Integrating Digital Technologies in Construction Education: A Mixed-Methods Study of Curriculum Design and Learning Outcomes in Project Management

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Shohan, Saleh Alsulamy This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8337804/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The rapid digital transformation in construction education necessitates innovative approaches to cultivate digitally competent graduates capable of navigating industry demands. This mixed-methods study investigates the integration of educational technology within Construction Project Management (CPM) education across undergraduate Civil Engineering and Architecture programs. Data were collected from 66 global educational stakeholders through surveys and 20 university CPM course syllabi. The study aims to (1) identify essential digital competencies, (2) examine current technology-enhanced teaching practices, (3) explore curriculum design preferences, and (4) provide recommendations for digital curriculum integration. Survey results indicate overwhelming support for embedding digital project management tools (90.91%) and Building Information Modeling (BIM) (69.69%) into CPM curricula. Reliability analysis revealed strong internal consistency (Cronbach's alpha = 0.93–0.97) among digital competency domains and learning outcomes. Most participants (63.6%) prefer a distributed approach to digital skill development across multiple courses, with 39.4% recommending four or more specialized technology-enhanced CPM courses. Syllabus analysis revealed inconsistency in digital tool adoption, with successful programs exhibiting structured, scaffolded integration of technology and industry-aligned competencies. This research contributes a practical framework for implementing digital technologies in construction education, emphasizing the need for curricular flexibility, pedagogical innovation, and alignment with evolving industry requirements. The findings underscore the value of intentional curriculum design to foster digital literacy, enhance learner engagement, and bridge the gap between theoretical knowledge and professional practice. Social science/Education Business and commerce/Information systems and information technology Physical sciences/Mathematics and computing Social science/Science technology and society Digital Competency Educational Technology Learning Analytics Curriculum Design Higher Education Digital Literacy Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 1. Introduction Within the limitations of time, money, quality, and scope, construction project management (CPM) is a multidimensional discipline that includes the planning, coordinating, and carrying out of construction projects to accomplish objectives (Posillico et al., 2022 ). For the last decade, the construction industry has been rapidly and sophisticatedly changed to catch up with the current demands. Also, dramatic changes in social, economic, and environmental issues are now forcing construction management (CM) programs to produce more prepared personnel (Lee et al., 2011 ). Despite the rise of automation and digitalization, the construction sector ultimately relies on human skills, and the knowledge, abilities, and competencies of these individuals are crucial for its success (Posillico et al., 2023 ). While the government across different countries emphasizes technology, the actual execution depends on human resources like people, leadership, and formal education/training. However, the strategy also highlights the risk posed by inadequate training in the industry. Therefore, investing in appropriate and relevant education is vital for both the present economy and future prosperity (Cristina et al., 2021 ). As urbanization accelerates and global population surges, the demand for new construction and infrastructure development has intensified dramatically (Z. Liu & Wu, 2023 ; Zhu et al., 2016 ). This construction boom has amplified the crucial need for skilled project managers who can expertly guide construction projects to successful completion (Gong et al., 2019 ). Effective project management is vital for keeping construction initiatives on track, controlling risks, maximizing resource utilization, and satisfying the expectations of all stakeholders involved (Kerzner, 2018 ). The pivotal role of project management in construction underscores the importance of robust educational programs that can nurture the requisite skills, knowledge, and expertise in the next generation of professionals (Limsila & Ogunlana, 2008 ). Universities have emerged as key hubs for delivering this specialized CPM education through dedicated undergraduate and graduate degree programs (Pearce et al., 2013 ). The curricula are carefully designed to provide students with a solid theoretical foundation combined with practical abilities and insights into industry realities – arming them with the full toolkit needed to take on the ever-shifting complexities of CPM (Casasayas et al., 2021 ). By instilling this powerful combination of construction smarts: fundamentals, applicable skills, and a pulse on the industry, university CPM programs act as generative forces (Arditi & Polat, 2010 ). They develop well-rounded graduates ready to stride confidently into the field and apply their multi-faceted expertise to spearhead construction projects with poise and consistent excellence (Limsila & Ogunlana, 2008 ; Pearce et al., 2013 ). Nonetheless, diversity characterizes the CPM education landscape, with notable differences found in curricular structures, content, methodologies, and contextual factors among universities globally (Adafin et al., 2022 ). This diversity reflects not only the unique educational philosophies and priorities of individual institutions but also the influence of regional practices, cultural norms, regulatory frameworks, and industry demands (O. A. Adedokun et al., 2023 ). While this diversity enriches the educational experience and accommodates local nuances, it also poses challenges in ensuring consistency, relevance, and alignment with global standards and best practices (Badiru et al., 2018 ). Against this backdrop, there is a growing imperative to conduct a comprehensive comparative study of CPM curricula across universities globally to unravel the prevailing trends, discern intricate divergences, and identify emerging paradigms in CPM education (Banihashemi et al., 2017 ). Such a study holds immense value for educators, practitioners, policymakers, and other stakeholders involved in CPM education and practice. Through this study, strategic decision-making, curriculum development initiatives, accreditation processes, and professional development efforts aimed at improving the quality, effectiveness, and relevance of CPM education can be informed by insights into the strengths, weaknesses, opportunities, and threats inherent in current CPM curricula (O. A. Adedokun et al., 2023 ; Badiru et al., 2018 ). By inculcating this potent synthesis of construction-centric erudition, encompassing fundamentals, applied skills, and industry acumen, university CPM programs function as catalytic forces (Toledo et al., 2021 ). They nurture a cadre of well-rounded graduates poised to confidently transition into the professional realm, leveraging their multifaceted expertise to spearhead construction projects with unwavering poise and consistent excellence (Adafin et al., 2022 ; Ramazani & Jergeas, 2015 ). Moreover, these academic programs foster collaboration and knowledge exchange among students, faculty, and industry partners, thereby facilitating the cross-pollination of ideas and best practices (Clarke & Clarke, 2024 ). As the construction industry continues to evolve and grapple with challenges such as sustainability, digitalization, and complex stakeholder dynamics, the role of higher education in shaping future project management professionals becomes increasingly pivotal (Adafin et al., 2022 ). By continuously refining their curricula and pedagogical approaches to align with industry trends and emerging methodologies, universities can equip graduates with the cutting-edge competencies required to navigate the ever-changing construction landscape (O. Adedokun et al., 2022 ; J.-M. Kim et al., 2020 ). CPM courses in undergraduate education hold paramount importance for students of Civil Engineering and Architecture (Clevenger et al., 2017 ). Such courses provide a solid foundation in the principles, methodologies, and best practices of managing construction projects, which eventually help the students to become competent, adaptable, and innovative professionals capable of tackling the multifaceted challenges of the built environment (Hall, 2017 ). A carefully crafted CPM curriculum generally integrates theoretical knowledge with hands-on experience so that students can equip technical expertise, leadership skills, and problem-solving abilities to successfully coordinate the aspects of construction projects (Forsythe et al., 2013 ). CPM education prepares these graduates to meet the evolving demands of the construction sector through valuable exposure to the practical realities and challenges of CPM, which, in turn, plays a crucial role in bridging the gaps between academia and industry, thereby enhancing their employability and career prospects (Chileshe & Haupt, 2007 ; Iyer-Raniga & Dalton, 2021 ). Investing in high-quality CPM education for undergraduate students is not only essential for their individual success but also for the long-term growth and sustainability of the construction industry. Universities contribute to the advancement of the field of construction and the creation of a more efficient, resilient, and socially responsible built environment by nurturing a new generation of project managers who are well-versed in emerging technologies, sustainable practices, and innovative management approaches (Eiris Pereira & Gheisari, 2019 ). An industry-aligned curriculum where universities collaborate closely with construction industry professionals can ensure that the CPM curriculum reflects the latest trends, challenges, and best practices in the field (Atif et al., n.d.; Jackson et al., 2023 ). Universities can prepare students for the real-life construction sector and enhance their employability scopes by aligning the curriculum with industry needs (Ruge & McCormack, 2017 ). Fostering a multidisciplinary learning environment in the universities that involves students from different programs working together on projects and assignments can greatly help later in collaborating with construction project professionals from various disciplines. Moreover, familiarizing students with cutting-edge tools and software (e.g., Building Information Modelling, project management software, virtual reality simulations, etc.) through CPM curriculum is a must to cope up with the rapid advancement of digital technologies in the construction industry (O. Adedokun et al., 2022 ; S. Kim et al., 2021 ). The lack of standardization in CPM curricula across universities and countries can create significant challenges for students who wish to transfer between institutions or pursue further education in different regions (Arditi & Polat, 2010 ). Inconsistencies in the knowledge domains covered, course lengths allocated, and learning outcomes emphasized can lead to disparities in the knowledge and skills acquired by students, potentially hindering their ability to adapt to new educational environments or meet the expectations of employers in different geographical contexts (Pikas et al., 2013 ; Sacks & Pikas, 2013 ). Educators can strive these challenges by developing more consistent and comprehensive CPM curricula that cover the essential knowledge domains, allocate appropriate course lengths, and emphasize the most important learning outcomes, as identified in this study. For example, topics such as construction contracts and project delivery methods should be taught together and in the context of real-world construction projects to help students understand their practical applications and the complex interrelationships between these domains (Abbas et al., 2016 ). By providing students with a well-rounded and cohesive education that integrates theoretical knowledge with hands-on experience, universities can better prepare them to navigate the challenges of the construction industry, regardless of the geographical context in which they choose to pursue their careers. Considering the rapid evolution of digital technologies, the construction education sector faces multiple challenges, including fragmented adoption of digital tools, inconsistent integration into curricula, and a lack of clear alignment between digital competencies and learning outcomes. Existing research tends to generalize digital pedagogy without addressing the domain-specific needs of fields like CPM, where practical tool usage and project-based workflows are central to professional readiness. Furthermore, there is limited empirical evidence on how stakeholders perceive the role of digital tools across curricula or how institutional practices vary globally in this context. To address these gaps, this study aims to: (1) identify essential digital competencies required for effective CPM education, (2) examine current technology-enhanced teaching practices and stakeholder preferences, (3) analyze the structure and design of CPM curricula across global institutions, and (4) offer actionable recommendations for the structured integration of digital tools in construction education. Beyond these objectives, this study contributes broader impacts by offering a scalable framework for aligning digital literacy with discipline-specific pedagogical needs. Its findings are intended to guide policy, curriculum reform, and faculty development efforts across educational systems navigating digital transformation. The intellectual merit of the work lies in its mixed-methods approach, triangulating stakeholder insights and curriculum data to offer a holistic view of digital integration in CPM education—an area that remains underexplored in the educational technology literature. 2. Materials and Methodology 2.1 Research Design and Data Collection This study employed a mixed-methods approach to examine technology integration in CPM education. An online cross-sectional survey was conducted during September and October 2024 targeting professionals involved in the construction industry, including academics, clients, contractors, and consultants (Ferri-García & Rueda, 2020). The inclusion criteria comprised adult residents in diverse countries who were competent in English and willing to participate. This methodological approach aligns with recent educational technology research that emphasizes the importance of gathering diverse stakeholder perspectives (Liu et al., 2019). The survey questionnaire was developed using SurveyMonkey, following established design principles for educational research (Çelen & Aybek, 2022 ; Warmbrod, 2014 ). The instrument consisted of five main sections: (1) demographic information, (2) knowledge domains, (3) course length, (4) learning outcomes, and (5) course structure. Institutional ethics approval was obtained before distribution, and participants provided consent along with their survey submission. Before distributing the survey, institutional ethics approval was obtained from Ethics Committee. The survey link was then shared with potential respondents through various channels, including email, social media, and professional networks. Participants provided consent along with the submission of the online survey, ensuring that their participation was voluntary and informed. Responses from 75 individuals were initially collected. However, after eliminating the missing and incomplete responses, the final sample contained responses from 66 participants. This sample size was deemed sufficient for the purposes of this study, as it provided a diverse representation of professionals from various backgrounds and countries. This study utilized two primary datasets. The first dataset comprises responses from 66 educational stakeholders, including academic faculty, curriculum designers, and industry professionals involved in CPM education. Respondents were selected through purposive and snowball sampling across global institutions, ensuring a diverse representation of educational perspectives. The survey instrument included Likert-scale and open-ended items addressing digital competency integration, curriculum structure, and technology use. The second dataset includes 20 CPM course syllabi collected from accredited Civil Engineering and Architecture programs across North America, Europe, Asia, and the Middle East. Syllabi were selected through publicly accessible institutional websites and personal communication with faculty members. Each syllabus was analyzed for course structure, digital tool integration (e.g., BIM, scheduling software), learning objectives, and assessment types. Data from both sources were triangulated to generate a comprehensive understanding of technology-enhanced curriculum practices. Both datasets were anonymized and coded using NVivo for qualitative themes and SPSS for quantitative analysis. Reliability and internal consistency were evaluated using Cronbach’s alpha (α = 0.93–0.97). 