Abstract Human–robot collaboration (HRC) refers to the interaction between humans and robots in a shared workspace, combining human adaptability with robotic precision to execute tasks. This study formalizes HRC competencies and identifies the characteristics (training components) of a digital environment for learning HRC in construction through separate focus group discussions with industry and academic participants. A thematic analysis, conducted using inductive coding and validated through interrater reliability, reveals the rationale for prioritizing the top-rated HRC competencies across industry and academia. The top-rated HRC knowledge areas emphasize the importance of integrating HRC to enhance efficiency and safety, as well as adapting it to evolving industry needs. Prioritized skills underscore the importance of aligning knowledge and skills to support effective HRC implementation and enhance human–robot interface and communication proficiencies. The top-rated abilities highlight the significance of foundational, adaptive, and collaborative abilities for safe and effective HRC. The characteristics of a digital environment for learning HRC include robotic technologies, such as drones, three-dimensional (3D) printers, and wearable exoskeletons, which are considered essential for HRC training in construction. Applications such as surveying, bricklaying, and high-precision tasks provide hands-on learning opportunities. Facilitating conditions, including robust network connectivity, reliable power supplies, and modular construction processes, enhance the learning experience. This study contributes to knowledge by formalizing HRC competencies and proposing a digital learning environment that incorporates robotic technologies, practical applications, and facilitating conditions based on the perspectives of industry professionals and academic experts. It also contributes to Activity Theory by advancing its use as a conceptual framework for structuring and interpreting relationships among learners, HRC competencies, stakeholder perspectives, and training components within digital learning environments for HRC in construction.
Abstract This case study examines the integration of structured reflection and peer dialogue into construction education to support experiential learning in courses with cooperative education (co-op) components. The instructional intervention was implemented in two course sections and consisted of five structured reflection activities aligned with course topics, followed by guided peer discussions. Students were asked to connect their co-op experiences to classroom concepts and share insights in a facilitated learning environment. Student feedback and instructor observations were used to assess engagement with the intervention. Observed outcomes suggest that structured reflection supported students in articulating and interpreting their workplace experiences, while peer dialogue expanded learning by exposing students to diverse project contexts and practices. Engagement with both activities appeared to deepen over time as students became more familiar with the reflective process. This case provides a replicable instructional approach for integrating experiential learning into construction and engineering education. The findings offer practical insights for designing reflection-based learning activities that strengthen the connection between academic content and professional practice.
Abstract While humanitarian engineering (HE) programs increasingly emphasize preparing students to engage in social change—from addressing inequitable access to infrastructure and technology in marginalized communities to challenging biases in the workplace and examining norms in engineering organizations that perpetuate inequality—there remains a limited understanding of how these experiences build students’ confidence to engage in social justice activism. This study investigates how HE graduate education influences students’ social justice self-efficacy (SJSE)—their perceived ability to create positive social change across personal, interpersonal, community, and institutional dimensions. Drawing from 88 interviews with 22 students across six HE graduate programs during their first year, we identify a distinct three-phase developmental pattern. Specifically, students often experience (1) a critical exposure phase in fall term coursework that dramatically increased personal SJSE while often decreasing community and institutional dimensions; (2) an integration phase in spring term experiences where students developed more balanced SJSE by identifying specific approaches to social impact while maintaining critical awareness; and (3) a testing phase during summer fieldwork where students confronted the challenges of applying their developing SJSE in real-world contexts. Rather than developing uniformly, students experienced nonlinear, asymmetric growth across SJSE dimensions, often maintaining optimism in one area despite challenges in others. These findings suggest HE education may benefit from providing targeted support during these critical transitions, encouraging specific, more focused engagement in social justice advocacy rather than system-wide transformation, creating opportunities for social justice advocacy practice, and having more of a focus on students’ interpersonal SJSE. This research advances understanding of how HE programs can foster advocates for making engineering more equitable, inclusive, and responsive to marginalized communities’ needs.
