, and reclassified into eight Wyoming-specific CTE clusters. Labor-market and wage data were integrated from national and state sources to contextualize educational pathways. The resulting platform features interactive tools, including a CTE cluster wheel, career interest profiler link, institutional filters, and program matrices that enable users to explore programs by career field and college. Findings indicate that integrating program-level data with labor-market information in a single digital environment improves transparency, usability, and alignment between education and workforce needs. The study demonstrates the potential of centralized CTE data platforms to support informed decision-making for students, educators, counselors, and policymakers, while offering a scalable model for other states seeking to strengthen education-to-workforce systems.

Abstract. Women remain underrepresented in Architecture, Engineering, and Construction (AEC) education and careers globally, particularly in technical and leadership roles. This comparative study examines the experiences of female students in AEC programs across China, the United States (U.S), and Ibero-America. Survey results reveal that female representation in academic programs varies widely, with mentorship and support systems less accessible in China and Ibero-America than in the U.S. Anticipated career barriers include poor work-life balance, limited promotion opportunities, low salaries, and discrimination, with 72% of Chinese respondents considering leaving the industry before entering the workforce, compared to 41% in the U.S. and 30% in Ibero-America. Students identified effective strategies for retention, such as mentorship programs, leadership pathways, caregiving flexibility, and mental health resources. Although there are variations between regions, cultural norms and recruitment practices continue to be the most significant factors influencing outcomes. Current studies lack cross-regional analyses of pre-career experiences and motivations among women in AEC, highlighting the need for targeted interventions. This study addresses this gap by providing evidence-based recommendations to improve preparation and long-term retention of women in AEC fields.

Abstract. Construction superintendents play a pivotal role in project success, yet academic research offers limited insight into how their responsibilities vary by company size and market type. This study analyzes 290 job postings from the Southeastern United States, categorizing them by company size (small, medium, large, mega) and market sector (e.g., civil, commercial, residential). Using MAXQDA for qualitative analysis, the research identifies common responsibilities and action verbs associated with the superintendent role. Findings show that core duties—such as schedule management, subcontractor coordination, safety enforcement, and quality control—are consistent across contexts. However, the complexity and emphasis of these tasks scale with company size and market sector. Small companies with smaller projects often require direct, hands-on oversight, while mega projects demand strategic leadership and high-level coordination; Governmental or Environmental sector projects focus on regulations, while residential sector projects focus on client satisfaction. Despite these variations, the superintendent’s essential functions remain stable across the industry. These insights support the development of more targeted training programs and academic curricula to better prepare future construction leaders for diverse project environments.

Abstract. This pilot study presents an integrated deep-learning framework that not only detects but also identifies and records noncompliance with personal protective equipment (PPE) in real time on construction sites. The framework utilizes an object detection model, achieving a mean average precision (mAP) of 93%, and employs a rolling average supported by a real-time object tracking algorithm to minimize false positives in complex site environments. Detected violations trigger a deep learning facial recognition model that identifies the individual. All relevant data, including time of occurrence, nature of violation, and identity, are then stored in a Structured Query Language (SQL) database for subsequent analysis. This system addresses a critical research gap by going beyond detection to create a comprehensive record of unsafe behaviors, thereby enabling targeted interventions and data-driven safety enhancements. Despite its promising results, limitations such as occlusions and a relatively small dataset remain, suggesting that future work should incorporate larger, more diverse datasets to further refine and validate the approach.

Abstract. Construction Inspectors (CIs) serve as critical agents in maintaining quality, safety, and compliance within transportation infrastructure projects. Despite their essential role, state Departments of Transportation (DOTs) in the United States continue to face difficulties in recruiting and retaining qualified personnel, primarily due to limited funding, retirements, and reduced interest from younger professionals. These challenges highlight the importance of implementing improved and standardized training programs to maintain a skilled and capable inspection workforce. This study conducts a comparative review of CI training programs across seven major state DOTs in the United States to identify standardized and state-specific training practices. The analysis explores different instructional modules, delivery modes, assessment mechanisms, and prerequisite coursework requirements. Findings revealed significant variation in training frameworks, reflecting differences in state priorities and instructional strategies. By synthesizing these practices, the study contributes to the development of a more standardized and competency-based approach to CI training, supporting the advancement of an adaptable and skilled inspector workforce across the nation’s transportation sector.