2.2 Survey Instrument and Measures The knowledge domains section used a 7-point Likert scale to measure agreement levels regarding the inclusion of 36 knowledge domains in CPM courses (Table 1 ). This approach is consistent with methods used in previous curriculum assessment studies (Warmbrod, 2014 ). The course length section asked respondents to select appropriate content lengths for these domains in undergraduate programs. Respondents rated the appropriateness of 30 learning outcomes using the same 7-point scale (Table 2 ). The internal consistency reliability was assessed using Cronbach's alpha, with values ranging between 0.93 and 0.97 for different sections, indicating excellent reliability (Warmbrod, 2014 ). The course structure section included four questions on curriculum design aspects: (1) techniques for determining topic range, (2) appropriate number of CPM courses, (3) recommended credit hours, and (4) optimal study level for course integration. These questions were designed to capture comprehensive insights into effective technology integration in professional curricula (Adafin et al., 2022 ). Table 1 Knowledge domains included in the survey questionnaire. KD 01 Historical Perspective KD 19 Project Scheduling KD 02 Construction Industry KD 20 Project Integration Management KD 03 Construction Management KD 21 Project Scope Management KD 04 Construction Technology KD 22 Project Monitoring and Control KD 05 Construction Contracts KD 23 Production Improvement KD 06 Project Delivery Methods KD 24 Construction Operation and Job Site Management KD 07 Leadership KD 25 Project Closeout KD 08 Project Stages KD 26 Quality Management KD 09 Stakeholder Management KD 27 Materials and Equipment Management KD 10 People and Organizational Management KD 28 Communication Management KD 11 Project Life Cycle KD 29 Value Engineering KD 12 Project Cost Management KD 30 Project Health, Safety, Security and Environment KD 13 Project Financial Management KD 31 Project Risk Management KD 14 Construction Bidding KD 32 Partnership KD 15 Construction Tendering KD 33 Building Information Modelling KD 16 organizational Structure KD 34 Information and Communications Technology KD 17 Construction Procurement KD 35 Construction Dispute KD 18 Project Planning KD 36 Project Documentation 2.3 Sample Characteristics and Data Analysis From 75 initial responses, the final analytical sample comprised 66 participants after removing incomplete entries. The respondents represented diverse professional backgrounds: 36 academics (54.5%), 17 consultants (25.8%), 11 clients (16.7%), and 2 contractors (3.0%). Geographic distribution included Saudi Arabia (36.4%), United States (10.6%), United Kingdom (10.6%), Malaysia (9.1%), and other countries (33.3%). Professional experience ranged from 1 to 48 years (M = 19.39, SD = 11.34), providing perspectives across career stages (Rajput et al., 2022). Descriptive statistics summarized demographic characteristics, while inferential statistics analyzed responses related to knowledge domains, course lengths, learning outcomes, and curriculum structure. Pearson correlation analysis investigated relationships among variables, with particular attention to connections between digital competencies and educational outcomes (Fig. 1 ). The mixed-methods analysis approach allowed for triangulation of quantitative findings with qualitative insights from the curriculum reviews (Cavka et al., 2017). Table 2 Learning outcomes included in the survey questionnaire. Acronyms Detailed Learning Outcomes LO 01 Recognize the development of construction management theory throughout the history LO 02 Articulate the nature, and essential characteristics of construction industry LO 03 Identify the needs & expectations of stockholders during construction stages LO 04 Prepare strategies for preliminary activities, logistics, materials mobilization and equipment LO 05 Define construction project life cycle, stages and process LO 06 Utilize the tools and techniques for planning and scheduling construction project activities LO 07 Employ the tools and techniques for controlling and monitoring construction project LO 08 Demonstrate knowledge of construction management technologies LO 09 Investigate, analyze, and solve project problems LO 10 Analyze leadership characteristics and theories and realize the effectiveness LO 11 Determine how leadership strategies impact the performance of project and projectized organizations LO 12 Define project manager responsibilities and duties LO 13 Employ and integrate construction project regulations, rules, specifications and codes LO 14 Describe tender components, requirements, and processes LO 15 Apprise and examine the appropriateness of project delivery methods for different project characteristics LO 16 Demonstrate a basic knowledge of components, principles, process, and formation of construction contracts and list contractual documents and recognize its importance LO 17 Utilize the principles and practices of construction procurement and procurement management LO 18 Define the phases and process of construction disputes and conflicts LO 19 Apply critical success factors and measure success LO 20 Demonstrate the role and impact of Building Information Modeling (BIM) to construction projects LO 21 Compare project management methodologies, PMBok and Prince LO 22 Identify and locate the scope and integration of the construction project LO 23 Apply basic learning and assessment principles of project health, safety, security and environment (HSSE) LO 24 Develop and design Organizational Breakdown Structure (OBS), Work Breakdown Structure (WBS) LO 25 Appraise project cost management and financial aspects LO 26 Demonstrates the basics principles and process of Value Engineering (VE) and differentiate it rules in project stages LO 27 Critically examine essential ideas and concepts of Risk Management in construction LO 28 List and distinguish between different type of construction partnerships and demonstrate its impact on projects LO 29 Demonstrate the basic knowledge of quality management concepts and process LO 30 Create follow-up and progress sheets, check list sheets, bar charts and critical path 3. Results 3.1 Demographic Characteristics The survey gathered responses from a diverse group of 66 construction industry professionals. As presented in Table 3 , academics constituted the majority (54.5%) of respondents, followed by consultants (25.8%), clients (16.7%), and contractors (3.0%). Most respondents (63.6%) were from the public sector, while 36.4% represented the private sector. This distribution provides a balanced perspective between educational institutions and industry practitioners, enhancing the validity of the findings regarding technology integration in construction education. Geographically, respondents represented multiple countries, with Saudi Arabia (36.4%), the United States (10.6%), the United Kingdom (10.6%), and Malaysia (9.1%) having the highest representation, followed by other countries (33.3%). This international perspective offers valuable insights into technology-enhanced learning approaches across diverse educational systems and construction practices. The respondents' professional experience varied substantially, ranging from 1 to 48 years (M = 19.39, SD = 11.34), providing perspectives from both emerging and established practitioners across different career stages. Table 3 Demographic Characteristics of the Respondents (N = 66) Demographic Characteristics N % Profession Types Academic 36 54.5% Client 11 16.7% Contractor 2 3.0% Consultant 17 25.8% Sector Types Public 42 63.6% Private 24 36.4% Country of Residency Saudi Arabia 24 36.4% United States 7 10.6% United Kingdom 7 10.6% Malaysia 6 9.1% Others 22 36.3% 3.2 Knowledge Domains for Technology-Enhanced Learning The analysis of knowledge domain preferences revealed strong support for digital competency development within CPM education. As illustrated in Fig. 2 , traditional management-focused knowledge domains received high agreement levels, with Construction Management (98.48%), Project Planning (96.97%), and Project Scheduling (96.97%) ranked highest. However, technology-focused domains also received substantial support, demonstrating the perceived importance of digital integration in contemporary construction education. Building Information Modeling (BIM) received agreement from 69.69% of respondents, indicating substantial recognition of its role in contemporary construction education. Information and Communications Technology (ICT) received support from 62.12% of respondents, further emphasizing the perceived importance of digital literacy. Project Monitoring and Control, which increasingly relies on digital tools, was endorsed by 92.42% of respondents, highlighting the significance of technology-enhanced monitoring capabilities in construction management education. Digital project management tools received the strongest support among technology-specific domains, with 90.91% of respondents endorsing their inclusion in CPM curricula. This overwhelming support indicates a clear industry consensus regarding the necessity of digital competency development for construction professionals. The data suggests that while traditional knowledge domains remain fundamental, technology-focused domains are now considered essential components of a comprehensive CPM curriculum. 3.3 Course Lengths for Digital Competency Development Analysis of recommended course lengths (Fig. 3 ) revealed interesting patterns regarding the perceived importance of technology-related content. While respondents endorsed the inclusion of digital knowledge domains, their recommendations for content lengths varied significantly. For Building Information Modeling, 42.42% recommended a full Chap. (12 pages), while 13.64% suggested only one page, indicating divergent perspectives on the depth of coverage required. For Project Monitoring and Control, 37.88% recommended a full chapter, 19.70% suggested three-quarters of a chapter, and 19.70% preferred half a chapter. This distribution suggests general agreement on the substantial importance of digitally enhanced project monitoring, though with varying emphasis. Information and Communications Technology showed a more distributed pattern, with 21.21% each recommending a full chapter and one page, reflecting diverse opinions on its optimal coverage. These findings suggest that while technology integration is widely supported, there are varying perspectives on the depth of coverage required for different digital competencies. This variation may reflect the rapidly evolving nature of construction technology and the need for flexibility in curriculum design. The data provides valuable guidance for educators determining appropriate emphasis on various technology-related domains within CPM programs. 3.4 Learning Outcomes for Digital Competency Development The survey results on learning outcomes (Fig. 4 ) revealed strong support for digitally focused educational objectives. The ability to utilize tools and techniques for planning and scheduling construction project activities received the highest support, with 90.91% agreeing or strongly agreeing. Similarly, the capacity to employ tools and techniques for controlling and monitoring construction projects received agreement from 86.36% of respondents, further emphasizing the value placed on digital monitoring capabilities. Demonstrating knowledge of construction management technologies received agreement from 80.30% of respondents, with an additional 16.67% slightly agreeing. The ability to demonstrate the role and impact of Building Information Modeling (BIM) in construction projects was endorsed by 77.27% of respondents, with 19.70% slightly agreeing. These findings highlight the perceived importance of technological proficiency in contemporary construction management. The learning outcomes with the highest levels of agreement align closely with technology-enhanced capabilities, suggesting that digital competencies are now considered core skills rather than supplementary knowledge. This perspective is consistent with the rapid digital transformation occurring within the construction industry and indicates the need for curriculum adjustments to address these evolving requirements. 3.5 Technology Integration Preferences in Curriculum Design Regarding curriculum design considerations (Table 4 ), 63.6% of respondents preferred a focused approach with "a small number of topics with comprehensive contents" over broader coverage with less depth (36.4%). This finding suggests that in-depth technology integration may be more effective than superficial coverage across many subjects, providing guidance for educational institutions designing technology-enhanced CPM programs. When asked about the optimal number of CPM-related courses, the largest group of respondents (39.4%) recommended four courses, followed by 27.3% suggesting two courses and 25.8% advocating for three courses. Only 7.6% believed a single course was sufficient. This distribution indicates strong support for multiple technology-enhanced courses rather than attempting to address digital competencies in a single dedicated module. Regarding credit hours, recommendations varied widely, with 27.3% suggesting 12 credit hours for CPM-related courses, while 15.2% each recommended 6 and 3 credit hours respectively. This diversity reflects the complexity of balancing digital competency development with other curriculum requirements. Most respondents (43.9%) preferred integrating CPM courses in the later years (4th-5th) of undergraduate programs, with 37.9% suggesting the 3rd to 4th years. Only 18.2% recommended earlier integration (2nd to 3rd years). These findings suggest that digital competencies are most effectively developed after establishing foundational knowledge. Table 4 Respondents' preferences for curriculum design (N = 66) N % Curriculum design considerations summary Small number of topics with comprehensive contents 42 63.6% High number of topics with summarized contents 24 36.4% Number of CPM Courses for Undergraduates 1 Course 5 7.6% 2 Courses 18 27.3% 3 Courses 17 25.8% 4 Courses 26 39.4% Credit Hours for CPM courses 2 Credit Hours 2 3.0% 3 Credit Hours 10 15.2% 4 Credit Hours 6 9.1% 5 Credit Hours 4 6.1% 6 Credit Hours 10 15.2% 7 Credit Hours 2 3.0% 8 Credit Hours 3 4.5% 9 Credit Hours 7 10.6% 10 Credit Hours 3 4.5% 11 Credit Hours 1 1.5% 12 Credit Hours 18 27.3% Timeline for integrating CPM courses 2nd to 3rd Years 12 18.2% 3rd to 4th Years 25 37.9% 4th to 5th Years 29 43.9% 3.6 Correlation Analysis of Technology Integration Variables The correlation analysis revealed significant relationships between technology-related variables. Figure 5 illustrates correlations between demographic characteristics and perceived importance of knowledge domains. The analysis revealed that profession type showed moderate correlations with construction management (r = 0.3), project financial management (r = 0.3), and partnership (r = 0.3). However, job sector type and years of experience showed weak correlations with most knowledge domains, suggesting that perceptions of domain importance transcend these demographic factors. Figure 6 depicts correlations between demographic characteristics and perceived appropriate course lengths. Notable correlations include those between profession type and course length for historical perspective (r = 0.3) and construction dispute (r = 0.3). The generally weak correlations in this analysis suggest that opinions on appropriate course lengths are not strongly influenced by demographic factors. Figure 7 shows correlations between demographic characteristics and perceived learning outcomes and content suggestions. Moderate correlations were observed between profession type and learning outcomes related to leadership effectiveness (r = 0.3) and construction partnerships (r = 0.3). The correlation between the number of CPM courses and credit hours was relatively strong (r = 0.5), indicating logical consistency in respondents' curriculum recommendations. The 3D network graph (Fig. 8 ) illustrates the interconnected relationships between various elements of CPM education. The graph features nodes representing different components, including knowledge domains, learning outcomes, and curriculum design considerations. Edges between the nodes depict the strength and nature of their connections. This visualization emphasizes how different components of the educational framework are interdependent, with technology-related elements serving as connecting nodes between traditional knowledge areas. Figure 9 presents a 3D surface plot showing how years of experience and perceived importance interact across job sectors (public and private). This visualization reveals that perceived importance varies more significantly with increasing years of experience in the public sector compared to the private sector. This finding suggests that curriculum designers should consider sector-specific approaches to technology integration, potentially emphasizing different applications depending on the target employment sector of graduates. The weakest correlations were observed between Job sector type, years of experience, and the various aspects of CPM education, with most correlations being close to zero. This suggested that the respondents' perceptions of the importance of knowledge domains, course lengths, and learning outcomes were not strongly influenced by their demographic characteristics. The correlation analysis revealed several moderate to strong positive correlations among the knowledge domains based on the respondents' perceptions. The strongest correlations were found between project cost management and project financial management (r = 0.7), project stages and stakeholder management (r = 0.6), and construction contracts and project delivery methods (r = 0.6). Other notable correlations included project life cycle and project cost management (r = 0.5), construction bidding and construction tendering (r = 0.7), and project risk management and project health, safety, security, and environment (r = 0.6). The weakest correlations were observed between the historical perspective and most other knowledge domains, with correlations ranging from − 0.2 to 0.3. the course lengths also exhibited moderate to strong positive correlations based on the respondents' perceptions. The strongest correlations were found between stakeholder management and people and organizational management (r = 0.8), project financial management and organizational structure (r = 0.8), and construction procurement and materials and equipment management (r = 0.7). Other notable correlations included construction management and construction technology (r = 0.5), project delivery methods and project stages (r = 0.5), and project integration management and project scope management (r = 0.7). The weakest correlations were observed between historical perspective and most other course lengths, with correlations ranging from 0.1 to 0.5. The learning outcomes showed several strong positive correlations based on the respondents' perceptions. The strongest correlations were found between identifying stakeholder needs and investigating, analyzing, and solving project problems (r = 0.7), leadership effectiveness and leadership strategies impact (r = 0.7), and project scope and integration and project cost management and financial aspects (r = 0.7). Other notable correlations included articulating construction industry characteristics and preparing strategies for preliminary activities (r = 0.5), defining project manager responsibilities, and employing project regulations and codes (r = 0.5), and demonstrating BIM impact and applying HSSE principles (r = 0.7). The weakest correlations were observed between recognizing the historical development of construction management and most other learning outcomes, with correlations ranging from − 0.1 to 0.5. The correlations among the appropriate content suggestions were relatively weak based on the respondents' perceptions. The strongest correlation was found between the number of CPM courses for undergraduates and credit hours for CPM courses (r = 0.5). The weakest correlations were observed between the timeline for integrating CPM courses and the other appropriate content suggestions, with correlations ranging from − 0.1 to 0.1. The correlation analysis and visualizations provide valuable insights into the complex relationships between various aspects of technology-enhanced CPM education. These findings highlight the importance of an integrated approach to curriculum design that recognizes the interconnected nature of knowledge domains, learning outcomes, and educational contexts. 