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Background: While improved student engagement has been highlighted as an essential goal and a major outcome of Problem and Project-Based learning (PBL), little empirical evidence has been provided regarding types and forms of student engagement. Material and method: The study explored forms of student engagement in PBL settings, drawing on empirical data of observations and group interviews with 23 project teams (116 students) in four different PBL undergraduate civil engineering courses at Qatar University. Results: The study identified four patterns of student engagement in a PBL setting. Participants reported significant indicators of the first two patterns - engagement as autonomy and as connection. Regarding the other two indicators, namely relational and emotional engagement, they reported positive yet slightly fewer indicators. Three factors were identified that influenced student engagement in a project teams, namely PBL types and its appropriateness to the nature of the course, students' prior experiences with PBL, and team dynamics. Conclusions: These results facilitate the establishment of an institutional framework supporting a progressive approach to embracing PBL. In this framework PBL implementation begins with diverse practices at the course level and has systemic change as its ultimate goal. This framework particularly aims to support an institutionalized approach to transition to PBL in a socio-cultural context (e.g., a non-western context) where instructors are as the primary and authoritative source of knowledge. The overall outcome of the study supports management of change from a lecture-based mode to PBL in a non-western context.

This study examined engineering students' initial readiness to transition to emergency online learning in response to COVID-19 in Qatar. A theoretical framework is proposed for understanding the factors influencing students' readiness for change. Sequential explanatory mixed-method research was conducted, with 140 participants completing an online survey, of which 68 also contributed written reflections and 8 participated in semi-structured interviews. Exploratory factor analysis displayed a four-factor structure, including initial preparedness and motivation for online learning, self-efficacy beliefs about online learning, self-directed learning online, and support. The qualitative outcomes supported the four factors and provided further insight into their varied and nuanced manifestation. In accounting for the perceived impact of the factors on readiness, significant differences were identified regarding pedagogical mode, with students enrolled in PBL courses reporting higher readiness than those from non-PBL courses. The practical implications for preparing students for future emergency online learning are discussed.

Background: This study investigated the development of engineering students' approaches to learning and views on collaboration in a PBL environment. Material and methods: An explanatory mixed research approach was employed with participants from four PBL-implementing engineering courses in Qatar and China. 197 students responded to two surveys, and 168 students participated in group interviews. Results: While the study reveals increased adoption of deep approaches to learning on team projects, little influence on surface approaches to learning was found. The study also provides evidence supporting the positive relationship between students' adoption of deep learning approaches and their acknowledgement of values of collaboration in teamwork. Conclusions: This study suggests that while PBL characteristics may support deep learning, certain factors may underpin surface learning, including a feeling of insecurity during first experiences with it, lack of skills, and assessment methods that favor surface learning. Further efforts on engaging students with PBL may benefit both deep learning and team effectiveness.

Background: Few studies have reported how students enact learner agency in a team setting or examined what elements of team settings students perceive as more supportive of their learning in problem- and project-based learning (PBL) processes. Purpose: This study explores how engineering students perceive their enactment of learner agency, particularly which aspects of the PBL process they find most important. Method: Thirty-nine students from two PBL civil engineering courses in Qatar participated in the study. Q methodology was chosen for both qualitative and quantitative data collection and analysis. A 40-item Q set based on a theoretical model of learner agency was used. Results: Eight significantly different student viewpoints emerged from the Q methodological factor analysis, indicating a range of individual perceptions of learner agency. Intrapersonal dimensions were highlighted by three of the eight viewpoints, behavioral dimensions were underlined by seven viewpoints, and environmental dimensions were valued by all viewpoints. Conclusion: While the results reveal a wide range of individual experiences with learner agency across the three dimensions, students addressed self-directed learning aspects both actively and passively, suggesting that many participants still value instructors' roles of providing direct instruction and authorized knowledge in PBL. The results highlight the need for more awareness of learner agency and more opportunities for students to enact learner agency by increasing PBL knowledge, skills, and efficacy. Q methodology can contribute to engineering education research by providing new theoretical and empirical insights into learners' subjective understanding of agency in a PBL setting as a complex system.