Abstract. Rapid growth in U.S. data-center construction is forcing specialized general contractors to onboard geographically dispersed teams under tight schedules. Many firms still rely on informal mentoring, creating variation in documentation, digital workflow execution, and communication norms as experienced hires arrive with different playbooks. This design-based, single-firm case study documents how an industry–academic team implemented an internal corporate university to standardize Procore-based processes and company expectations. The team conducted a training needs assessment, selected an LMS using a multi-criteria decision matrix, and developed 40 microlearning modules organized into three components: construction management foundations, Procore workflow execution, and “The Company Way.” The program was piloted on two project teams using six core modules (Submittals, Job Cost Control, Scheduling Basics, Pay Applications, RFIs, and Leadership Fundamentals). Pilot indicators from LMS analytics (completion, time-on-task, quiz performance) and coded supervisor logs suggest clearer expectations for task completion and more consistent workflow execution, while longitudinal outcomes remain in progress. The paper contributes a transferable framework, an LMS selection approach, and a practical mixed-method evaluation design for contractors scaling onboarding during rapid growth.

Abstract. The Australian construction sector continues to face a significant shortage of skilled labor, a challenge exacerbated by high rates of apprenticeship non-completion, a trend also observed in other developed economies. This study examines barriers to apprenticeship completion among participants enrolled in Building and Construction apprenticeships. Employing qualitative methods, data was gathered through focus group interviews with apprentices, employers, and trainers, and analyzed using content analysis in NVivo 12. Findings reveal a multifaceted set of challenges, including educational difficulties, employer-related constraints, financial pressures, unclear career pathways, poor work ethic, and ambiguous role expectations. This exploratory research enhances understanding of the structural and interpersonal factors influencing apprenticeship outcomes and provides actionable insights for vocational education stakeholders.

Abstract. Labor shortages continue to challenge the construction industry’s ability to meet project demands and maintain productivity. One workforce strategy receiving increasing attention is multiskilling, which involves training and assigning workers to perform tasks across more than one trade. This paper reviews existing studies on multiskilling in construction to understand its impact on project performance and workforce outcomes. A total of 53 studies were examined, including 17 that quantitatively assessed cost, schedule, productivity, and manpower utilization. The findings suggest that multiskilling can improve efficiency and flexibility, though most studies rely on simulated data rather than real world projects. There remains a need for research grounded in field data, particularly within the United States, to better understand how multiskilling performs under actual site conditions. The review identifies gaps, including inconsistent definitions of performance metrics, limited comparisons with single-skilled labor, and lack of consideration for regulatory requirements such as prevailing wage and apprentice-to-journeyman ratios. Continued research is needed to address these gaps and build a more practical understanding of how multiskilling can be effectively applied in construction projects.

Abstract. Mental health is a significant cause of suicide and disability worldwide. It has particularly affected the construction industry. The American construction industry, a vital economic sector, faces a significant but often unaddressed crisis regarding the mental health and well-being of its workforce. Synthesizing findings from multiple studies, this paper will critically examine the prevalence, causes, and impacts of mental health issues among construction workers and project professionals. Research consistently highlights the severe psychosocial work environment as a primary contributor to these issues. Key stressors include demanding schedules, long working hours, high job insecurity, tight deadlines, hazardous working conditions, and a pervasive culture that discourages the expression of vulnerability or the seeking of help. Studies confirm alarmingly construction industry high rates of mental health issues, including depression, anxiety, and elevated suicide risk, significantly greater than those in the general working population. Additionally, a lack of adequate social and organizational support aggravates the negative effects of work stress. These challenges have a tangible impact on operational outcomes, including reduced labor productivity, increased turnover, higher rates of accidents, and compromised project quality. Addressing this crisis requires a multi-faceted approach, encompassing organizational culture change, improved work-life balance, and the implementation of robust mental health support programs. The findings of this study produced in a framework will help deepen the understanding of professional mental health assessment scales and relevant factors as used in the construction industry.

Abstract. The COVID-19 pandemic forced a rapid shift to remote working across the UK construction industry, fundamentally altering established Quantity Surveying (QS) practices that traditionally relied on site presence and face-to-face collaboration. While prior studies have examined these changes at an industry level, limited qualitative evidence exists on how UK-based Quantity Surveyors experienced this transformation in practice. This study aims to explore how the pandemic reshaped QS roles, working practices, and future competency requirements. A qualitative, phenomenological approach was adopted, using semi-structured interviews with seven practising UK Quantity Surveyors. The data were analysed thematically. The findings indicate that digital tools enabled continuity of service but weakened informal communication and mentorship, while remote working intensified workloads and blurred work–life boundaries, increasing burnout risk. Hybrid working and enhanced digital competence emerged as central to sustainable future practice, alongside the continued importance of traditional site-based skills. The study provides empirical insight into the professional impacts of pandemic-driven change and highlights implications for organisational policy, professional development, and the future delivery of Quantity Surveying services.