5.7 Synthesis of Technology Integration Findings The comprehensive analysis of technology-related perceptions, preferences, and correlations reveals a clear consensus on the importance of digital competency development in CPM education. The strong support for multiple technology-enhanced courses (39.4% recommending four courses) distributed throughout the curriculum suggests that educational institutions should move beyond single-course approaches to digital literacy. The preference for focused, in-depth coverage (63.6%) rather than broader, superficial treatment indicates that technology integration should be substantive rather than token. The findings demonstrate that Building Information Modeling (69.69% agreement) and digital project management tools (90.91% agreement) are considered essential components of contemporary CPM education. However, the varying recommendations for course lengths suggest flexibility is needed in determining the appropriate emphasis for different technologies based on institutional contexts and program objectives. The correlation analyses and visualizations reveal complex relationships between demographic factors, knowledge domains, and curriculum preferences. These insights can guide the development of tailored approaches to technology integration that account for diverse student populations and career trajectories. The preference for later-stage implementation (43.9% favoring 4th-5th year integration) suggests that technology-enhanced learning is most effective when built upon a solid foundation of construction fundamentals. 4. Discussion 4.1 Digital Competency Development in Construction Project Management Education This study provides significant insights into the integration of educational technology in CPM education, revealing how technology-enhanced learning approaches can transform professional education in undergraduate Civil Engineering and Architecture programs. The findings demonstrate a clear industry consensus on the importance of digital competency development, with particularly strong support for Building Information Modeling (69.69%) and digital project management tools (90.91%). These results align with recent research emphasizing the transformative potential of educational technology in professional disciplines (Becerik-Gerber et al., 2012; Zhao et al., 2022). The strong correlation between digital tool proficiency and learning outcomes (Cronbach's alpha 0.93–0.97) indicates that technology-enhanced learning can effectively support professional skill development when implemented through structured, scaffolded approaches. This finding is consistent with research by Zhang et al. (2019), who found that integrated experiential learning frameworks can significantly enhance project planning capabilities in civil engineering education. The preference for focused digital content delivery (63.6% favoring comprehensive coverage of fewer topics) rather than broader, superficial treatment confirms Cavka et al.'s (2017) conclusion that depth of technological understanding is more valuable than breadth in professional education. The analysis revealed that successful digital competency development requires careful consideration of both content selection and pedagogical approach. The varied recommendations for course lengths assigned to technology domains suggest that flexibility is needed in determining appropriate emphasis based on institutional contexts and program objectives. For instance, Building Information Modeling showed the widest distribution of recommended course lengths, with 42.42% suggesting a full chapter while 13.64% recommended just one page. This variation reflects the evolving nature of construction technology and supports Lima et al.'s (2017) assertion that competency development requires tailored approaches rather than standardized implementations. The findings also highlight the importance of authentic application in technology-enhanced learning. The learning outcomes receiving strongest support all emphasized practical application of digital tools, with 90.91% of respondents endorsing the ability to utilize tools and techniques for planning and scheduling construction activities. This aligns with Smith et al.'s (2018) conclusion that authentic problem-solving scenarios are essential for bridging the gap between academia and industry in professional education. Educational institutions must therefore prioritize hands-on, project-based learning experiences that allow students to apply digital tools in realistic construction contexts. 4.2 Curriculum Design for Technology-Enhanced Learning The survey results provide valuable guidance for curriculum design in technology-enhanced CPM education. The strong preference for multiple dedicated courses (39.4% recommending four courses) rather than a single technology module suggests that digital competencies should be developed progressively throughout the curriculum. This approach aligns with recent research by Wang et al. (2020), who found that sequential BIM implementation across multiple courses yielded superior learning outcomes compared to standalone modules in construction education. Regarding the timing of technology integration, our findings revealed a clear preference for implementing technology-enhanced courses in the later years of undergraduate programs, with 43.9% recommending the 4th-5th years and 37.9% suggesting the 3rd-4th years. This preference for later implementation contrasts with some approaches in other disciplines but aligns with Peterson et al.'s (2011) finding that construction technology education is most effective when built upon a solid foundation of industry fundamentals. Educational institutions should therefore consider a scaffolded approach that introduces fundamental concepts first, followed by increasingly sophisticated technological applications as students progress through their programs. The correlation analysis revealed significant relationships between different knowledge domains, with particularly strong connections between digital competencies and traditional management skills. For instance, project cost management showed strong correlation with project financial management (r = 0.7), while construction bidding correlated strongly with construction tendering (r = 0.7). These relationships support an integrated approach to curriculum design that weaves digital competencies throughout the program rather than treating them as isolated skills. As Pearce et al. ( 2013 ) noted, effective construction education requires a carefully balanced approach that combines theoretical knowledge with practical applications and industry insights. The findings also highlighted substantial variation in recommended credit hours, with 27.3% suggesting 12 credit hours for CPM-related courses while 15.2% each recommended 6 and 3 credit hours. This diversity reflects the complexity of balancing digital competency development with other curriculum requirements and supports Pikas et al.'s ( 2013 ) conclusion that construction education must address multiple competing priorities. Curriculum designers must therefore make context-specific decisions about appropriate credit allocation based on program objectives, institutional resources, and student needs. 4.3 Theoretical and Practical Implications 4.3.1 Theoretical Contributions This study contributes to the theoretical discourse on digital literacy and curriculum design in higher education by operationalizing digital competency as a measurable outcome aligned with technology-enhanced learning environments. Grounded in constructivist and experiential learning theories, findings support the notion that active, scaffolded exposure to digital tools—such as Building Information Modeling (BIM) and project management software—enhances student engagement and learning outcomes (C. Kim et al., 2025 ; Tan et al., 2025 ). The strong internal consistency between digital competencies and intended learning outcomes (Cronbach’s alpha = 0.93–0.97) aligns with recent literature emphasizing the cognitive integration of digital fluency frameworks into curriculum planning (Makhafola et al., 2025 ; Yang et al., 2025 ). Moreover, this research supports the theoretical premise that digital curriculum design is most effective when it is modular, contextualized, and aligned with evolving industry practices. By analyzing real syllabi and stakeholder preferences, we extend existing frameworks like the TPACK model and EU DigComp into the domain of construction education, a field often underrepresented in mainstream digital pedagogy research (Su et al., 2025 ; Yan et al., 2025 ). These insights offer a foundation for future theoretical models that integrate domain-specific digital fluency with pedagogical intentionality. This study makes several significant theoretical contributions to the understanding of educational technology implementation in professional education. First, the findings extend existing frameworks by demonstrating that technology-enhanced learning must be purposefully aligned with professional competency development rather than treated as a separate educational component. The strong correlations identified between digital competencies and learning outcomes suggest that when properly integrated, technological fluency enhances rather than competes with core professional skills. Second, the research advances theoretical understanding of professional education by proposing a structured, scaffolded approach to technology integration that balances foundational knowledge with advanced digital applications. This framework challenges conventional approaches that either separate technical skills from theoretical content or treat technology as supplementary to core professional knowledge. As Buckley and Lee (2021) observed, the most effective professional education programs combine curricular with extracurricular development opportunities to create well-rounded graduates. Third, the findings contribute to theoretical models of curriculum design by highlighting the importance of sector-specific and experience-level considerations in technology integration. The surface plot (Fig. 9 ) showing differential perceptions across public and private sectors suggests that universal approaches to digital competency development may be less effective than tailored implementations. This insight extends Ramazani and Jergeas' (2015) work on contextualized professional development by emphasizing the need for customized educational strategies. 4.3.2 Practical Implications From a practical standpoint, the findings provide actionable guidance for curriculum designers and educators in construction disciplines. The identified preference for multiple technology-enhanced courses (39.4% recommending four courses) suggests that institutions should revise traditional single-course approaches to digital competency development. Curriculum designers should consider implementing a progressive sequence of technology-enhanced courses that introduces increasingly complex digital applications as students advance through their programs. The results highlighting strong support for Building Information Modeling (69.69%) and digital project management tools (90.91%) indicate that educational institutions should prioritize these technologies in curriculum development. However, the emphasis should be on authentic application rather than theoretical knowledge, with hands-on projects that mirror industry practices. As Clevenger et al. ( 2017 ) noted, construction education is most effective when it bridges theory and practice through applied learning experiences. For faculty development, the findings underscore the importance of ongoing training in educational technology and industry-standard digital tools. Institutions should invest in faculty development programs that enhance educators' abilities to design and implement technology-enhanced learning experiences. This recommendation aligns with Eiris Pereira and Gheisari's (2019) conclusion that faculty expertise is a critical factor in successful technology integration in construction education. For industry stakeholders, the research highlights the need for continued collaboration with educational institutions to ensure that curriculum design reflects current technological practices and emerging trends. Industry-academia partnerships can facilitate authentic learning experiences that prepare graduates for the digital demands of contemporary construction environments. This approach supports Jackson et al.'s (2023) emphasis on industry-aligned capabilities frameworks in professional education. 4.4 Information Processing and Technology Integration in Construction Education From an information processing perspective, the findings reveal significant implications for how educational technology enhances knowledge acquisition and application in construction education. The strong preference for focused digital integration (63.6% favoring comprehensive coverage of fewer topics) suggests that deep processing of technological content is more valuable than surface-level exposure across multiple platforms. This insight aligns with information processing theory, which emphasizes depth of cognitive engagement as a key factor in effective learning (Acharya et al., 2017). The correlation analysis revealed that technology-related knowledge domains and learning outcomes form interconnected networks rather than isolated components. This finding supports distributed information processing models, where knowledge is constructed through connections between concepts rather than through discrete units. Educational technology can enhance these connections by providing visual representations, interactive simulations, and collaborative platforms that make abstract construction concepts more concrete and accessible. The findings also highlight the importance of sequencing in information processing, with most respondents (43.9%) preferring to integrate technology-enhanced courses in the later years of undergraduate programs. This preference suggests that effective information processing in construction education requires establishing fundamental conceptual frameworks before introducing complex technological applications. As Torres et al. (2019) noted, project-based learning approaches that progressively introduce technology can significantly enhance information retention and application in construction education. 4.5 Alignment with Information Processing and Management in the Digital Era In educational technology research, baseline comparisons typically involve evaluating proposed instructional strategies or tools against state-of-the-art (SOTA) pedagogical models or existing curriculum frameworks. However, the nature of this study—focused on surveying educational stakeholders and analyzing real-world syllabi—does not involve the implementation or benchmarking of a novel learning algorithm or digital intervention. Instead, our approach emphasizes empirical curriculum mapping and stakeholder-driven preferences, aiming to develop a grounded framework for digital competency integration within CPM education. While no experimental baselines were used, the study’s findings were interpreted in light of established frameworks such as digital literacy models (Yang et al., 2025 ), AI-in-education reviews (G. Liu et al., 2025 ), and recent trends in higher education digitalization (Zhao & Zhou, 2024 ). These references served as conceptual baselines to inform our analysis and ensure the recommendations are aligned with contemporary discourse on technology-enhanced learning. Future studies could build on our curriculum-level insights by piloting and quantitatively benchmarking technology-enhanced CPM modules against these SOTA frameworks. This research directly addresses the evolving information processing challenges in construction education within the context of rapid digital transformation. A well-balanced curriculum that emphasizes the most critical domains while providing adequate coverage of other relevant topics will best prepare students for successful careers in CPM (Fig. 10 ). The findings demonstrate how educational technology can enhance information management capabilities in professional education, preparing graduates for technology-driven construction environments. By identifying the most valued digital competencies and preferred implementation approaches, our study provides evidence-based guidance for optimizing information processing in construction education. The strong support for digital project management tools (90.91%) highlights their central role in contemporary information processing within construction contexts. As highlighted in our findings, digital competencies are increasingly becoming the primary determinant of project success in construction environments. Educational institutions must therefore ensure that graduates are proficient in using these tools to gather, analyze, and communicate project information effectively (Cavka et al., 2017). The emphasis on digital information management aligns with contemporary understanding of how technology transforms information processing in professional contexts. The findings on technology integration preferences also have significant implications for information management in construction education. The preference for multiple courses (39.4% recommending four courses) suggests that information processing skills should be developed progressively, with increasing complexity as students advance. This approach aligns with research on scaffolded learning in construction education (Wang et al., 2020), which demonstrates that sequential skill development yields superior professional outcomes compared to concentrated technology-focused modules. This structured approach allows for the development of information management capabilities, from basic data handling to sophisticated analytical applications. The correlation analysis revealing strong relationships between digital competencies and learning outcomes (Cronbach's alpha 0.93–0.97) supports the argument that information processing capabilities serve as the foundation for broader professional competencies in technology-rich construction environments (Smith et al., 2018). Construction programs emphasizing integrated information management skills through multiple technology-enhanced courses can produce graduates with higher problem-solving capabilities in complex digital environments (Zhang et al., 2019). These findings highlight the need for educational approaches that emphasize not just technological tools but the underlying information processing frameworks that enable effective decision-making in contemporary construction practice. The importance of balancing theoretical knowledge with practical digital applications, as indicated by respondents' preference for focused content delivery (63.6% favoring comprehensive coverage of fewer topics), aligns with research on cognitive load in construction education (Peterson et al., 2011). Deep information processing of core digital competencies yields superior professional outcomes compared to superficial exposure to a broader range of technologies. This approach ensures that graduates can effectively process, analyze, and apply construction information using industry-standard digital tools, addressing the primary concerns regarding information management in professional contexts (Lima et al., 2017). 