Abstract To address structural challenges in international civil engineering graduate education under the Belt and Road Initiative, this study systematically evaluates current training systems and proposes a collaborative model. Employing a quantitative survey design, structured data were collected from 198 participants, including 118 faculty members and 80 international graduate students across 94 Chinese universities. Data were analyzed using exploratory factor analysis. The results reveal a fundamental cognitive gap between educational supply and demand: exploratory factor analysis (EFA) extracted a detailed five-factor structure for teachers—covering goals, competencies, teaching, platforms, and faculty—versus a macrointegrated three-factor structure for students. Quantitatively, notable discrepancies emerged in evaluating goal alignment (91% teacher approval versus 81% student approval for personal development relevance) and high-level competence acquisition, with only 22% of teachers rating academic communication training as highly effective. To bridge these supply–demand mismatches, this study introduces the “one body, two wings, four wheels” framework. Moving beyond broad pedagogical concepts, this study contributes specific, actionable policy pathways: mandating an annual curriculum update to integrate cutting-edge industry practices, institutionalizing cross-national dual-mentor collaborative platforms, and promoting the localized mutual recognition of Chinese Engineering Construction Standards. These targeted interventions provide an evidence-based roadmap for aligning institutional supply with students’ developmental demands.
Abstract Graduate-level building information modeling (BIM) courses often enroll students with widely varying technical skills and professional backgrounds, presenting challenges to educators in implementing equitable and effective instruction. This case study describes the development and implementation of an adaptive instructional method for a graduate BIM course that supports diverse student needs through inclusive teaching strategies grounded in educational best practices. Using Bloom’s taxonomy and evidence-based instructional practices (EBIPs) such as project-based learning, peer collaboration, and scaffolded instruction, the course was structured to provide differentiated support across three learner profiles: experienced professionals, midcareer practitioners, and full-time students. Instructional adaptations were refined throughout the semester based on learner feedback and the aggregate quality of the deidentified course artifacts. The important lessons learned highlight structured flexibility, ongoing formative assessments, and differentiated project-based approaches to support diverse learners. Incorporating an adaptable curriculum into EBIPs may enhance the inclusivity and replicability of BIM. All analyses used deidentified aggregate artifacts produced as part of normal coursework, and no research-specific data collection was undertaken.
Abstract Peer assessment has been widely used in educational settings, particularly in group projects. Despite its known benefits, there is limited evidence on how the design of peer assessment activities influences group dynamics or how it can be used as a mechanism to foster the development of transferable skills. In this study, we investigated the effect of a midproject intervention on group cohesion and overall peer satisfaction. The intervention consisted of an interim peer assessment, where students evaluated each other’s performance using a structured rating scale, followed by a structured conversation to provide feedback. The intervention was implemented in a third-year civil engineering group design project module with a total duration of 15 weeks. We used the standard deviation of end-of-module peer assessment scores as a proxy to measure group cohesion and overall satisfaction with peer performance and compared this metric across groups from four consecutive academic years, including one year with the intervention and three without. Results reveal that the intervention positively impacted group dynamics, and that the feedback mechanism enables students to reflect on and enhance transferable skills, including communication, reliability, enthusiasm and contribution. These findings offer evidence to support the integration of peer assessment as a tool for enhancing group functioning and skills development.
Abstract As climate change and increased development in urban areas increasingly impact communities, universities need to take a larger role in sustainability education, with a focus on green infrastructure solutions. This case study describes a cocurricular service-learning project on a neglected green roof of an academic building. Over three years, students from seven majors at all undergraduate levels voluntarily rehabilitated the green roof, which included removing weeds and replanting the green roof. Four engineering majors were represented in this effort: civil engineering, mechanical engineering, electrical engineering, and computer science. Students investigated plant selection, plant placement, and maintenance through planting 12 different species of sedum and one species of thyme in shady and sunny locations. They observed that thyme did not survive on the roof, and plants in the sunny location had more growth but higher die-off compared to the shady location. During the third year, it was clear that irrigation during the summer months and keeping the roof free of weeds was an important part of maintaining the green roof. Surveys indicated that students enjoyed working on the green roof, felt it was rewarding to make the green roof look better, enjoyed working with all grade levels and majors, and felt an increase in the sense of community in the School of Engineering. The green roof provided an opportunity for students to learn about sustainable green stormwater infrastructure, in addition to providing a greater sense of community and increased utilization of the green roof for other curricular purposes. Cocurricular service-learning opportunities incorporating campus or local community green infrastructure can leverage the benefits of service learning while improving community green spaces for the benefit of all students, staff, and faculty.