Abstract. This study evaluates TxDOT's pavement asset management maturity by conducting a document-based assessment in accordance with international and federal standards. The analytical approach was rooted in ISO 55000/55001 standards, the GFM maturity model, and FHWA TAM requirements. TxDOT's performance reports, asset management plans, and strategic plans were evaluated subjectively and assigned a grade based on a five-level maturity scale. A directed content analysis of TxDOT documents was conducted, encompassing coding best practices and assessing maturity levels ranging from Initial to Leading. Findings recommended Policy alignment, data management, decision-making, and performance management have been assigned as “Proficient” Level 4, whereas lifecycle management, risk management and resilience, and organization-wide integration fall into the category as “Structured” Level 3. All federal TAM criteria are satisfied by TxDOT, and excellence is demonstrated in inventory and condition monitoring; however, comprehensive risk mitigation and continuous improvement are lacking. The document-based maturity evaluation indicates TxDOT's progress and identifies areas for improvement. Findings also suggest that adherence to international standards, implementation of risk and resilience planning, and conducting maturity self-assessments may enhance asset management. The study outlines an approach for state DOTs to assess their asset management maturity relative to industry guidelines and promote strategic enhancements.

Abstract. Knowledge transfer (KT) within construction organizations, especially small and medium-sized construction organizations (SMGCs) is often overlooked. Understanding how small and medium size general contractors utilize different methods for transferring knowledge helps organizations within this subset adapt to competitive market conditions. This research used semi-structured interviews to investigate the extent to which SMGCs utilize formal KT methods and explores the perceived benefits associated with these processes. Open coding identified 9 themes regarding the benefits of formal KT perceived by project teams. Axial coding identified 4 key themes related to KT, including employee development and engagement, continuous communication and collaboration, individual project optimization and evaluation, and organizational learning. Selective coding then suggested the need to focus on KT at different levels. Including: individual, project, and organization level to facilitate effective KT within SMGCs. The results further suggest that KT is best achieved through constant communication and collaboration between project teams. Also that development of standardized KT processes is an effective strategy.

Abstract. This study investigates the psychological competencies required for effective leadership within the Architecture, Engineering, and Construction (AEC) industry, with a particular focus on emotional intelligence (EI) and transformational leadership. Recognizing that leadership significantly influences organizational performance, this research aims to identify traits that promote collaboration, innovation, and team cohesion in project-based environments. Drawing from established psychological theories and leadership models, this study examines how leadership is perceived across different organizational roles and experience levels. Using a survey platform called Qualtrics, a survey questionnaire was distributed to approximately 1,000 students and faculty members in the Construction Management and Architecture Department at Kennesaw State University. Of the responses received, 22 participants who are currently working in the AEC industry provided insights into their understanding of EI and leadership practices. The findings support that emotional intelligence, particularly interpersonal and intrapersonal skills, alongside transformational leadership behaviors, are widely regarded as essential qualities for effective leadership in the AEC sector. These results offer practical implications for leadership development, emphasizing the importance of soft skills and emotional awareness in fostering high-performing teams and resilient organizations.

Abstract. This paper analyzes trends in construction-related research awards and the inclusion of an interdisciplinary approach in the United States National Science Foundation (NSF) awarded research. The data included in this paper is from the NSF fiscal years from 1985 to 2024. The need for an interdisciplinary approach in construction research has been well-argued in research publications. An interdisciplinary approach in research emphasizes addressing research problems by teams or individuals that integrate information, data, techniques, tools, perspectives, concepts, and/or theories from two or more disciplines. In this paper, the NSF-funded awards that include the word “construction” in the title or abstract are analyzed into four categories: “construction” and “management” awards, “construction” and trending topic awards, “construction” and “workforce” awards, and “construction” and “education” awards. The data was further analyzed to investigate the occurrence of the word “interdisciplinary” in the title or abstract. The results show that the number of interdisciplinary awards in these four categories ranged from 3.7% to 13.1%, and the awarded amount ranged from 3% to 16.5% of the total awards in the respective categories. The study offers a comprehensive, longitudinal evaluation of interdisciplinarity in NSF-funded construction research in the United States.