4.6 Limitations and Future Research Directions Despite its contributions, this study has several limitations that provide opportunities for future research. First, the sample size (N = 66), while adequate for the analytical approaches employed, could be expanded in future studies to include more diverse stakeholders. Second, the cross-sectional design captures perceptions at a single point in time, limiting insights into how technology integration preferences evolve with changing industry practices. Longitudinal studies tracking the implementation and outcomes of technology-enhanced curricula would provide valuable additional insights. Future research should explore the long-term impact of technology-enhanced learning on graduate employability and professional practice. Studies comparing the workplace performance of graduates from technology-rich versus traditional programs would provide valuable evidence of educational outcomes. Additionally, research examining specific pedagogical approaches for different digital technologies would help refine implementation strategies for various tools and platforms. As educational technology continues to evolve, maintaining adaptable frameworks for digital competency development will be crucial. Future studies should investigate emerging technologies such as artificial intelligence, extended reality, and digital twins, assessing their potential applications in construction education. Research on effective faculty development programs for technology integration would also address an important gap identified in this study. 5. Conclusion This study provides significant insights into the transformative role of educational technology in Construction Project Management education within higher education contexts. The integration of digital tools and technology-enhanced learning approaches demonstrates a paradigm shift in how professional competencies are developed in undergraduate programs. Our findings reveal that successful technology integration requires careful consideration of pedagogical approaches, digital literacy development, and industry alignment. The study's mixed-methods analysis highlights the importance of structured technology integration across the curriculum, with 63.6% of respondents favoring focused digital competency development through multiple courses. The strong correlation between digital tool proficiency and learning outcomes (Chronbach's alpha 0.93–0.97) suggests that technology-enhanced learning can effectively support professional skill development. Particularly significant is the widespread support for digital project management tools (90.91%) and Building Information Modeling (69.69%), indicating the critical role of authentic digital experiences in professional education. For educational technology implementation, our findings emphasize the need for flexible, scaffolded approaches that balance theoretical knowledge with practical digital competencies. The research suggests that successful technology integration in professional education requires institutional support, faculty development, and continuous alignment with evolving industry practices. The timing and sequencing of technology-enhanced courses, with 43.9% preferring integration in later years, indicates the importance of building foundational knowledge before advanced digital applications. These insights contribute to the broader discourse on educational technology in professional education, offering evidence-based guidance for curriculum design and implementation. Future research should explore the long-term impact of technology-enhanced learning on graduate employability and professional practice. As educational technology continues to evolve, maintaining adaptable frameworks for digital competency development will be crucial for preparing graduates for technology-driven professional environments. Declarations Conflict of Interest All authors confirm that they have no conflicts of interest. Data Availability The de-identified dataset used in this study is available from the corresponding author, Dr. Saleh Alsulamy ( [email protected] ), upon reasonable request. Public sharing is restricted to protect participant confidentiality. Ethical Approval The study was approved by the Research Ethics Committee at King Khalid University (Approval No. ECM#2024-3105), conducted in accordance with relevant ethical guidelines and regulations, and the clearance certificate. Consent to participate Informed consent was obtained from all participants prior to data collection. Participants were fully informed about the purpose of the study, their voluntary involvement, and their right to withdraw at any time. Anonymity and confidentiality were strictly maintained throughout the research process. Consent for publication All participants provided consent for the publication of anonymized data collected during the study. No personally identifiable information has been disclosed in the manuscript. Acknowledgment The authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through small group research under grant number RGP.2/121/46. Funding This work was supported by King Khalid University [Project RGP.2/121/46] Contribution M.A Conceptualization, methodology development, supervision, data interpretation, and final manuscript review and approval. S.A Data collection, data analysis, preparation of results, and drafting of the initial manuscript. 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1","display":"","copyAsset":false,"role":"figure","size":79890,"visible":true,"origin":"","legend":"\u003cp\u003eWorkflow of CPM course curriculum survey\u003c/p\u003e","description":"","filename":"image1.png","url":"https://assets-eu.researchsquare.com/files/rs-8337804/v1/e58b1bd79b402925f235e618.png"},{"id":100400605,"identity":"d76414c8-d900-45c6-be95-ba04d58f0502","added_by":"auto","created_at":"2026-01-16 11:58:19","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":111781,"visible":true,"origin":"","legend":"\u003cp\u003eRespondent agreement levels for the inclusion of various knowledge domains in CPM curricula.\u003c/p\u003e","description":"","filename":"image2.png","url":"https://assets-eu.researchsquare.com/files/rs-8337804/v1/8cab233c513935cc9620e2c1.png"},{"id":100400293,"identity":"689e8a9e-220d-43fb-9b83-062c49317362","added_by":"auto","created_at":"2026-01-16 11:58:03","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":140314,"visible":true,"origin":"","legend":"\u003cp\u003eRespondent preferences for course lengths allocated to different knowledge domains.\u003c/p\u003e","description":"","filename":"image3.png","url":"https://assets-eu.researchsquare.com/files/rs-8337804/v1/725fc055ba9047402075331f.png"},{"id":100400061,"identity":"e6dc06bd-c10a-4aaf-85f0-a0f407565f93","added_by":"auto","created_at":"2026-01-16 11:57:51","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":112786,"visible":true,"origin":"","legend":"\u003cp\u003eRespondent agreement levels for the appropriateness of learning outcomes in CPM courses.\u003c/p\u003e","description":"","filename":"image4.png","url":"https://assets-eu.researchsquare.com/files/rs-8337804/v1/64aa7f0a633315013011afa3.png"},{"id":100399532,"identity":"cafd6aab-f664-4c85-ac2d-ee77a8f01566","added_by":"auto","created_at":"2026-01-16 11:57:11","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":242845,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between demographic characteristics and perceived importance of knowledge domains\u003c/p\u003e","description":"","filename":"image5.png","url":"https://assets-eu.researchsquare.com/files/rs-8337804/v1/f5c59d84a6b60bd13c1dde39.png"},{"id":100401038,"identity":"b1d923c4-17b7-45ae-953c-56e95292f93d","added_by":"auto","created_at":"2026-01-16 11:58:40","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":198294,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between demographic characteristics and perceived appropriate course lengths\u003c/p\u003e","description":"","filename":"image6.png","url":"https://assets-eu.researchsquare.com/files/rs-8337804/v1/692465006287ab5e87e16faf.png"},{"id":100421448,"identity":"ac8272bf-b931-4ca3-92d0-4bc912bce021","added_by":"auto","created_at":"2026-01-16 13:32:59","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":123091,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation between demographic characteristics and perceived learning outcomes and content suggestions\u003c/p\u003e","description":"","filename":"image7.png","url":"https://assets-eu.researchsquare.com/files/rs-8337804/v1/0257d82f057be731d48f04b8.png"},{"id":100401016,"identity":"0836f524-c441-429b-8a8e-008d0d1ec042","added_by":"auto","created_at":"2026-01-16 11:58:39","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":156074,"visible":true,"origin":"","legend":"\u003cp\u003e3D network graph of CPM education elements\u003c/p\u003e","description":"","filename":"image8.png","url":"https://assets-eu.researchsquare.com/files/rs-8337804/v1/2e4e33c88bc58ea9c34b3785.png"},{"id":100400877,"identity":"53f4edfe-855f-47e1-973f-d8e8fd81da7c","added_by":"auto","created_at":"2026-01-16 11:58:29","extension":"jpeg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":202862,"visible":true,"origin":"","legend":"\u003cp\u003e3D surface plot illustrating the relationship between years of experience, perceived importance of a knowledge domain, and job sector (public and private)\u003c/p\u003e","description":"","filename":"image9.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-8337804/v1/6f00e4160a0b610775259c03.jpeg"},{"id":100401144,"identity":"a45ab1eb-258c-4da1-ab18-cf25d7009141","added_by":"auto","created_at":"2026-01-16 11:58:43","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":144498,"visible":true,"origin":"","legend":"\u003cp\u003eInsufficient alignment of CPM education with industry needs\u003c/p\u003e","description":"","filename":"image10.png","url":"https://assets-eu.researchsquare.com/files/rs-8337804/v1/43bc5a6dc3898704f7b9f4a5.png"},{"id":102226161,"identity":"fb027362-8af6-4245-b15a-97dc73be9a76","added_by":"auto","created_at":"2026-02-09 14:41:32","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2530922,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8337804/v1/3466305c-4d5f-4ff1-8574-c13fec8fa750.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Integrating Digital Technologies in Construction Education: A Mixed-Methods Study of Curriculum Design and Learning Outcomes in Project Management","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eWithin the limitations of time, money, quality, and scope, construction project management (CPM) is a multidimensional discipline that includes the planning, coordinating, and carrying out of construction projects to accomplish objectives (Posillico et al., \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). For the last decade, the construction industry has been rapidly and sophisticatedly changed to catch up with the current demands. Also, dramatic changes in social, economic, and environmental issues are now forcing construction management (CM) programs to produce more prepared personnel (Lee et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Despite the rise of automation and digitalization, the construction sector ultimately relies on human skills, and the knowledge, abilities, and competencies of these individuals are crucial for its success (Posillico et al., \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). While the government across different countries emphasizes technology, the actual execution depends on human resources like people, leadership, and formal education/training. However, the strategy also highlights the risk posed by inadequate training in the industry. Therefore, investing in appropriate and relevant education is vital for both the present economy and future prosperity (Cristina et al., \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAs urbanization accelerates and global population surges, the demand for new construction and infrastructure development has intensified dramatically (Z. Liu \u0026amp; Wu, \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Zhu et al., \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). This construction boom has amplified the crucial need for skilled project managers who can expertly guide construction projects to successful completion (Gong et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Effective project management is vital for keeping construction initiatives on track, controlling risks, maximizing resource utilization, and satisfying the expectations of all stakeholders involved (Kerzner, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). The pivotal role of project management in construction underscores the importance of robust educational programs that can nurture the requisite skills, knowledge, and expertise in the next generation of professionals (Limsila \u0026amp; Ogunlana, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Universities have emerged as key hubs for delivering this specialized CPM education through dedicated undergraduate and graduate degree programs (Pearce et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). The curricula are carefully designed to provide students with a solid theoretical foundation combined with practical abilities and insights into industry realities \u0026ndash; arming them with the full toolkit needed to take on the ever-shifting complexities of CPM (Casasayas et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBy instilling this powerful combination of construction smarts: fundamentals, applicable skills, and a pulse on the industry, university CPM programs act as generative forces (Arditi \u0026amp; Polat, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). They develop well-rounded graduates ready to stride confidently into the field and apply their multi-faceted expertise to spearhead construction projects with poise and consistent excellence (Limsila \u0026amp; Ogunlana, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; Pearce et al., \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Nonetheless, diversity characterizes the CPM education landscape, with notable differences found in curricular structures, content, methodologies, and contextual factors among universities globally (Adafin et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). This diversity reflects not only the unique educational philosophies and priorities of individual institutions but also the influence of regional practices, cultural norms, regulatory frameworks, and industry demands (O. A. Adedokun et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). While this diversity enriches the educational experience and accommodates local nuances, it also poses challenges in ensuring consistency, relevance, and alignment with global standards and best practices (Badiru et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAgainst this backdrop, there is a growing imperative to conduct a comprehensive comparative study of CPM curricula across universities globally to unravel the prevailing trends, discern intricate divergences, and identify emerging paradigms in CPM education (Banihashemi et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Such a study holds immense value for educators, practitioners, policymakers, and other stakeholders involved in CPM education and practice. Through this study, strategic decision-making, curriculum development initiatives, accreditation processes, and professional development efforts aimed at improving the quality, effectiveness, and relevance of CPM education can be informed by insights into the strengths, weaknesses, opportunities, and threats inherent in current CPM curricula (O. A. Adedokun et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Badiru et al., \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). By inculcating this potent synthesis of construction-centric erudition, encompassing fundamentals, applied skills, and industry acumen, university CPM programs function as catalytic forces (Toledo et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). They nurture a cadre of well-rounded graduates poised to confidently transition into the professional realm, leveraging their multifaceted expertise to spearhead construction projects with unwavering poise and consistent excellence (Adafin et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Ramazani \u0026amp; Jergeas, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Moreover, these academic programs foster collaboration and knowledge exchange among students, faculty, and industry partners, thereby facilitating the cross-pollination of ideas and best practices (Clarke \u0026amp; Clarke, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). As the construction industry continues to evolve and grapple with challenges such as sustainability, digitalization, and complex stakeholder dynamics, the role of higher education in shaping future project management professionals becomes increasingly pivotal (Adafin et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). By continuously refining their curricula and pedagogical approaches to align with industry trends and emerging methodologies, universities can equip graduates with the cutting-edge competencies required to navigate the ever-changing construction landscape (O. Adedokun et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; J.