, university programs inconstruction engineering must adapt to meet the current and future job market demands. Theresults will not only identify specific AI competencies deemed vital in the constructionindustry, per the perspectives of the interviewed professionals and experts, but also provideactionable insights into how these skills can be developed and integrated into the industry,enhancing project efficiency and quality. The analysis of semi-structured interviews withindustry experts reveals a labor market that highly values critical reflection, ethical principles,interpersonal and management skills, technical mastery in programming, data analysis,mastery of emerging technologies and construction-related software, English, andcybersecurity
dropout [14]. Numerous studies have corroborated that studentswith a strong sense of belonging are more motivated, which is reflected in their activeparticipation and interaction in class, factors that significantly contribute to their academicsuccess, persistence in their studies, and reduction in the likelihood of dropping out orchanging academic programs [15-17]. Active and collaborative learning techniques fosterreflection at individual, group, and general levels and enhance feedback exchange amongpeers and faculty. These strategies promote critical thinking and problem-solving skills,increasing students' motivation and confidence and strengthening their sense of belonging [8,16].Self-efficacy is an individual's belief in their ability to
real-world problem analysis into science-relatedsubjects using case study approaches. These approaches engage students with practicalissues, fostering sophisticated thinking, promoting reflection, integrating, applying priorknowledge, and developing self-management learning skills. In our university's ConstructionEngineering program, introducing case studies addressing real-world problems in thesisprojects in the first semester of 2017 significantly improved the graduation rate, rising from10% in 2016 to 25.9% by 2022. These enhancements across various performance metricsdemonstrate the efficacy of this methodology. This research employs a non-experimentalmixed-methods approach, utilizing surveys and interviews as primary data collection
following question intended to identify the major challenges and vulnerabilities that low-income communities face post-disaster. The results are presented in box plots, where the boxranges from the first quartile (Q1) to the third quartile (Q3) of the distribution, the median isindicated by a horizontal line, the mean is represented with an “x”, and the whiskers highlight theminimum and maximum values. As evident from the box plots presented in Figure 5, the majorchallenges and vulnerabilities include: (1) lack of housing, yielding a mean of 4.69; (2) lack ofwater and food, reflecting a mean of 4.79; and (3) delayed disaster recovery, yielding a mean of4.45. 5 4.5
engagement, in-class collaborative learningstrategies and post-class comprehensive student feedback in addition to instructor’s observationand reflection were employed in the pilot test – an important step in developing an effectiveeducational case study.IntroductionThe utilization of case studies in educational settings, tracing back over a century, represents asignificant evolution in pedagogical methods. Harrison et al. [1] provide a comprehensiveoverview of this evolution, highlighting the methodological development and flexibility of casestudy research. Their work underscores the adaptability of case studies in providing in-depthunderstanding across various disciplines, particularly social sciences, education, business, law,and health, to
greatly when it is adopted in multiple courses or programs of construction education. [19] Multidisciplinary AECO Students reflected that they could better learn program communication practices and strategies when using the BIM software with actual project data in the industry. [41] Multidisciplinary AECO Interdisciplinary BIM-based joint capstone course in program highway engineering improved students’ collaborations and communication skills with other professionals. [42] Multidisciplinary AECO
negatively worded items tended to havea decreased agreement over that period. While the trends showed the expected movement thatwould reflect an increased sense of belonging to the construction industry, only two showedstatistical difference between pre- and post-internship scores. Item 8, “I am similar to the kind ofpeople who succeed in my career” was statistically significant at the 95% level (t(104) = -1.70, p= .046) and Item 13, “ I do NOT know what I need to do to make a supervisor in my companylike me” was statistically significant at the 90% level (t(104) = 1.49, p = .070). Strongly 7 Agree Agree 6 Somewhat 5 Agree Neither Agree nor 4 Disagree Somewhat 3 Disagree Disagree 2 Strongly Disagree 1
sleep time exists, which has consequences on students’performance. These effects are studied and summarized in the literature section. This is alignedwith the question on the likelihood of changing sleep time in possible, which was above average.Another notable point is the expected working hours for professionals in the construction industry.The reported hours indicate that the educational system – deliberately or unintentionally – shapesthe mindset of students to work 51-60 hours (41%) or 61-70 hours (14%), as reflected in Figure 3.This trend is consistent with the numbers reported for the expected and ideal sleep time in theconstruction industry, as reflected in Table 4. Finally, another point worth mentioning is thestatement about
students had to use questions to prompt the AI to use wordsindicating that this construction project used the Lean methodology or similar ones. Throughoutthe process, it was demonstrated how students executed and acquired skills related to criticalthinking, reflection, problem identification, and solution seeking. Upon completion of theexercises, a survey was conducted on critical thinking and AI, and how they relate or assist. It wasdetermined that during the project, different skills were learned, such as interpreting and analyzinginformation, and using artificial intelligence as a learning tool. The significance of this study liesin the adoption of innovative pedagogical methods that engage students in the subject matter,thereby maximizing
scale, for itemsphrased in a positive tone, a score of 4 instead indicates the lowest level of stress. Thisadjustment ensures that the scale accurately reflects the respondent’s perceived stress levels byaccounting for the positive or negative framing of each statement. Below are the first twoquestions from the section on personal-family related stressors, demonstrating the application ofreverse coding based on the tone of each question: 1) “In the past 30 days, how often have youfelt nervous and stressed?” Given its negative tone, a response of 4 (Very Often) on this questionindicates a high level of stress. 2) “In the past 30 days, how often have you felt confident aboutyour ability to handle your personal problems?” Due to its positive tone