Abstract. Construction education at universities, community colleges, and trade schools plays a vital role in preparing students with the technical knowledge and professional marketable skills needed to successfully join the construction workforce. High-quality programs integrate classroom learning, hands-on experiences, and other activities to ensure graduates are workforce-ready. One of those other activities includes construction competitions that provide opportunities to students to apply classroom concepts in practical and competitive environments. Unfortunately, some construction programs are challenged to effectively identify and recruit students continuously who have the right mix of interest, availability, and experience. Thus, the problem addressed by this paper is the lack of data-driven understanding of the impact of students’ interest, experience, and commitment to participate in construction competitions. The overall goal of this study is to serve as an attempt to fill this gap by achieving two distinct objectives: (1) deconstructing the students’ selection criteria represented by "Total Score" and (2) predicting the probability of a candidate's final status outcome (i.e., accept an invitation to be part of a team). This research followed a quantitative research methodology. Data was collected through a detailed questionnaire distributed to construction students. The responses were analyzed to identify patterns in students' readiness and engagement, as well as gaps in experience or scheduling availability. The findings aim to inform faculty advisors and team coordinators in the selection and development of competition team members, ensuring that teams are composed of students with the appropriate balance of interest, experience, and availability.

Abstract. The U.S. construction industry continues to face a critical shortage of skilled workers due to rising infrastructure demand alongside an aging workforce. This research examines the California High-Speed Rail (CAHSR) project to assess the impact of skilled labor shortages on cost and schedule performance, as well as effective responses. A qualitatively driven mixed-methods design was adopted, with a combination of a targeted literature review, analysis of California High-Speed Rail Authority (CHSRA) business plans and labor data (2021-2024), and semi-structured interviews with CAHSR project stakeholders. The findings reveal that labor shortages are linked to higher costs associated with wage inflation, overtime premiums, and extended project durations; while schedule risks stem from delays on critical-path activities, task resequencing, reliance on overtime, and reduced flexibility. The study also highlights the limitations of short-term solutions and the importance of scalable, long-term workforce planning strategies such as internal workforce development, targeted recruitment, early planning, and selective technology adoption. These insights can inform comparable megaprojects seeking greater performance control and delivery resilience.

Abstract. Vertical construction has emerged as a solution to optimize limited space in areas with minimal territorial expansion. This methodology emphasizes maximizing land use efficiency by constructing upwards, rendering skyscrapers as the epitome of human innovation, architectural brilliance, and engineering complexity. These structures not only redefine city skylines but also address urban challenges, including sustainability, population density, and resource management. This research paper employs a qualitative methodology, primarily utilizing case studies to examine the architectural innovations, environmental impacts, and construction challenges associated with the three tallest skyscrapers in the world: the Burj Khalifa in Dubai, Merdeka 118 in Kuala Lumpur, and the Shanghai Tower in Shanghai. Through detailed case analyses, this study examines how each of these monumental structures utilizes cutting-edge design strategies and sustainable technologies, thereby contributing to the evolution of modern urban landscapes. The case studies provide valuable insights into engineering solutions and innovative design approaches that set new standards for future high-rise construction worldwide. This paper highlights the importance of vertical buildings in shaping future urban environments by examining their integration of complex architectural designs and their responses to contemporary urban needs.

Abstract. This paper evaluates the performance of AI generated machine learning models. Three commonly used AI platforms were selected for this study; ChatGPT, Gemini, and Perplexity. The dataset used was uploaded to the AI platforms and the choice of models was left open. The number of models investigated by Perplexity was the highest. Another iteration of the modelling was done by asking the AI platforms to run the same analysis using nine different models and the models were specified in this case. The results showed different prediction accuracy among the models, while the prediction accuracy was close among the platforms, in most cases. The drop in prediction accuracy from the training set to the test set was also checked for all the models and platform to study the overfitting tendency. The results showed that Perplexity had the highest overfitting tendency, while ChatGPT had the lowest. The results show that the use of AI worked well with the different machine learning techniques. On the other hand, the regression models did not work well and require human intervention to make them work better.