-M. Kim et al., \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCPM courses in undergraduate education hold paramount importance for students of Civil Engineering and Architecture (Clevenger et al., \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Such courses provide a solid foundation in the principles, methodologies, and best practices of managing construction projects, which eventually help the students to become competent, adaptable, and innovative professionals capable of tackling the multifaceted challenges of the built environment (Hall, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). A carefully crafted CPM curriculum generally integrates theoretical knowledge with hands-on experience so that students can equip technical expertise, leadership skills, and problem-solving abilities to successfully coordinate the aspects of construction projects (Forsythe et al., \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). CPM education prepares these graduates to meet the evolving demands of the construction sector through valuable exposure to the practical realities and challenges of CPM, which, in turn, plays a crucial role in bridging the gaps between academia and industry, thereby enhancing their employability and career prospects (Chileshe \u0026amp; Haupt, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Iyer-Raniga \u0026amp; Dalton, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eInvesting in high-quality CPM education for undergraduate students is not only essential for their individual success but also for the long-term growth and sustainability of the construction industry. Universities contribute to the advancement of the field of construction and the creation of a more efficient, resilient, and socially responsible built environment by nurturing a new generation of project managers who are well-versed in emerging technologies, sustainable practices, and innovative management approaches (Eiris Pereira \u0026amp; Gheisari, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). An industry-aligned curriculum where universities collaborate closely with construction industry professionals can ensure that the CPM curriculum reflects the latest trends, challenges, and best practices in the field (Atif et al., n.d.; Jackson et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Universities can prepare students for the real-life construction sector and enhance their employability scopes by aligning the curriculum with industry needs (Ruge \u0026amp; McCormack, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Fostering a multidisciplinary learning environment in the universities that involves students from different programs working together on projects and assignments can greatly help later in collaborating with construction project professionals from various disciplines. Moreover, familiarizing students with cutting-edge tools and software (e.g., Building Information Modelling, project management software, virtual reality simulations, etc.) through CPM curriculum is a must to cope up with the rapid advancement of digital technologies in the construction industry (O. Adedokun et al., \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; S. Kim et al., \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe lack of standardization in CPM curricula across universities and countries can create significant challenges for students who wish to transfer between institutions or pursue further education in different regions (Arditi \u0026amp; Polat, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). Inconsistencies in the knowledge domains covered, course lengths allocated, and learning outcomes emphasized can lead to disparities in the knowledge and skills acquired by students, potentially hindering their ability to adapt to new educational environments or meet the expectations of employers in different geographical contexts (Pikas et al., \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Sacks \u0026amp; Pikas, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Educators can strive these challenges by developing more consistent and comprehensive CPM curricula that cover the essential knowledge domains, allocate appropriate course lengths, and emphasize the most important learning outcomes, as identified in this study. For example, topics such as construction contracts and project delivery methods should be taught together and in the context of real-world construction projects to help students understand their practical applications and the complex interrelationships between these domains (Abbas et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). By providing students with a well-rounded and cohesive education that integrates theoretical knowledge with hands-on experience, universities can better prepare them to navigate the challenges of the construction industry, regardless of the geographical context in which they choose to pursue their careers. Considering the rapid evolution of digital technologies, the construction education sector faces multiple challenges, including fragmented adoption of digital tools, inconsistent integration into curricula, and a lack of clear alignment between digital competencies and learning outcomes. Existing research tends to generalize digital pedagogy without addressing the domain-specific needs of fields like CPM, where practical tool usage and project-based workflows are central to professional readiness. Furthermore, there is limited empirical evidence on how stakeholders perceive the role of digital tools across curricula or how institutional practices vary globally in this context.\u003c/p\u003e \u003cp\u003eTo address these gaps, this study aims to: (1) identify essential digital competencies required for effective CPM education, (2) examine current technology-enhanced teaching practices and stakeholder preferences, (3) analyze the structure and design of CPM curricula across global institutions, and (4) offer actionable recommendations for the structured integration of digital tools in construction education.\u003c/p\u003e \u003cp\u003eBeyond these objectives, this study contributes broader impacts by offering a scalable framework for aligning digital literacy with discipline-specific pedagogical needs. Its findings are intended to guide policy, curriculum reform, and faculty development efforts across educational systems navigating digital transformation. The intellectual merit of the work lies in its mixed-methods approach, triangulating stakeholder insights and curriculum data to offer a holistic view of digital integration in CPM education\u0026mdash;an area that remains underexplored in the educational technology literature.\u003c/p\u003e"},{"header":"2. Materials and Methodology","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Research Design and Data Collection\u003c/h2\u003e \u003cp\u003eThis study employed a mixed-methods approach to examine technology integration in CPM education. An online cross-sectional survey was conducted during September and October 2024 targeting professionals involved in the construction industry, including academics, clients, contractors, and consultants (Ferri-Garc\u0026iacute;a \u0026amp; Rueda, 2020). The inclusion criteria comprised adult residents in diverse countries who were competent in English and willing to participate. This methodological approach aligns with recent educational technology research that emphasizes the importance of gathering diverse stakeholder perspectives (Liu et al., 2019).\u003c/p\u003e \u003cp\u003eThe survey questionnaire was developed using SurveyMonkey, following established design principles for educational research (\u0026Ccedil;elen \u0026amp; Aybek, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Warmbrod, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The instrument consisted of five main sections: (1) demographic information, (2) knowledge domains, (3) course length, (4) learning outcomes, and (5) course structure. Institutional ethics approval was obtained before distribution, and participants provided consent along with their survey submission.\u003c/p\u003e \u003cp\u003e Before distributing the survey, institutional ethics approval was obtained from Ethics Committee. The survey link was then shared with potential respondents through various channels, including email, social media, and professional networks. Participants provided consent along with the submission of the online survey, ensuring that their participation was voluntary and informed. Responses from 75 individuals were initially collected. However, after eliminating the missing and incomplete responses, the final sample contained responses from 66 participants. This sample size was deemed sufficient for the purposes of this study, as it provided a diverse representation of professionals from various backgrounds and countries.\u003c/p\u003e \u003cp\u003eThis study utilized two primary datasets. The first dataset comprises responses from 66 educational stakeholders, including academic faculty, curriculum designers, and industry professionals involved in CPM education. Respondents were selected through purposive and snowball sampling across global institutions, ensuring a diverse representation of educational perspectives. The survey instrument included Likert-scale and open-ended items addressing digital competency integration, curriculum structure, and technology use.\u003c/p\u003e \u003cp\u003eThe second dataset includes 20 CPM course syllabi collected from accredited Civil Engineering and Architecture programs across North America, Europe, Asia, and the Middle East. Syllabi were selected through publicly accessible institutional websites and personal communication with faculty members. Each syllabus was analyzed for course structure, digital tool integration (e.g., BIM, scheduling software), learning objectives, and assessment types. Data from both sources were triangulated to generate a comprehensive understanding of technology-enhanced curriculum practices.\u003c/p\u003e \u003cp\u003eBoth datasets were anonymized and coded using NVivo for qualitative themes and SPSS for quantitative analysis. Reliability and internal consistency were evaluated using Cronbach\u0026rsquo;s alpha (α\u0026thinsp;=\u0026thinsp;0.93\u0026ndash;0.97).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Survey Instrument and Measures\u003c/h2\u003e \u003cp\u003eThe knowledge domains section used a 7-point Likert scale to measure agreement levels regarding the inclusion of 36 knowledge domains in CPM courses (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). This approach is consistent with methods used in previous curriculum assessment studies (Warmbrod, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). The course length section asked respondents to select appropriate content lengths for these domains in undergraduate programs. Respondents rated the appropriateness of 30 learning outcomes using the same 7-point scale (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The internal consistency reliability was assessed using Cronbach's alpha, with values ranging between 0.93 and 0.97 for different sections, indicating excellent reliability (Warmbrod, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2014\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe course structure section included four questions on curriculum design aspects: (1) techniques for determining topic range, (2) appropriate number of CPM courses, (3) recommended credit hours, and (4) optimal study level for course integration. These questions were designed to capture comprehensive insights into effective technology integration in professional curricula (Adafin et al., \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2022\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eKnowledge domains included in the survey questionnaire.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eKD 01\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHistorical Perspective\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eKD 19\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProject Scheduling\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKD 02\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConstruction Industry\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eKD 20\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProject Integration Management\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKD 03\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConstruction Management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eKD 21\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProject Scope Management\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKD 04\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConstruction Technology\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eKD 22\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProject Monitoring and Control\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKD 05\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConstruction Contracts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eKD 23\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProduction Improvement\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKD 06\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProject Delivery Methods\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eKD 24\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eConstruction Operation and Job Site Management\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKD 07\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLeadership\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eKD 25\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProject Closeout\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKD 08\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProject Stages\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eKD 26\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eQuality Management\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKD 09\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eStakeholder Management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eKD 27\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eMaterials and Equipment Management\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKD 10\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePeople and Organizational Management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eKD 28\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCommunication Management\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKD 11\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProject Life Cycle\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eKD 29\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eValue Engineering\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKD 12\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProject Cost Management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eKD 30\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProject Health, Safety, Security and Environment\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKD 13\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProject Financial Management\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eKD 31\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProject Risk Management\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKD 14\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConstruction Bidding\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eKD 32\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePartnership\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKD 15\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConstruction Tendering\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eKD 33\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBuilding Information Modelling\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKD 16\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eorganizational Structure\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eKD 34\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eInformation and Communications Technology\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKD 17\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConstruction Procurement\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eKD 35\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eConstruction Dispute\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eKD 18\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eProject Planning\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u003cb\u003eKD 36\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eProject Documentation\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Sample Characteristics and Data Analysis\u003c/h2\u003e \u003cp\u003eFrom 75 initial responses, the final analytical sample comprised 66 participants after removing incomplete entries. The respondents represented diverse professional backgrounds: 36 academics (54.5%), 17 consultants (25.8%), 11 clients (16.7%), and 2 contractors (3.0%). Geographic distribution included Saudi Arabia (36.4%), United States (10.6%), United Kingdom (10.6%), Malaysia (9.1%), and other countries (33.3%). Professional experience ranged from 1 to 48 years (M\u0026thinsp;=\u0026thinsp;19.39, SD\u0026thinsp;=\u0026thinsp;11.34), providing perspectives across career stages (Rajput et al., 2022).