This qualitative longitudinal study explored three engineering instructors' professional agency in implementing project-based learning (PBL), including multiple sets of data (18 interviews, observations, and written reflections spanning three semesters). The results show that the instructors' care for students, interest in pedagogical innovation, and efforts in professional learning supported their confidence in stance, sense of agency, and competence in PBL practice. The efficacy and strong beliefs of the instructors further supported their agency-in-action regarding how they acted to influence their teaching by negotiating both its content and conditions. The study also revealed how individual resources and social conditions frame the enactment of professional agency and how the instructors developed agency and strategies to overcome challenging issues at work. Although they developed different types of agency, they demonstrated the same attitude towards resilience and negotiation for autonomy as well as the same engagement in self-empowerment and transforming their agentic competence into educational leadership.

Digital transformation (DT) is revolutionizing building facility management (FM) by streamlining operations, maximizing resources, and increasing performance. FM firms prioritize DT to stay competitive as speed and efficiency become more crucial in the corporate context. Traditional FM methods like manual record-keeping and reactive maintenance cannot meet recent corporate needs. Modern technologies such as IoT, AI, digital twins, and data analytics enable real-time building asset monitoring and optimization. This paper evaluates the digital transformation readiness level index of building facility management (DTRLIBFM), which includes critical success factors for DT development, using structural equation modeling (SEM). DTRLIBFM model determines the importance of key factors that contribute to the success of digital transformation initiatives, specifically focusing on the DT readiness level index of building facility management. Expert interviews and an intensive literature review were employed to identify the critical success factors for the DTRLIFMB. The Delphi technique was employed to validate these factors with 13 highly experienced professionals, and they were subsequently appraised for significance through an online questionnaire that was circulated to industry experts. To quantitatively evaluate the interconnectedness of different elements of DTRLIFMB and establish the impact of each construct on the overall digital transformation, data from 220 participants from around the world were analyzed using (SEM). The evaluation included reliability, validity, hypothesis testing, multivariate normality, and goodness-of-fit indexes. The DTRLIBFM model, with 20 indicators in three constructs, explains how DT readiness affects a building's digitalization importance level. The research provides governments, organizations, contractors, consultants, suppliers, subcontractors, and facility managers with a current DT index and DT roadmap for building facility management. [ABSTRACT FROM AUTHOR]

Construction projects play a vital role in the global economy. However, the construction industry still lags in the adoption of digital technologies which have the potential to alleviate inefficiencies. There is also a lack of construction professionals with skills to implement digital technologies, and the industry is plagued by inadequate research and development (R&D) and low productivity. This paper applies the Digital Transformation Readiness Level Index in Building Construction (DTRLIIBC) to investigate digital transformation in the construction industry, and specifically in the construction phase, by identifying technologies, alternatives, policy incentives to ensure best practices, and infrastructure needed to smoothly implement digital technologies. A survey was distributed to executive managers, department managers, project managers, senior engineers, and supervisors in the construction industry. Interviews were also conducted with 13 experts with more than 20 years of experience, using the Delphi method to ensure the validity and reliability of the factors identified as significant based on their experience and perspectives. This study thus assessed potential factors related to digital transformation, along with identifying factors enabling the use of the DTRLIIBC itself. Structural Equation Modeling (SEM) was employed to identify causal relationships among the variables while minimizing measurement errors, as SEM was considered a multiple regression analysis to improve the efficiency of the model. To ascertain the model's robustness and stability, a comprehensive evaluation was conducted that included tests for multivariate normality conformance, validity and reliability assessments, and accuracy evaluations to improve overall performance in the construction industry. The benefit of implementing SEM is its ability to provide a clear decision-making alternative as well as a potential vision for construction industry firms to improve efficiency and productivity in construction projects. [ABSTRACT FROM AUTHOR]

