Construction management (CM) is a crucial discipline within civil engineering, and it addresses the complexities of modern projects through a combination of technical, managerial, and organizational skills. The construction industry is evolving rapidly due to urbanization, technological advancements, and increased project complexity, leading to a significant demand for effective management practices. This trend is evident in the growing number of academic programs and student enrollments in CM that are aligned with the industry’s demand. However, the current academic curricula do not meet the existing needs, and ongoing updates are necessary to equip students with the skills required to excel as CM professionals, focusing on construction methods, materials, budgeting, scheduling, quality management, safety, and leadership. This study implements a strategic plan to prepare future professionals for the challenges of an increasingly complex construction industry. At xxx University, we introduced innovative modules focusing on Machine Learning (ML), an essential skill for effective data analysis, and Multi-Objective Optimization (MO), which is crucial for informed decision-making in complex scenarios. These modules utilize engaging videos designed to facilitate understanding while emphasizing the real-world applications of the content. We tested two hypotheses: first, that CM professionals lack proficiency in data analytics, including MO and ML; second, that a video-based intervention can effectively enhance the knowledge of both undergraduate and graduate students in these areas. To evaluate the impact of these modules on CM students' knowledge and skills, we designed two surveys: the first administered before viewing the instructional videos to assess baseline knowledge, and the second conducted afterward to measure knowledge gains. While this study contributes to the development of a comprehensive CM program at xxx University, it also offers valuable insights for other institutions seeking to enhance their curricula to better meet the evolving demands of CM students in an increasingly complex world.
The full paper will be available to logged in and registered conference attendees once the conference starts on June 22, 2025, and to all visitors after the conference ends on June 25, 2025