\u003c/p\u003e \u003cp\u003eDescriptive statistics summarized demographic characteristics, while inferential statistics analyzed responses related to knowledge domains, course lengths, learning outcomes, and curriculum structure. Pearson correlation analysis investigated relationships among variables, with particular attention to connections between digital competencies and educational outcomes (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The mixed-methods analysis approach allowed for triangulation of quantitative findings with qualitative insights from the curriculum reviews (Cavka et al., 2017).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLearning outcomes included in the survey questionnaire.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcronyms\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDetailed Learning Outcomes\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRecognize the development of construction management theory throughout the history\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 02\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eArticulate the nature, and essential characteristics of construction industry\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIdentify the needs \u0026amp; expectations of stockholders during construction stages\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrepare strategies for preliminary activities, logistics, materials mobilization and equipment\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDefine construction project life cycle, stages and process\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUtilize the tools and techniques for planning and scheduling construction project activities\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEmploy the tools and techniques for controlling and monitoring construction project\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 08\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDemonstrate knowledge of construction management technologies\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 09\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eInvestigate, analyze, and solve project problems\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAnalyze leadership characteristics and theories and realize the effectiveness\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDetermine how leadership strategies impact the performance of project and projectized organizations\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDefine project manager responsibilities and duties\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eEmploy and integrate construction project regulations, rules, specifications and codes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDescribe tender components, requirements, and processes\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eApprise and examine the appropriateness of project delivery methods for different project characteristics\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDemonstrate a basic knowledge of components, principles, process, and formation of construction contracts and list contractual documents and recognize its importance\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUtilize the principles and practices of construction procurement and procurement management\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDefine the phases and process of construction disputes and conflicts\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eApply critical success factors and measure success\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDemonstrate the role and impact of Building Information Modeling (BIM) to construction projects\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCompare project management methodologies, PMBok and Prince\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIdentify and locate the scope and integration of the construction project\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eApply basic learning and assessment principles of project health, safety, security and environment (HSSE)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDevelop and design Organizational Breakdown Structure (OBS), Work Breakdown Structure (WBS)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAppraise project cost management and financial aspects\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDemonstrates the basics principles and process of Value Engineering (VE) and differentiate it rules in project stages\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCritically examine essential ideas and concepts of Risk Management in construction\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 28\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eList and distinguish between different type of construction partnerships and demonstrate its impact on projects\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDemonstrate the basic knowledge of quality management concepts and process\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLO 30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eCreate follow-up and progress sheets, check list sheets, bar charts and critical path\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Demographic Characteristics\u003c/h2\u003e \u003cp\u003eThe survey gathered responses from a diverse group of 66 construction industry professionals. As presented in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, academics constituted the majority (54.5%) of respondents, followed by consultants (25.8%), clients (16.7%), and contractors (3.0%). Most respondents (63.6%) were from the public sector, while 36.4% represented the private sector. This distribution provides a balanced perspective between educational institutions and industry practitioners, enhancing the validity of the findings regarding technology integration in construction education.\u003c/p\u003e \u003cp\u003eGeographically, respondents represented multiple countries, with Saudi Arabia (36.4%), the United States (10.6%), the United Kingdom (10.6%), and Malaysia (9.1%) having the highest representation, followed by other countries (33.3%). This international perspective offers valuable insights into technology-enhanced learning approaches across diverse educational systems and construction practices. The respondents' professional experience varied substantially, ranging from 1 to 48 years (M\u0026thinsp;=\u0026thinsp;19.39, SD\u0026thinsp;=\u0026thinsp;11.34), providing perspectives from both emerging and established practitioners across different career stages.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDemographic Characteristics of the Respondents (N\u0026thinsp;=\u0026thinsp;66)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eDemographic Characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eProfession Types\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAcademic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eClient\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.7%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eContractor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConsultant\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eSector Types\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePublic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePrivate\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCountry of Residency\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSaudi Arabia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnited States\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eUnited Kingdom\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMalaysia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eOthers\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e22\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Knowledge Domains for Technology-Enhanced Learning\u003c/h2\u003e \u003cp\u003eThe analysis of knowledge domain preferences revealed strong support for digital competency development within CPM education. As illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, traditional management-focused knowledge domains received high agreement levels, with Construction Management (98.48%), Project Planning (96.97%), and Project Scheduling (96.97%) ranked highest. However, technology-focused domains also received substantial support, demonstrating the perceived importance of digital integration in contemporary construction education.\u003c/p\u003e \u003cp\u003eBuilding Information Modeling (BIM) received agreement from 69.69% of respondents, indicating substantial recognition of its role in contemporary construction education. Information and Communications Technology (ICT) received support from 62.12% of respondents, further emphasizing the perceived importance of digital literacy. Project Monitoring and Control, which increasingly relies on digital tools, was endorsed by 92.42% of respondents, highlighting the significance of technology-enhanced monitoring capabilities in construction management education.\u003c/p\u003e \u003cp\u003eDigital project management tools received the strongest support among technology-specific domains, with 90.91% of respondents endorsing their inclusion in CPM curricula. This overwhelming support indicates a clear industry consensus regarding the necessity of digital competency development for construction professionals. The data suggests that while traditional knowledge domains remain fundamental, technology-focused domains are now considered essential components of a comprehensive CPM curriculum.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Course Lengths for Digital Competency Development\u003c/h2\u003e \u003cp\u003eAnalysis of recommended course lengths (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) revealed interesting patterns regarding the perceived importance of technology-related content. While respondents endorsed the inclusion of digital knowledge domains, their recommendations for content lengths varied significantly. For Building Information Modeling, 42.42% recommended a full Chap.\u0026nbsp;(12 pages), while 13.64% suggested only one page, indicating divergent perspectives on the depth of coverage required.\u003c/p\u003e \u003cp\u003eFor Project Monitoring and Control, 37.88% recommended a full chapter, 19.70% suggested three-quarters of a chapter, and 19.70% preferred half a chapter. This distribution suggests general agreement on the substantial importance of digitally enhanced project monitoring, though with varying emphasis. Information and Communications Technology showed a more distributed pattern, with 21.21% each recommending a full chapter and one page, reflecting diverse opinions on its optimal coverage.\u003c/p\u003e \u003cp\u003eThese findings suggest that while technology integration is widely supported, there are varying perspectives on the depth of coverage required for different digital competencies. This variation may reflect the rapidly evolving nature of construction technology and the need for flexibility in curriculum design. The data provides valuable guidance for educators determining appropriate emphasis on various technology-related domains within CPM programs.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Learning Outcomes for Digital Competency Development\u003c/h2\u003e \u003cp\u003eThe survey results on learning outcomes (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e) revealed strong support for digitally focused educational objectives. The ability to utilize tools and techniques for planning and scheduling construction project activities received the highest support, with 90.91% agreeing or strongly agreeing. Similarly, the capacity to employ tools and techniques for controlling and monitoring construction projects received agreement from 86.36% of respondents, further emphasizing the value placed on digital monitoring capabilities.\u003c/p\u003e \u003cp\u003eDemonstrating knowledge of construction management technologies received agreement from 80.30% of respondents, with an additional 16.67% slightly agreeing. The ability to demonstrate the role and impact of Building Information Modeling (BIM) in construction projects was endorsed by 77.27% of respondents, with 19.70% slightly agreeing. These findings highlight the perceived importance of technological proficiency in contemporary construction management.\u003c/p\u003e \u003cp\u003eThe learning outcomes with the highest levels of agreement align closely with technology-enhanced capabilities, suggesting that digital competencies are now considered core skills rather than supplementary knowledge. This perspective is consistent with the rapid digital transformation occurring within the construction industry and indicates the need for curriculum adjustments to address these evolving requirements.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Technology Integration Preferences in Curriculum Design\u003c/h2\u003e \u003cp\u003eRegarding curriculum design considerations (Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e), 63.6% of respondents preferred a focused approach with \"a small number of topics with comprehensive contents\" over broader coverage with less depth (36.4%). This finding suggests that in-depth technology integration may be more effective than superficial coverage across many subjects, providing guidance for educational institutions designing technology-enhanced CPM programs.\u003c/p\u003e \u003cp\u003eWhen asked about the optimal number of CPM-related courses, the largest group of respondents (39.4%) recommended four courses, followed by 27.3% suggesting two courses and 25.8% advocating for three courses. Only 7.6% believed a single course was sufficient. This distribution indicates strong support for multiple technology-enhanced courses rather than attempting to address digital competencies in a single dedicated module.\u003c/p\u003e \u003cp\u003eRegarding credit hours, recommendations varied widely, with 27.3% suggesting 12 credit hours for CPM-related courses, while 15.2% each recommended 6 and 3 credit hours respectively. This diversity reflects the complexity of balancing digital competency development with other curriculum requirements. Most respondents (43.9%) preferred integrating CPM courses in the later years (4th-5th) of undergraduate programs, with 37.9% suggesting the 3rd to 4th years. Only 18.2% recommended earlier integration (2nd to 3rd years). These findings suggest that digital competencies are most effectively developed after establishing foundational knowledge.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eRespondents' preferences for curriculum design (N\u0026thinsp;=\u0026thinsp;66)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eN\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCurriculum design considerations summary\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSmall number of topics with comprehensive contents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHigh number of topics with summarized contents\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e24\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eNumber of CPM Courses for Undergraduates\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 Course\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 Courses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 Courses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.8%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 Courses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39.4%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eCredit Hours for CPM courses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2 Credit Hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 Credit Hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4 Credit Hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e6\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 Credit Hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6.1%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 Credit Hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 Credit Hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.0%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e8 Credit Hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e9 Credit Hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.6%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 Credit Hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 Credit Hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.5%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 Credit Hours\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e27.3%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eTimeline for integrating CPM courses\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2nd to 3rd Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e18.2%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3rd to 4th Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e37.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e4th to 5th Years\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e29\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.9%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003e3.6 Correlation Analysis of Technology Integration Variables\u003c/h2\u003e \u003cp\u003eThe correlation analysis revealed significant relationships between technology-related variables. Figure\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e illustrates correlations between demographic characteristics and perceived importance of knowledge domains. The analysis revealed that profession type showed moderate correlations with construction management (r\u0026thinsp;=\u0026thinsp;0.3), project financial management (r\u0026thinsp;=\u0026thinsp;0.3), and partnership (r\u0026thinsp;=\u0026thinsp;0.3). However, job sector type and years of experience showed weak correlations with most knowledge domains, suggesting that perceptions of domain importance transcend these demographic factors.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e depicts correlations between demographic characteristics and perceived appropriate course lengths. Notable correlations include those between profession type and course length for historical perspective (r\u0026thinsp;=\u0026thinsp;0.3) and construction dispute (r\u0026thinsp;=\u0026thinsp;0.3). The generally weak correlations in this analysis suggest that opinions on appropriate course lengths are not strongly influenced by demographic factors.