This study presents the development of a comprehensive model for evaluating the level of readiness of buildings for digital transformation during the pre-construction phase. The proposed model utilizes structural equation modeling (SEM) and includes a full list of key factors for achieving success. This tool is designed to support industry stakeholders in assessing operational efficiency in terms of digital transformation readiness in the pre-construction phase (DTRPC) and analyze the effectiveness and limitations of DTRPC across various management levels. Key success factors were identified through interviews with experts and a review of the relevant literature. These variables were then validated through two rounds of the 8 Delphi technique, which included the input of 13 highly qualified experts. Finally, an online questionnaire was disseminated to industry professionals, who assessed the factors' relative levels of significance. Questionnaire responses were collected from a sample of 300 individuals from different professional fields. SEM was then used to quantitatively analyze the relationships between the various components of the DTRPC success factors. The goal was to determine the impact of each construct on the overall level of readiness. The model underwent a thorough evaluation to determine its strength and stability across several parameters, including accuracy, conformity to multivariate normalcy, and reliability and validity. A hypothesis analysis was also conducted. The collected data were used to develop the proposed DTRPC model, consisting of 30 essential performance indicators grouped into four categories. The use of SEM uncovered a significant correlation between the operational indicators of these critical factors and the construct groups, as well as the influence of effective DTRPC constructs on overall project performance. This research expands the current knowledge by identifying important indications for evaluating the success of the DTRPC model and using them to create a comprehensive global SEM that can be used as a tool for measuring readiness at the pre-construction stage. This has the potential to provide essential assistance to organizations, project managers, and policymakers in making informed decisions. [ABSTRACT FROM AUTHOR]

The construction project information for FM team control and maintenance is vital. However, current practices indicate significant data drops during the handover stage, leading to rework during FM systems integration of inaccurate, delivered information. Although challenges in BIM implementation are well studied, there is a current lack of best practices from FM industry experts highlighting challenges with a specific focus on the areas of the data drop. Therefore, the aim is to develop a framework that can reduce data loss and improve data management. The objectives include robust literature review on challenges of information loss during handover phase, management and frameworks; Adopting case study and workshops to identify information loss challenges, framework development and validation with industry experts. This paper adopted a grounded theory approach to explore literature and conducted case studies, including a series of semistructured interviews and a workshop with FM industry experts. The findings show the areas and causes of information loss and how to manage them through the developed information loss management framework (ILMF). Practical Applications: With the start of any type of project, planning and establishing rules from the beginning facilitates the smooth transition between different phases. Similarly, in construction projects, this research provides guidelines on how facility managers can manage information loss when exchanged through projects' stages. Furthermore, with the continuing advancements in the construction world, the facility management should be equipped with management and leadership guidelines as presented in the proposed framework to reduce data loss during handover. However, there are cost and contractual issues that prohibit any involvement of the facility manager in early project stages. The results of this study provide an identification of professional practices do's and do not's that facilitate the management and development of projects with the support of the latest technologies in the market. Ultimately, developing a guide that adapts international standards. The study's contribution to knowledge includes the development of a new information loss management framework that adopts BIM and ISO standards after exploring the existing data management frameworks in the literature that lack data loss management as a focus. The framework works as a guide for various stakeholders such as designers, contractors with a focus on FM to facilitates data coordination and management to reduce information loss, its creation and validation were conducted in collaboration with industry experts. Furthermore, its novelty lies in integrating FM role, information management, information loss, address project life cycle, and adopts the ISO 19650 series. [ABSTRACT FROM AUTHOR]

Smart buildings and cities are rapidly emerging as solutions to address the challenges of efficiency, urbanisation, and sustainability in the sector. The study proposes deploying data-driven digital twins for smart buildings by utilising the available building's technology and IT infrastructure to complement and augment existing functions. The digital twin will consist of a core data-driven energy model and a 2D visual representation of the building's systems, with the potential for future evolution into a 3D model. This study aims to present a preliminary investigation into the idea of data-driven digital twins in building management towards enhancing the operations of smart buildings and empowering the concept of smart cities. It is demonstrated on a building on the campus of Qatar University. With an emphasis on the air conditioning systems of the building, considering their substantial contribution to overall energy consumption, the study maintains an open approach to also encompass other energy systems within the buildings, and presents a comparative evaluation between simulation-based and data-driven modelling on the case study, as well as an exploration of various machine learning algorithms that can be used. Furthermore, exploring essential smart applications of the building's data-driven digital twin. Practical Application: The study provides a comprehensive exploration of the practical aspects of deploying data-driven digital twins for smart buildings, addressing challenges related to data collection, model development, integration with building infrastructure, and potential limitations. The paper aims to advance the field of facility management and promote smart and sustainable practices in building operations. By contributing to the existing knowledge in facility services and management, our study offers practical guidance towards optimising building performance, reducing energy consumption, and fostering sustainable urban development. [ABSTRACT FROM AUTHOR]