Abstract. In the United States, approximately 400 million tons of asphalt are replaced annually, Evidence shows that the Cold Recycled Asphalt (CRA), delivered as Cold In-Place Recycling (CIR) or Cold Central Plant Recycling (CCPR), remains underutilized on federal projects. Moreover, studies reveal that contracting guidance is fragmented and difficult to enforce specification. To address this gap, this study develops an evidence-informed Unified Facilities Guide Specifications (UFGS)-style specification framework that consolidates requirements for materials, mix design, production control, and field acceptance for CRA. The research adopts a qualitative, specification-development approach, combining a comparative review of federal, state, and industry specifications with semi-structured interviews of agency engineers, contractors, and researchers to adjudicate inconsistencies and refine enforceable thresholds. Key outcomes include (i) harmonized mix-design procedures that mirror field conditions; (ii) a lab-to-field acceptance ladder sets 100% at a test-section break-over density and calibrates nuclear gauge readings to laboratory bulk specific gravity, (iii) standardized gradation treated as a production consistency metric, and (iv) a contract-ready quality control checklist with designer guidance for CIR versus CCPR selection, curing expectations and rejuvenator use. The proposed framework improves enforceability, reduces quality variability, and supports cost and carbon reduction objectives while recovering high-quality aggregates on federal rehabilitation projects.

Abstract. Cross-laminated timber (CLT) provides environmental and structural advantages; however, moisture management remains a critical challenge for long-term durability, particularly in humid and coastal climates. While commercial liquid-applied coatings are widely used to protect mass timber, the added performance of weather and vapor-resistive barriers (WRBs) under prolonged outdoor exposure remains insufficiently documented. This study presents a comparative field evaluation of coated CLT wall and slab panels, with and without WRB systems, subjected to summer and early-fall coastal exposure in Bristol, Rhode Island. One full-scale mock-up was assembled using lab-fabricated CLT panels. All faces received a three-coat liquid finish, and half of each panel was additionally covered with a vapor-permeable WRB to enable direct side-by-side comparison. Moisture and temperature sensors were installed at three depths (shallow-, mid-, and deep-depth layer) across all conditions. Data collected over a three-and-a-half-month period were analyzed alongside local weather-station records to assess the extent and depth of moisture ingress, the duration of elevated moisture levels above durability and mold-growth thresholds, and the overall effectiveness of WRB protection relative to coated-only assemblies. Results demonstrated that WRB application reduced surface wetting duration by 26 days (from 46 to 20 days above 16% MC) on horizontal shallow surfaces and shortened recovery times, especially on horizontal elements exposed to direct rainfall and ponding, while deeper layers remained largely within safe service ranges. The findings provide evidence-based guidance for best practices in moisture protection of CLT systems under coastal exposure and support ongoing efforts to develop standardized durability protocols for mass timber construction.

Abstract. Cross-laminated timber (CLT) is increasingly adopted for sustainable building construction; however, the energy and durability performance of CLT wall systems strongly depend on insulation configuration and climate. This study compared performance of three CLT wall assemblies including exterior-insulated, split-insulated, and interior-insulated, under two northeastern climate zones of Bristol, Rhode Island (4A) and Syracuse, New York (5A). Using the Combined Heat, Air, and Moisture–Building Envelope Systems (CHAMPS-BES) software, steady-state simulations were conducted to evaluate temperature distribution, heat flux, and thermal conductance through each configuration. Results show that insulation placement considerably alters thermal continuity and the temperature stability of the CLT layer. The split-insulated assembly achieved the lowest thermal conductance (0.14 W/m²·°C) and the most uniform temperature profile in both climates, while the exterior-insulated system performed comparably well in the milder coastal environment. The interior-insulated wall produced the steepest gradients and highest conductance, reflecting lower efficiency. Although overall behavior remained consistent, greater temperature differentials in Syracuse amplified heat-flow magnitude. Findings indicate that insulation strategy should align with regional climate and envelope design intent, as hybrid and exterior-insulated walls enhance thermal performance and potential durability.