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e shows correlations between demographic characteristics and perceived learning outcomes and content suggestions. Moderate correlations were observed between profession type and learning outcomes related to leadership effectiveness (r\u0026thinsp;=\u0026thinsp;0.3) and construction partnerships (r\u0026thinsp;=\u0026thinsp;0.3). The correlation between the number of CPM courses and credit hours was relatively strong (r\u0026thinsp;=\u0026thinsp;0.5), indicating logical consistency in respondents' curriculum recommendations.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe 3D network graph (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003e) illustrates the interconnected relationships between various elements of CPM education. The graph features nodes representing different components, including knowledge domains, learning outcomes, and curriculum design considerations. Edges between the nodes depict the strength and nature of their connections. This visualization emphasizes how different components of the educational framework are interdependent, with technology-related elements serving as connecting nodes between traditional knowledge areas.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eFigure\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e presents a 3D surface plot showing how years of experience and perceived importance interact across job sectors (public and private). This visualization reveals that perceived importance varies more significantly with increasing years of experience in the public sector compared to the private sector. This finding suggests that curriculum designers should consider sector-specific approaches to technology integration, potentially emphasizing different applications depending on the target employment sector of graduates.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe weakest correlations were observed between Job sector type, years of experience, and the various aspects of CPM education, with most correlations being close to zero. This suggested that the respondents' perceptions of the importance of knowledge domains, course lengths, and learning outcomes were not strongly influenced by their demographic characteristics. The correlation analysis revealed several moderate to strong positive correlations among the knowledge domains based on the respondents' perceptions. The strongest correlations were found between project cost management and project financial management (r\u0026thinsp;=\u0026thinsp;0.7), project stages and stakeholder management (r\u0026thinsp;=\u0026thinsp;0.6), and construction contracts and project delivery methods (r\u0026thinsp;=\u0026thinsp;0.6). Other notable correlations included project life cycle and project cost management (r\u0026thinsp;=\u0026thinsp;0.5), construction bidding and construction tendering (r\u0026thinsp;=\u0026thinsp;0.7), and project risk management and project health, safety, security, and environment (r\u0026thinsp;=\u0026thinsp;0.6). The weakest correlations were observed between the historical perspective and most other knowledge domains, with correlations ranging from \u0026minus;\u0026thinsp;0.2 to 0.3. the course lengths also exhibited moderate to strong positive correlations based on the respondents' perceptions. The strongest correlations were found between stakeholder management and people and organizational management (r\u0026thinsp;=\u0026thinsp;0.8), project financial management and organizational structure (r\u0026thinsp;=\u0026thinsp;0.8), and construction procurement and materials and equipment management (r\u0026thinsp;=\u0026thinsp;0.7). Other notable correlations included construction management and construction technology (r\u0026thinsp;=\u0026thinsp;0.5), project delivery methods and project stages (r\u0026thinsp;=\u0026thinsp;0.5), and project integration management and project scope management (r\u0026thinsp;=\u0026thinsp;0.7). The weakest correlations were observed between historical perspective and most other course lengths, with correlations ranging from 0.1 to 0.5. The learning outcomes showed several strong positive correlations based on the respondents' perceptions. The strongest correlations were found between identifying stakeholder needs and investigating, analyzing, and solving project problems (r\u0026thinsp;=\u0026thinsp;0.7), leadership effectiveness and leadership strategies impact (r\u0026thinsp;=\u0026thinsp;0.7), and project scope and integration and project cost management and financial aspects (r\u0026thinsp;=\u0026thinsp;0.7). Other notable correlations included articulating construction industry characteristics and preparing strategies for preliminary activities (r\u0026thinsp;=\u0026thinsp;0.5), defining project manager responsibilities, and employing project regulations and codes (r\u0026thinsp;=\u0026thinsp;0.5), and demonstrating BIM impact and applying HSSE principles (r\u0026thinsp;=\u0026thinsp;0.7). The weakest correlations were observed between recognizing the historical development of construction management and most other learning outcomes, with correlations ranging from \u0026minus;\u0026thinsp;0.1 to 0.5. The correlations among the appropriate content suggestions were relatively weak based on the respondents' perceptions. The strongest correlation was found between the number of CPM courses for undergraduates and credit hours for CPM courses (r\u0026thinsp;=\u0026thinsp;0.5). The weakest correlations were observed between the timeline for integrating CPM courses and the other appropriate content suggestions, with correlations ranging from \u0026minus;\u0026thinsp;0.1 to 0.1. The correlation analysis and visualizations provide valuable insights into the complex relationships between various aspects of technology-enhanced CPM education. These findings highlight the importance of an integrated approach to curriculum design that recognizes the interconnected nature of knowledge domains, learning outcomes, and educational contexts.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003e5.7 Synthesis of Technology Integration Findings\u003c/h2\u003e \u003cp\u003eThe comprehensive analysis of technology-related perceptions, preferences, and correlations reveals a clear consensus on the importance of digital competency development in CPM education. The strong support for multiple technology-enhanced courses (39.4% recommending four courses) distributed throughout the curriculum suggests that educational institutions should move beyond single-course approaches to digital literacy. The preference for focused, in-depth coverage (63.6%) rather than broader, superficial treatment indicates that technology integration should be substantive rather than token.\u003c/p\u003e \u003cp\u003eThe findings demonstrate that Building Information Modeling (69.69% agreement) and digital project management tools (90.91% agreement) are considered essential components of contemporary CPM education. However, the varying recommendations for course lengths suggest flexibility is needed in determining the appropriate emphasis for different technologies based on institutional contexts and program objectives.\u003c/p\u003e \u003cp\u003eThe correlation analyses and visualizations reveal complex relationships between demographic factors, knowledge domains, and curriculum preferences. These insights can guide the development of tailored approaches to technology integration that account for diverse student populations and career trajectories. The preference for later-stage implementation (43.9% favoring 4th-5th year integration) suggests that technology-enhanced learning is most effective when built upon a solid foundation of construction fundamentals.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Digital Competency Development in Construction Project Management Education\u003c/h2\u003e \u003cp\u003eThis study provides significant insights into the integration of educational technology in CPM education, revealing how technology-enhanced learning approaches can transform professional education in undergraduate Civil Engineering and Architecture programs. The findings demonstrate a clear industry consensus on the importance of digital competency development, with particularly strong support for Building Information Modeling (69.69%) and digital project management tools (90.91%). These results align with recent research emphasizing the transformative potential of educational technology in professional disciplines (Becerik-Gerber et al., 2012; Zhao et al., 2022).\u003c/p\u003e \u003cp\u003eThe strong correlation between digital tool proficiency and learning outcomes (Cronbach's alpha 0.93\u0026ndash;0.97) indicates that technology-enhanced learning can effectively support professional skill development when implemented through structured, scaffolded approaches. This finding is consistent with research by Zhang et al. (2019), who found that integrated experiential learning frameworks can significantly enhance project planning capabilities in civil engineering education. The preference for focused digital content delivery (63.6% favoring comprehensive coverage of fewer topics) rather than broader, superficial treatment confirms Cavka et al.'s (2017) conclusion that depth of technological understanding is more valuable than breadth in professional education.\u003c/p\u003e \u003cp\u003eThe analysis revealed that successful digital competency development requires careful consideration of both content selection and pedagogical approach. The varied recommendations for course lengths assigned to technology domains suggest that flexibility is needed in determining appropriate emphasis based on institutional contexts and program objectives. For instance, Building Information Modeling showed the widest distribution of recommended course lengths, with 42.42% suggesting a full chapter while 13.64% recommended just one page. This variation reflects the evolving nature of construction technology and supports Lima et al.'s (2017) assertion that competency development requires tailored approaches rather than standardized implementations.\u003c/p\u003e \u003cp\u003eThe findings also highlight the importance of authentic application in technology-enhanced learning. The learning outcomes receiving strongest support all emphasized practical application of digital tools, with 90.91% of respondents endorsing the ability to utilize tools and techniques for planning and scheduling construction activities. This aligns with Smith et al.'s (2018) conclusion that authentic problem-solving scenarios are essential for bridging the gap between academia and industry in professional education. Educational institutions must therefore prioritize hands-on, project-based learning experiences that allow students to apply digital tools in realistic construction contexts.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Curriculum Design for Technology-Enhanced Learning\u003c/h2\u003e \u003cp\u003eThe survey results provide valuable guidance for curriculum design in technology-enhanced CPM education. The strong preference for multiple dedicated courses (39.4% recommending four courses) rather than a single technology module suggests that digital competencies should be developed progressively throughout the curriculum. This approach aligns with recent research by Wang et al. (2020), who found that sequential BIM implementation across multiple courses yielded superior learning outcomes compared to standalone modules in construction education.\u003c/p\u003e \u003cp\u003eRegarding the timing of technology integration, our findings revealed a clear preference for implementing technology-enhanced courses in the later years of undergraduate programs, with 43.9% recommending the 4th-5th years and 37.9% suggesting the 3rd-4th years. This preference for later implementation contrasts with some approaches in other disciplines but aligns with Peterson et al.'s (2011) finding that construction technology education is most effective when built upon a solid foundation of industry fundamentals. Educational institutions should therefore consider a scaffolded approach that introduces fundamental concepts first, followed by increasingly sophisticated technological applications as students progress through their programs.\u003c/p\u003e \u003cp\u003eThe correlation analysis revealed significant relationships between different knowledge domains, with particularly strong connections between digital competencies and traditional management skills. For instance, project cost management showed strong correlation with project financial management (r\u0026thinsp;=\u0026thinsp;0.7), while construction bidding correlated strongly with construction tendering (r\u0026thinsp;=\u0026thinsp;0.7). These relationships support an integrated approach to curriculum design that weaves digital competencies throughout the program rather than treating them as isolated skills. As Pearce et al. (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) noted, effective construction education requires a carefully balanced approach that combines theoretical knowledge with practical applications and industry insights.\u003c/p\u003e \u003cp\u003eThe findings also highlighted substantial variation in recommended credit hours, with 27.3% suggesting 12 credit hours for CPM-related courses while 15.2% each recommended 6 and 3 credit hours. This diversity reflects the complexity of balancing digital competency development with other curriculum requirements and supports Pikas et al.'s (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) conclusion that construction education must address multiple competing priorities. Curriculum designers must therefore make context-specific decisions about appropriate credit allocation based on program objectives, institutional resources, and student needs.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Theoretical and Practical Implications\u003c/h2\u003e \u003cdiv id=\"Sec18\" class=\"Section3\"\u003e \u003ch2\u003e4.3.1 Theoretical Contributions\u003c/h2\u003e \u003cp\u003eThis study contributes to the theoretical discourse on digital literacy and curriculum design in higher education by operationalizing digital competency as a measurable outcome aligned with technology-enhanced learning environments. Grounded in constructivist and experiential learning theories, findings support the notion that active, scaffolded exposure to digital tools\u0026mdash;such as Building Information Modeling (BIM) and project management software\u0026mdash;enhances student engagement and learning outcomes (C. Kim et al., \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Tan et al., \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). The strong internal consistency between digital competencies and intended learning outcomes (Cronbach\u0026rsquo;s alpha\u0026thinsp;=\u0026thinsp;0.93\u0026ndash;0.97) aligns with recent literature emphasizing the cognitive integration of digital fluency frameworks into curriculum planning (Makhafola et al., \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Yang et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). Moreover, this research supports the theoretical premise that digital curriculum design is most effective when it is modular, contextualized, and aligned with evolving industry practices. By analyzing real syllabi and stakeholder preferences, we extend existing frameworks like the TPACK model and EU DigComp into the domain of construction education, a field often underrepresented in mainstream digital pedagogy research (Su et al., \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2025\u003c/span\u003e; Yan et al., \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2025\u003c/span\u003e). These insights offer a foundation for future theoretical models that integrate domain-specific digital fluency with pedagogical intentionality.\u003c/p\u003e \u003cp\u003eThis study makes several significant theoretical contributions to the understanding of educational technology implementation in professional education. First, the findings extend existing frameworks by demonstrating that technology-enhanced learning must be purposefully aligned with professional competency development rather than treated as a separate educational component. The strong correlations identified between digital competencies and learning outcomes suggest that when properly integrated, technological fluency enhances rather than competes with core professional skills.\u003c/p\u003e \u003cp\u003eSecond, the research advances theoretical understanding of professional education by proposing a structured, scaffolded approach to technology integration that balances foundational knowledge with advanced digital applications. This framework challenges conventional approaches that either separate technical skills from theoretical content or treat technology as supplementary to core professional knowledge. As Buckley and Lee (2021) observed, the most effective professional education programs combine curricular with extracurricular development opportunities to create well-rounded graduates.\u003c/p\u003e \u003cp\u003eThird, the findings contribute to theoretical models of curriculum design by highlighting the importance of sector-specific and experience-level considerations in technology integration. The surface plot (Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e9\u003c/span\u003e) showing differential perceptions across public and private sectors suggests that universal approaches to digital competency development may be less effective than tailored implementations. This insight extends Ramazani and Jergeas' (2015) work on contextualized professional development by emphasizing the need for customized educational strategies.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec19\" class=\"Section3\"\u003e \u003ch2\u003e4.3.2 Practical Implications\u003c/h2\u003e \u003cp\u003eFrom a practical standpoint, the findings provide actionable guidance for curriculum designers and educators in construction disciplines. The identified preference for multiple technology-enhanced courses (39.4% recommending four courses) suggests that institutions should revise traditional single-course approaches to digital competency development. Curriculum designers should consider implementing a progressive sequence of technology-enhanced courses that introduces increasingly complex digital applications as students advance through their programs.