This study explores engineering students' enactment of collective agency and perceptions of professional identity. Empirical data were drawn from observation and group interviews with 30 engineering students in a civil engineering course using a problem and project-based learning (PBL) approach. Using the technique of quantifying qualitative data, the study identified patterns of agency manifestation in seven domains within project work: (1) motivation, (2) goal setting, (3) planning, (4) project progression, (5) self-reflection and evaluation, (6) team dynamics, and (7) external support and resources. The study identified a significant correlation between the engineering students' collective agency in these seven aspects of their learning process and their project team outcomes based on group-based project grades. Although students reported many reasons for choosing to study engineering, the majority of the students were found to have a general uncertainty regarding their sense of professional identity, suggesting more activities to support the building of professional competences, such as PBL, should be provided at an earlier stage of engineering curricula.

The rapid advancement of digital technology has enabled digital transformation across various sectors, including construction. The construction industry has long been associated with conventional, labor-intensive practices that can adversely influence the entire construction process. However, this culture is changing as key players in the sector are progressively identifying and embracing the vast opportunities and associated benefits of using digital tools and technologies to improve the performance and outcomes of the overall project lifecycle. To this end, this study uses the Delphi technique to identify 70 factors that contribute to the digital transformation of the construction industry, categorizing them into five groups: management, design, technology, policy, and infrastructure. Delphi analysis is used to examine the critical success factors for digital transformation identified in the literature and rate their importance during the preconstruction, construction, and facility management phases. Furthermore, this research results in the introduction of the Digital Transformation Level of Readiness Framework (DTRLF) to help facility management firms, clients, organizations, contractors, and designers comprehend the implementation of digital transformation within their respective domains and support decision-makers in establishing action to adapt related technologies in their respected project phases. [ABSTRACT FROM AUTHOR]

Organizational resilience indicates the capacity of an organization or a system to return to its steady condition, or exceed it, after going through a disruptive event that disrupts its steady condition. Qatar's oil and gas sector has shown remarkable resilience during the COVID-19 pandemic due to its preparedness and readiness to deal with such a disruption. As a lesson learned from the recent COVID-19 pandemic, local governmental institutions need to support national preparedness and resilience to handle emergencies and unpredictable crises by learning from the successful model of Qatar's oil and gas sector. This study presents the key Resilience Engineering Indicators (REIs) that make this sector resilient and validates the six Resilience Engineering indexes or dimensions adopted, which include top management commitment, speaking up culture, learning, awareness, being prepared, and flexibility. The study evaluated the performance of these REIs using a 5-point Likert Scale survey questionnaire based on the relevance to resilience dimensions. The results show ten REIs contributing to the organization's resilience and the top four most important Resilience Dimensions (RDs). Moreover, this is the first study to evaluate and assess the organizational resilience level in Qatar's oil and gas sector. This study's results can be integrated into different organizations' strategies to improve the efforts to enhance the national response to disturbances in governance. [ABSTRACT FROM AUTHOR]

Fast-track construction has recently become the prevailing construction approach globally. It enables owners and developers to make rapid returns on investment through shortened construction periods. This strategy has many effects on the industry; therefore, four groups of factors were studied in this project: (1) financial, (2) logistics and finance, (3) management, and (4) legal. A 22-question survey was distributed to 155 professionals in the construction industry, who evaluated the impact of the stated factors on a 5-point scale. The results revealed a high level of consistency determined through Cronbach's alpha, and a positive correlation was found by Spearman's rank coefficient. The Relative Importance Index was used to rank the factors based the evaluation by the professionals, resulting in the following impact ranking: (1) poor communication among design and construction teams, (2) large amounts of rework, (3) low quality of work by the contractor, (4) design errors, (5) late or insufficient payment according to terms agreed with the client, and (6) unavailability of materials in the market. By providing a quantitative RII model to evaluate fast-track project management performance with the use of corresponding performance indicators, this study will benefit industry practitioners and researchers as it identifies the most significant factors that impact fast-tract project management performance. [ABSTRACT FROM AUTHOR]