Abstract Large language models (LLMs) are rapidly entering civil engineering research and practice, yet little is known about their use in educational contexts. This study reports results from an institutional case study based on a taxonomy-aligned survey of 109 respondents (103 undergraduates, four graduate students, and two faculty) in civil engineering–related programs at a large US university. The survey examined adoption patterns, task functions, verification practices, disclosure norms, and training needs. Undergraduates primarily used LLMs for tutoring and concept explanation (83%) and design ideation (67%), with limited adoption in coding (7%) and technical reasoning (41%). Verification practices were robust: 86% recalculated manually, 52% checked against standards, and only 4% reported nonverification, yielding a median of two methods per user. Ethical orientations favored conditional disclosure for major contributions (53%) and placed primary responsibility for errors on the human user (75%). Demand for formal training was high, especially among those with greater adoption, familiarity, and verification breadth. Results reveal a developmental gap between student practices, which emphasize low-risk learning and ideation, and research and faculty practices, which emphasize technically rigorous applications. The study underscores the need for curricular pathways that guide students from exploratory uses toward responsibly verified technical tasks within similar educational contexts. By linking a civil engineering–specific taxonomy of LLM functions with educational survey data, this work offers institutionally grounded empirical evidence on artificial intelligence (AI) literacy in civil engineering education and highlights directions for curriculum and assessment design.
Abstract Fostering greater interest and engagement in science, technology, engineering, and mathematics (STEM) and preparing students to succeed in industries shaped by rapid technological advancements are key goals of STEM education. Motivation plays a crucial role in student success, shaping engagement with coursework, persistence in demanding career paths, and perceptions of future opportunities. Therefore understanding the drivers of motivation is essential, not only to improve retention and reduce attrition, but also to enhance learning outcomes and overall academic and professional achievement. Although the importance of motivation is widely recognized, limited research has examined the specific factors that hinder STEM students’ ability to sustain it, or the strategies needed to address these barriers. This study addresses this gap by exploring both the enablers and obstacles to motivation and identifying strategies for improvement. A survey of 135 Construction Management (CM) students at Florida International University (FIU) revealed that academic, financial, and social factors strongly influence motivation. Key challenges included the perceived difficulty of career paths, uncertainty about future opportunities, financial stress, poor work–life balance (WLB), and burnout. Based on these findings, the study recommends practical strategies to foster motivation, such as peer mentoring and tutoring, financial aid workshops, career fairs, and time management workshops. These approaches can help students overcome barriers, persist in their studies, and achieve both academic and professional success. The findings provide educational institutions and stakeholders with actionable strategies to strengthen motivation and improve outcomes.
Abstract This article explores the integration of active learning strategies within large, required core courses in undergraduate engineering education, drawing on a case study of a faculty member teaching a Statics and Strength of Materials course to more than 200 students each semester. The focus is placed on pedagogical adaptations, logistical complexities, student participation, and institutional support systems required to make active learning successful on a scale. The study discusses the design and implementation of various techniques such as group hands-on challenges, discipline-specific problems, model demonstration, in-class exercises, and recitation sessions, while critically assessing their impact on student engagement and academic performance. It also highlights barriers including classroom space constraints, time limitations, resistance to change, and the need for ongoing faculty development. Practical recommendations are provided for scaling these approaches and building a sustainable support structure for educators, with the aim of fostering deeper learning and greater student engagement in large engineering courses.