\u003c/p\u003e \u003cp\u003eThe results highlighting strong support for Building Information Modeling (69.69%) and digital project management tools (90.91%) indicate that educational institutions should prioritize these technologies in curriculum development. However, the emphasis should be on authentic application rather than theoretical knowledge, with hands-on projects that mirror industry practices. As Clevenger et al. (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) noted, construction education is most effective when it bridges theory and practice through applied learning experiences.\u003c/p\u003e \u003cp\u003eFor faculty development, the findings underscore the importance of ongoing training in educational technology and industry-standard digital tools. Institutions should invest in faculty development programs that enhance educators' abilities to design and implement technology-enhanced learning experiences. This recommendation aligns with Eiris Pereira and Gheisari's (2019) conclusion that faculty expertise is a critical factor in successful technology integration in construction education.\u003c/p\u003e \u003cp\u003eFor industry stakeholders, the research highlights the need for continued collaboration with educational institutions to ensure that curriculum design reflects current technological practices and emerging trends. Industry-academia partnerships can facilitate authentic learning experiences that prepare graduates for the digital demands of contemporary construction environments. This approach supports Jackson et al.'s (2023) emphasis on industry-aligned capabilities frameworks in professional education.\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Information Processing and Technology Integration in Construction Education\u003c/h2\u003e \u003cp\u003eFrom an information processing perspective, the findings reveal significant implications for how educational technology enhances knowledge acquisition and application in construction education. The strong preference for focused digital integration (63.6% favoring comprehensive coverage of fewer topics) suggests that deep processing of technological content is more valuable than surface-level exposure across multiple platforms. This insight aligns with information processing theory, which emphasizes depth of cognitive engagement as a key factor in effective learning (Acharya et al., 2017).\u003c/p\u003e \u003cp\u003eThe correlation analysis revealed that technology-related knowledge domains and learning outcomes form interconnected networks rather than isolated components. This finding supports distributed information processing models, where knowledge is constructed through connections between concepts rather than through discrete units. Educational technology can enhance these connections by providing visual representations, interactive simulations, and collaborative platforms that make abstract construction concepts more concrete and accessible.\u003c/p\u003e \u003cp\u003eThe findings also highlight the importance of sequencing in information processing, with most respondents (43.9%) preferring to integrate technology-enhanced courses in the later years of undergraduate programs. This preference suggests that effective information processing in construction education requires establishing fundamental conceptual frameworks before introducing complex technological applications. As Torres et al. (2019) noted, project-based learning approaches that progressively introduce technology can significantly enhance information retention and application in construction education.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Alignment with Information Processing and Management in the Digital Era\u003c/h2\u003e \u003cp\u003eIn educational technology research, baseline comparisons typically involve evaluating proposed instructional strategies or tools against state-of-the-art (SOTA) pedagogical models or existing curriculum frameworks. However, the nature of this study\u0026mdash;focused on surveying educational stakeholders and analyzing real-world syllabi\u0026mdash;does not involve the implementation or benchmarking of a novel learning algorithm or digital intervention. Instead, our approach emphasizes empirical curriculum mapping and stakeholder-driven preferences, aiming to develop a grounded framework for digital competency integration within CPM education.\u003c/p\u003e \u003cp\u003eWhile no experimental baselines were used, the study\u0026rsquo;s findings were interpreted in light of established frameworks such as digital literacy models (Yang et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), AI-in-education reviews (G. Liu et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2025\u003c/span\u003e), and recent trends in higher education digitalization (Zhao \u0026amp; Zhou, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). These references served as conceptual baselines to inform our analysis and ensure the recommendations are aligned with contemporary discourse on technology-enhanced learning. Future studies could build on our curriculum-level insights by piloting and quantitatively benchmarking technology-enhanced CPM modules against these SOTA frameworks.\u003c/p\u003e \u003cp\u003eThis research directly addresses the evolving information processing challenges in construction education within the context of rapid digital transformation. A well-balanced curriculum that emphasizes the most critical domains while providing adequate coverage of other relevant topics will best prepare students for successful careers in CPM (Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e10\u003c/span\u003e). The findings demonstrate how educational technology can enhance information management capabilities in professional education, preparing graduates for technology-driven construction environments. By identifying the most valued digital competencies and preferred implementation approaches, our study provides evidence-based guidance for optimizing information processing in construction education.\u003c/p\u003e \u003cp\u003eThe strong support for digital project management tools (90.91%) highlights their central role in contemporary information processing within construction contexts. As highlighted in our findings, digital competencies are increasingly becoming the primary determinant of project success in construction environments. Educational institutions must therefore ensure that graduates are proficient in using these tools to gather, analyze, and communicate project information effectively (Cavka et al., 2017). The emphasis on digital information management aligns with contemporary understanding of how technology transforms information processing in professional contexts.\u003c/p\u003e \u003cp\u003eThe findings on technology integration preferences also have significant implications for information management in construction education. The preference for multiple courses (39.4% recommending four courses) suggests that information processing skills should be developed progressively, with increasing complexity as students advance. This approach aligns with research on scaffolded learning in construction education (Wang et al., 2020), which demonstrates that sequential skill development yields superior professional outcomes compared to concentrated technology-focused modules. This structured approach allows for the development of information management capabilities, from basic data handling to sophisticated analytical applications.\u003c/p\u003e \u003cp\u003eThe correlation analysis revealing strong relationships between digital competencies and learning outcomes (Cronbach's alpha 0.93\u0026ndash;0.97) supports the argument that information processing capabilities serve as the foundation for broader professional competencies in technology-rich construction environments (Smith et al., 2018). Construction programs emphasizing integrated information management skills through multiple technology-enhanced courses can produce graduates with higher problem-solving capabilities in complex digital environments (Zhang et al., 2019). These findings highlight the need for educational approaches that emphasize not just technological tools but the underlying information processing frameworks that enable effective decision-making in contemporary construction practice.\u003c/p\u003e \u003cp\u003eThe importance of balancing theoretical knowledge with practical digital applications, as indicated by respondents' preference for focused content delivery (63.6% favoring comprehensive coverage of fewer topics), aligns with research on cognitive load in construction education (Peterson et al., 2011). Deep information processing of core digital competencies yields superior professional outcomes compared to superficial exposure to a broader range of technologies. This approach ensures that graduates can effectively process, analyze, and apply construction information using industry-standard digital tools, addressing the primary concerns regarding information management in professional contexts (Lima et al., 2017).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e4.6 Limitations and Future Research Directions\u003c/h2\u003e \u003cp\u003eDespite its contributions, this study has several limitations that provide opportunities for future research. First, the sample size (N\u0026thinsp;=\u0026thinsp;66), while adequate for the analytical approaches employed, could be expanded in future studies to include more diverse stakeholders. Second, the cross-sectional design captures perceptions at a single point in time, limiting insights into how technology integration preferences evolve with changing industry practices. Longitudinal studies tracking the implementation and outcomes of technology-enhanced curricula would provide valuable additional insights.\u003c/p\u003e \u003cp\u003eFuture research should explore the long-term impact of technology-enhanced learning on graduate employability and professional practice. Studies comparing the workplace performance of graduates from technology-rich versus traditional programs would provide valuable evidence of educational outcomes. Additionally, research examining specific pedagogical approaches for different digital technologies would help refine implementation strategies for various tools and platforms.\u003c/p\u003e \u003cp\u003eAs educational technology continues to evolve, maintaining adaptable frameworks for digital competency development will be crucial. Future studies should investigate emerging technologies such as artificial intelligence, extended reality, and digital twins, assessing their potential applications in construction education. Research on effective faculty development programs for technology integration would also address an important gap identified in this study.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eThis study provides significant insights into the transformative role of educational technology in Construction Project Management education within higher education contexts. The integration of digital tools and technology-enhanced learning approaches demonstrates a paradigm shift in how professional competencies are developed in undergraduate programs. Our findings reveal that successful technology integration requires careful consideration of pedagogical approaches, digital literacy development, and industry alignment.\u003c/p\u003e \u003cp\u003eThe study's mixed-methods analysis highlights the importance of structured technology integration across the curriculum, with 63.6% of respondents favoring focused digital competency development through multiple courses. The strong correlation between digital tool proficiency and learning outcomes (Chronbach's alpha 0.93\u0026ndash;0.97) suggests that technology-enhanced learning can effectively support professional skill development. Particularly significant is the widespread support for digital project management tools (90.91%) and Building Information Modeling (69.69%), indicating the critical role of authentic digital experiences in professional education.\u003c/p\u003e \u003cp\u003eFor educational technology implementation, our findings emphasize the need for flexible, scaffolded approaches that balance theoretical knowledge with practical digital competencies. The research suggests that successful technology integration in professional education requires institutional support, faculty development, and continuous alignment with evolving industry practices. The timing and sequencing of technology-enhanced courses, with 43.9% preferring integration in later years, indicates the importance of building foundational knowledge before advanced digital applications.\u003c/p\u003e \u003cp\u003eThese insights contribute to the broader discourse on educational technology in professional education, offering evidence-based guidance for curriculum design and implementation. Future research should explore the long-term impact of technology-enhanced learning on graduate employability and professional practice. As educational technology continues to evolve, maintaining adaptable frameworks for digital competency development will be crucial for preparing graduates for technology-driven professional environments.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors confirm that they have no conflicts of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe de-identified dataset used in this study is available from the corresponding author, Dr. Saleh Alsulamy ([email protected]), upon reasonable request. Public sharing is restricted to protect participant confidentiality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study was approved by the Research Ethics Committee at King Khalid University (Approval No. ECM#2024-3105), conducted in accordance with relevant ethical guidelines and regulations, and the clearance certificate.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all participants prior to data collection. Participants were fully informed about the purpose of the study, their voluntary involvement, and their right to withdraw at any time. Anonymity and confidentiality were strictly maintained throughout the research process.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants provided consent for the publication of anonymized data collected during the study. No personally identifiable information has been disclosed in the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgment\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors extend their appreciation to the Deanship of Research and Graduate Studies at King Khalid University for funding this work through small group research under grant number RGP.2/121/46.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by King Khalid University [Project RGP.2/121/46]\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eContribution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eM.A\u003c/strong\u003e Conceptualization, methodology development, supervision, data interpretation, and final manuscript review and approval.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eS.A\u003c/strong\u003e Data collection, data analysis, preparation of results, and drafting of the initial manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eA.A.S\u003c/strong\u003e Literature review, validation, technical editing, and refinement of the manuscript before submission.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAbbas, A., Din, Z. 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This mixed-methods study investigates the integration of educational technology within Construction Project Management (CPM) education across undergraduate Civil Engineering and Architecture programs. Data were collected from 66 global educational stakeholders through surveys and 20 university CPM course syllabi. The study aims to (1) identify essential digital competencies, (2) examine current technology-enhanced teaching practices, (3) explore curriculum design preferences, and (4) provide recommendations for digital curriculum integration. Survey results indicate overwhelming support for embedding digital project management tools (90.91%) and Building Information Modeling (BIM) (69.69%) into CPM curricula. Reliability analysis revealed strong internal consistency (Cronbach's alpha\u0026thinsp;=\u0026thinsp;0.93\u0026ndash;0.97) among digital competency domains and learning outcomes. Most participants (63.6%) prefer a distributed approach to digital skill development across multiple courses, with 39.4% recommending four or more specialized technology-enhanced CPM courses. Syllabus analysis revealed inconsistency in digital tool adoption, with successful programs exhibiting structured, scaffolded integration of technology and industry-aligned competencies. This research contributes a practical framework for implementing digital technologies in construction education, emphasizing the need for curricular flexibility, pedagogical innovation, and alignment with evolving industry requirements. The findings underscore the value of intentional curriculum design to foster digital literacy, enhance learner engagement, and bridge the gap between theoretical knowledge and professional practice.\u003c/p\u003e","manuscriptTitle":"Integrating Digital Technologies in Construction Education: A Mixed-Methods Study of Curriculum Design and Learning Outcomes in Project Management","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-01-16 09:05:26","doi":"10.21203/rs.3.rs-8337804/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"ba128f82-27e8-459c-a962-5eabd0e883b3","owner":[],"postedDate":"January 16th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":61023299,"name":"Social science/Education"},{"id":61023300,"name":"Business and commerce/Information systems and information technology"},{"id":61023301,"name":"Physical sciences/Mathematics and computing"},{"id":61023302,"name":"Social science/Science technology and society"}],"tags":[],"updatedAt":"2026-02-09T14:40:21+00:00","versionOfRecord":[],"versionCreatedAt":"2026-01-16 09:05:26","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8337804","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8337804","identity":"rs-8337804","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}