Abstract. The performance of concrete is strongly influenced by the type, morphology, and proportion of coarse aggregates used in the concrete mixture. This study examines how combining limestone (LS) with siliceous river gravel (RG) and crushed river gravel (CRG) affects key properties of concrete, focusing on abrasion resistance, coefficient of thermal expansion (CTE), and dynamic modulus of elasticity. Six mixture designs were developed with varying aggregate ratios and were tested in accordance with ASTM and TxDOT standards. Results showed that mixtures containing CRG exhibited higher abrasion resistance, primarily due to greater angularity and surface texture that enhanced aggregate interlock. The CTE of CRG mixtures was 3–10% higher than that of RG mixtures, reflecting stronger mechanical bonding and greater thermal strain transfer. Increasing LS content reduced CTE, improving dimensional stability. Dynamic modulus results indicated that CRG mixtures achieved up to 4% higher stiffness. Overall, aggregate type and morphology significantly influence mechanical and thermal performance. Optimizing aggregate blending, particularly by incorporating angular CRG with LS, can improve stiffness, abrasion resistance, and thermal stability, enhance durability of concrete structure.

Abstract. Construction workers face a severe physiological burden from the synergistic interaction between ergonomic workload and environmental heat stress. However, current risk assessments fail to account for a critical amplifying factor: the additional thermal load imposed by mandatory Personal Protective Equipment (PPE), a research gap this study addresses by synthesizing the available evidence on dual stressors. This study uses a systematic literature review, following Preferred Reporting Items for Systemic Reviews guidelines, to analyze secondary data from peer-reviewed studies that concurrently investigated both heat and ergonomic stressors using objective physiological or performance-based outcomes. The results show that the combined exposure produces a multiplicative strain, causing quantifiable decrements in physical work capacity, including endurance time reductions of up to 35%, and significant productivity losses. Critically, none of the synthesized studies measured the thermal burden of PPE, indicating that current risk models systematically underestimate the total physiological strain on workers. This study benefits the construction industry by establishing that even dual-stressor safety models are insufficient. It provides a directive for professionals and policymakers to shift future research and development from simply documenting the problem to engineering solutions, such as thermally managed PPE, which is essential for creating genuinely safer and more resilient work environments.

Abstract. Delays during the pre-evacuation phase remain a leading cause of fire-related fatalities, yet the relative influence of emotional and social factors on pre-evacuation decision-making is not well understood. Previous studies show that fear heightens physiological readiness, but evidence is limited regarding whether such arousal directly leads to action or is moderated by social cues. This study addresses that gap by comparing fear-induced physiological activation and social influence in predicting evacuation behavior under simulated fire conditions. To model social influence, a trained research team member acted as a confederate, posing as a fellow participant so the real participant believed they were collaborating; during the alarm, the confederate either remained seated or exited. Twenty-two participants completed an autobiographical fear-recall task followed by a mock alarm while physiological responses were recorded using the Empatica E4 wristband. Results showed that fear induction significantly increased arousal, but physiological measures, electrodermal activity, heart rate, and temperature, did not predict evacuation decision. Participants were more likely to evacuate when the confederate left demonstrating that social cues outweighed internal activation. These findings show that emotional readiness alone is insufficient for action and highlight the importance of leadership, communication, and group modeling in improving emergency preparedness and safety training.

Abstract. Monitoring construction workers’ thermo-physiological responses, such as heart rate (HR), core temperature (Tcore), and skin temperature (Tskin), is critical for managing heat stress (HS) under extreme environmental conditions. Continuous physiological monitoring is often impractical on construction sites due to workforce size, task variability, and differences in metabolic rate (MR) and individual characteristics. To address this gap, this study applies a modeling-based approach to simulate and predict hourly Tcore, Tskin, and HR using modified Multi-Node Fiala Thermophysiological (MN-FTM) and Two-Node Thermo-Physiological (TN-TPM) models driven by meteorological and worker-specific inputs. Six simulation scenarios were developed to represent variations in worker attributes and heat exposure conditions. Results show pronounced physiological responses to HS, with peak strain occurring between 11:00 AM and 1:00 PM. HR and Tcore exhibited strong nonlinear relationships across scenarios, while older and heavier workers demonstrated slower recovery during late-afternoon periods, and higher MR was associated with elevated Tcore. The findings highlight the importance of identifying construction workers’ thermophysiological risk factors to support targeted heat mitigation strategies. The presented computational framework can complement continuous field monitoring and be integrated into decision-support, safety-analytics, and training platforms, enhancing practitioners’ capacity to apply simulation-based and data-informed heat-risk management.