Abstract Virtual site visits have become an essential innovation in construction education, offering safe, repeatable, and flexible alternatives to physical site visits, which are often limited by safety concerns, logistics, and access restrictions. Although immersive technologies and collaborative virtual platforms have expanded these opportunities, the instructional organization of learning content within such environments remains underexplored. This study addresses this gap by comparing the impacts of systematic and nonsystematic learning progressions on students’ knowledge development and collaborative problem-solving during online construction site visits. A virtual learning platform focusing on building mechanical systems was developed, incorporating four learning objectives progressing from declarative to procedural knowledge. Using a between-subject experimental design, undergraduate construction students experienced either a systematic or nonsystematic learning sequence. Results indicated that both learning progressions effectively supported students’ knowledge development within the online construction site visit environment; however, notable differences emerged in higher-order reasoning and collaborative practices. Students in the systematic learning progression condition demonstrated stronger performance on tasks requiring conceptual integration and procedural reasoning. They also exhibited more structured collaborative behaviors, such as referencing two-dimensional (2D) drawings while manipulating three-dimensional (3D) models and collaboratively verifying calculations. These behaviors suggest that systematic sequencing may reduce cognitive load and facilitate schema integration during complex tasks. In contrast, learners in the nonsystematic condition engaged more freely in exploratory navigation but showed less coordinated reasoning and weaker linkage across concepts. Overall, these findings highlight the critical role of instructional sequencing design in virtual construction education and provide insights for designing adaptive scaffolding frameworks in future online site visits.
Abstract The construction industry increasingly relies on data-sensing technologies, such as drones and quadrupedal robots, for inspection, safety management, and decision-making, but effective training lags due to cost, limited expertise, and a lack of immersive, hands-on practice. Immersive embodied interaction (IEI) can increase effective training by coupling bodily movement to virtual actions, but its application in construction is underexplored. Grounded in embodied cognition theory, this study proposes a process for integrating IEI into data-sensing training and experimentally compared enhanced IEI with traditional virtual reality (VR). A total of 41 participants were assigned to 2 conditions: (1) enhanced embodied interaction using a programmed game controller, and (2) traditional VR interaction using standard controllers. Participants completed two VR-based construction tasks simulating real jobsites: a drone inspection and a quadrupedal robodog operation. Outcomes included task completion time, collision frequency, collision and recovery duration, and subjective ratings. Relative to traditional VR, enhanced IEI reduced completion time by 30% in the drone task ( p = 0.036 ) and 37% in the robodog task ( p < 0.001 ). In the drone task, collision frequency increased, but collision duration was significantly shorter ( p = 0.004 ), indicating faster recovery. In the robodog task, collision frequency was statistically unchanged ( p = 0.056 ), and recovery time decreased. Participants reported a higher sense of accomplishment with IEI. These findings suggest that IEI can improve the efficiency and intuitiveness of VR-based training for data-sensing technologies in construction, with potential benefits for learning, skill acquisition, and safety-related behaviors. The study advances knowledge by providing a framework for enhancing data-sensing education in the construction industry.
Abstract Many innovative pedagogical strategies, such as near-peer mentoring, have been developed to address challenges of the first-year college curriculum. Near-peer mentoring involves upper-level students mentoring lower-level students and has been shown to improve student outcomes, such as increased sense of belonging, increased confidence in abilities, and enhanced academic and professional growth. However, many of these programs primarily focus on the mentee and often overlook the mentor. Additionally, these programs can have high barriers to entry and may require extensive administrative support and infrastructure, especially for large classes. This paper presents a curriculum-level near-peer mentoring framework with the goals of (1) enhancing both mentors’ and mentees’ sense of belonging and identities as engineers, and (2) improving the quality of mentees’ semester-long team project solutions, conclusions, and final products. This framework was applied to a large first-year civil and environmental engineering (CEE) course with more than 210 mentees and uses more than 165 mentors primarily from fourth year CEE courses. Mentees and mentors were paired according to similar interests, and each pair met five times during a semester. After each mentoring session, both mentees and mentors completed mirrored surveys about their experiences. Both mentors and mentees somewhat agreed that the near-peer mentoring created a stronger sense of identity as a civil engineer, an increased sense of belonging, and higher quality project solutions, conclusions, and final products. Both groups rated the mentoring experience as beneficial with average self-reported scores of 3.7 out of 5, and both groups believed they helped their counterparts make connections with each other and to the project. Overall, this novel curriculum-level near-peer mentoring framework will allow all students to gain the many benefits of mentoring, and it scales well without additional faculty/teaching assistant (TA) resources.