objective. This allowedthe study to observe the natural interaction between the students without putting any pressure onthem to consciously practice the targeted skills.Pre-Summative Assessment QuestionnaireThe pre-summative assessment involved a self-reflection questionnaire utilizing a 5-point Likertscale, ranging from strongly disagree to strongly agree. To avoid bias, for each skill -communication, analytical thinking, decision-making, and leadership - three questions wereprovided to prompt students to self-evaluate their proficiency in these skills prior to the pilotstudy. These questions are detailed in Table 1, offering a comprehensive view of the students'initial perceptions of their skills. Table 1: Students' self-perceived levels
improvement about various infrastructure inequity scenarios, and (ii)students’ interest in working for systemic change to address inequity in resilient infrastructuredevelopments. The demographic questions recorded the participants’ social and educationalbackgrounds. The post-survey included the same Likert scale questions as the pre-survey tocompare the responses and assess knowledge improvements through the module. Additionally,the post-survey included Likert scale questions to reflect students’ feedback on the efficacy ofthe training in improving their understanding of SERI concepts.The pre-and post-survey data were analyzed using both quantitative and qualitative methods. Thestudy utilized the Wilcoxon signed rank test to compare students
. Figure 3. Key Elements of CEM Senior Capstone DevelopmentThrough this course development process, several key characteristics that define the success ofCEM capstone course have been identified, including: • Integration of Multidisciplinary Concepts: The course is structured to address a wide range of concepts and practices, including project planning, scheduling, budgeting, risk management, sustainability, and stakeholder coordination. This interdisciplinary approach reflects the multifaceted nature of construction projects in the real world. • Focus on Practical Application: Students are tasked with applying their acquired knowledge and skills to address complex challenges within the construction industry
is ranked fifth with 10 points. However, this ranking is not reflected in the findings ofthis study, indicating a mismatch between the expected and actual contributions of these twocategories to the overall LEED score. This inconsistency between the points attained by LEED-certified projects and the assigned weight to these categories may stem from inadequateweighting criteria for certain categories, underscoring the need for periodic review of LEEDstandards and incorporation of insights from existing certified projects. This finding is in linewith Da Silva and Ruwanpura (2009) indicating that the Materials and Resources category wasthe lowest credit category in terms of credit achievement.The discrepancies highlighted above indicate that
, and institutionalagendas might affect their applicability.The recommendations outlined in the study reflect the synthesis of the literature review andinsights contributed by both the writers and experts involved in the research process. Therefore,the selection of AI applications, curricular components, and cooperation methodologies may beinfluenced by biases or subjectivity, potentially affecting the comprehensiveness and success ofthe proposed initiatives. The study primarily focuses on urgent recommendations forincorporating AI into construction management education. Nevertheless, the long-term impactsof these interventions on student learning outcomes, industry-academia collaborations, and thebroader construction sector remain unclear
sustainability are integrated into campus initiatives. 3.8 0.7 0.18 Average 3.8 0.43 0.11When respondents were asked about implementing innovative solutions to environmentalchallenges, they perceived the campus as not very innovative in this regard. The average score of3.8, with a variance of 0.16 and a CV of 0.04, reflects agreement on this sentiment. Similarly, theyfeel the same way about incorporating regional priorities regarding sustainability into campusinitiatives.Moreover, regional priorities were determined based on their regional importance, as identified bythe USGBC regional councils and chapters, and were then shared with the
thetargeted area.In LiDAR systems, a laser scanner emits laser beams in various directions, and a sensor detectsthe reflected light. By calculating the time taken for the laser pulses to travel to the target andback, the LiDAR system can accurately ascertain distances to objects. This technology findsextensive applications in diverse fields such as topographic mapping, forestry, autonomousvehicles, geology, urban planning, and archaeology. LiDAR is pivotal in producing highlydetailed and accurate elevation models and three-dimensional representations of landscapes orstructures.Although the technology is sophisticated, only a few smartphone manufacturers, primarily AppleInc., have integrated it into their products. LiDAR scanners are crucial in
defining the problem, while employing a systematicapproach with diverse tactics and heuristics to navigate complexities. Constantly monitoring andreflecting on their progress, they prioritize accuracy over speed, valuing the right solution over ahasty one. They excel in jotting down ideas and creating visual aids like charts and figures,ensuring an organized problem-solving journey. Flexibility is another hallmark, allowing them toconsider various perspectives and keep options open for innovative solutions. Their systematic,reflective, and adaptable approach makes them invaluable assets in any problem-solving endeavor[28]. Which means every engineer has or develops that skill. In fact, during their studies it isfundamental for the students
avariety of digital tools. Their choices reflect their degree of awareness and understanding ofavailable tools, showcasing whether they are acquainted with a diverse range of technologiesrelevant to the construction industry. On the other hand, assessing students' comfort levels inusing a specific digital tool provides insights into their confidence and self-perceivedcompetence. This subjective measure complements the objective evaluation of their toolselection, offering a holistic view of their digital skill awareness, confidence, and readiness toapply their knowledge.These scenarios were crafted to assess participants' knowledge of digital technologies and theirreadiness to apply them in practical construction scenarios. By presenting authentic