Abstract. The growing integration of robotic technologies into construction operations has created new opportunities to enhance safety, precision, and productivity. However, as robots increasingly share workspaces with human collaborators, understanding the cognitive demands imposed on construction individuals becomes critical to ensuring efficient and safe human-robot collaboration (HRC). As such, this study systematically reviews existing body of research on cognitive workload in HRC within the construction domain. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, this study systematically reviews empirical evidence from 32 peer-reviewed studies published across Scopus and Web of Science (WOS) databases. The review examines cognitive workload under three identified key themes: (1) robot control and communication, (2) task sharing and delegation, as well as (3) work and environment conditions. It synthesizes the measurement approaches employed across the studies, including subjective, physiological, and behavioral indicators, identifies research gaps, and proposes future directions. By integrating insights from empirical studies, this review establishes a conceptual foundation for human-centered robot design and provides practical guidance for developing human-centered and cognitively aware collaborative environments.

Abstract. The construction industry continues to face persistently high rates of injuries and fatalities despite decades of safety initiatives, underscoring the need for innovative, data-driven approaches. Recent advances in artificial intelligence, particularly Large Language Models (LLMs), have opened new avenues for enhancing safety through automation, hazard recognition, and intelligent decision support. This study presents a comprehensive scientometric and thematic analysis of 60 peer-reviewed journal papers published between 2020 and 2025 that explore the intersection of LLMs and construction safety. The bibliometric results reveal a sharp growth in publications beginning in 2024, coinciding with the rise of generative AI technologies. Thematic analysis identifies five major research domains: text-based safety analytics, multimodal sensing and real-time monitoring, knowledge-enhanced reasoning, generative AI for data augmentation, and human-AI interaction for safety training and decision support. Key challenges include data scarcity, limited domain-specific reliability, and practical barriers to implementation. Overall, this study maps the intellectual landscape of LLM applications in construction safety, highlighting both current progress and future opportunities for leveraging language-based AI to achieve safer, more resilient construction environments.

Abstract. Despite Wearable sensing devices' (WSDs) capability to enhance real-time safety monitoring on construction jobsites, their adoption remains limited due to cost, privacy concerns, and worker acceptance. Existing studies on WSD acceptance have focused on workers with prior exposure, leaving limited insight into how those without experience assess their usefulness – a key determinant of adoption intention. This gap was addressed through semi-structured interviews with 17 construction fieldworkers (11 trade workers, 6 supervisors) across four project sites in Alabama, USA. Interview data were coded and organized into themes. Findings revealed five application areas: (1) heat-exposure nudges, (2) moving-equipment alerts, (3) electrical-proximity warnings, (4) edge/height reminders, and (5) air-quality notifications. Participants primarily valued alerts for proximity to moving equipment, energized rooms or cables, and early heat warnings. However, they will prefer not to get WSD alerts during less risky tasks or precision tasks that require full concentration. Also, most participants expressed concerns that false alarms would disrupt their workflow. Additionally, six enabling features were identified and thoroughly discussed. Collectively, the findings from this study clarify when WSD alerts will help or hinder work and specific design requirements that can improve acceptance and sustained use. Future research could examine data-sharing preferences and organizational enablers.

Abstract. As the global population ages, falls among older adults have become a significant concern in residential settings. This study investigates how flooring materials, finishes, and visual patterns affect fall risk among elderly individuals, based on a qualitative, literature-based comparative analysis focusing on intrinsic human factors. A comprehensive literature review was conducted to identify flooring features that either increase or reduce fall risk. The analysis is derived from peer-reviewed studies, industry reports, and guidelines from the CDC, WHO, and relevant design organizations. Results show that high-friction surfaces, such as carpets and textured tiles, significantly reduce the likelihood of slips, while glossy or low-friction materials increase fall risk. Additionally, low-contrast patterns help minimize visual confusion and improve depth perception, while smooth floor transitions reduce tripping hazards. These findings inform design and material choices that support aging in place and promote universal design principles. Recommendations for construction professionals and designers include selecting non-glare, high-friction materials and maintaining consistent, low-contrast floor patterns for elderly populations. This research provides practical insights to enhance home safety and guide construction practices that facilitate healthy aging as the global population continues to expand.

Abstract. Roofing is one of the most physically demanding construction trades, yet limited research has quantified how its unique postural demands contribute to work-related musculoskeletal disorders (WMSDs). This study addresses this gap through a field-based comparison of musculoskeletal pain and ergonomic exposure between roofers and non-roofers. A structured questionnaire was administered to 32 construction workers (16 roofers and 16 non-roofers) to assess self-reported pain intensity across body regions and foot zones, along with the duration and frequency of awkward working postures. Descriptive statistics, independent-samples t-tests, and Mann–Whitney U tests were used to examine group differences. Roofers reported significantly higher total body pain, feet pain, and a greater number of painful body zones than non-roofers (p < .05). Toe-specific Pain was notably greater among roofers (p = .003), suggesting excessive forefoot strain caused by frequent kneeling, stooping, and balancing on sloped surfaces. Roofers also experienced greater exposure to awkward postures, despite working comparable hours. These findings underscore the importance of implementing improved ergonomic practices (ergonomic training and task rotation), properly fitted footwear, and advanced insole technologies to monitor and mitigate WMSDs, thereby fostering safer, healthier, and more productive work environments.

Abstract. Construction projects remain among the most hazardous workplaces, with high accident rates resulting from dynamic site conditions, complex scheduling, and limited foresight in hazard prediction. Traditional safety management practices often rely on reactive approaches and fragmented tools, which limit their effectiveness in preventing accidents. Building Information Modeling (BIM) offers new opportunities for integrating safety planning directly into project models. This paper presents a systematic review of recent developments in BIM-based safety management, with an emphasis on hazard prediction, visualization, and risk mitigation. The findings highlight that BIM can support automated hazard identification, enhance safety communication through visual simulations, and improve decision-making in planning and execution phases. Studies demonstrate that BIM integration enables early detection of workspace conflicts, cost–time–safety trade-offs, and compliance with safety codes through automated rule checking. Addressing BIM roles in hazard prediction, the study identifies eight common workflows used in BIM-based safety management. However, challenges remain in terms of interoperability, model standardization, and adoption in real-world project environments. This research provides insights into new trends in technology-driven safety strategies, indicating IoT, computer vision, and digital-twin integrations are transforming BIM from a static model into a dynamic, real-time safety monitor that tracks proximity and behavior.

Abstract. Industry 3.0 and 4.0 have shown the integral use of information technology (IT) in various fields including the construction industry and academia. Recently, artificial intelligence (AI) tools crept in and so the academia embraced it in ways that needed to be productive in the learning efforts. Specifically, ChatGPT made everyone rethink how to engage with the tool positively as plagiarism issues were rife. Therefore, this research examined the use of AI tools among students in the construction safety course with the objective of determining the use of ChatGPT in answering assignments towards student grades. A survey questionnaire was distributed to 50 students about using AI tools such as ChatGPT in assignments. Data gathered were analyzed using SAS on Demand. Results showed that most students were aware of ChatGPT, and they used it in answering various assignments, especially writing assignments. It was recommended that the course assignments be revised to reflect effective use of AI tools for future courses. This research contributed to the overall body of research and knowledge related to AI use in academia and the construction industry.

Abstract. This study describes a newly developed Core Temperature Visualization System (COTVIS) and functionally tests the system, designed to improve safety among construction workers. COTVIS functions as a Peer Awareness Alert System (PAAS), enabling real-time visual alerts based on biometric data, specifically heart rate and core body temperature. Unlike existing wearable technologies that rely solely on individual awareness, COTVIS shifts the responsibility for intervention to the entire crew by displaying alerts visible to nearby workers and within Bluetooth low energy distance to the triggered COTVIS. This approach addresses a critical need where individual risk perception often limits the effectiveness of safety measures. Testing in controlled environments demonstrated that COTVIS can potentially be used as a deterrent to safety-related injuries and illnesses and be an advanced alert system for injured workers. The findings suggest that with further development and field testing, COTVIS could be an integral component of broader site safety strategies.

Abstract. Drones have been increasingly adopted in the construction industry to address labor shortages, enhance productivity, and reduce inefficiencies. This growing adoption has made human-drone interaction inevitable on jobsites, raising concerns about potential safety impacts on human workers and underscoring the need for systematic investigation of relevant human factors. Human-centered experiments are essential for directly examining these factors, where virtual reality (VR) offers a controlled, repeatable, and risk-free environment for simulating high-risk construction scenarios and observing safety-critical behaviors. This study presents the development and validation of a VR environment designed to serve as a realistic and engaging platform for human-drone interaction research in construction. The workflow for VR development is outlined, followed by a pilot study to evaluate the feasibility of the developed VR environment. The evaluation quantitatively examined sense of presence, perceived workload, motion sickness, VR technical reliability, and scenario design relevance. The findings validated the feasibility of the developed VR environment as an experimental platform for advancing human-drone interaction research, which will ultimately support the development of safer and more productive construction practices.