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Description
Owner organizations in the architecture, engineering, and construction (AEC) industry are presented with a wide variety of project delivery approaches. Implementation of these approaches, while enticing due to their potential to save money, reduce schedule delays, or improve quality, is extremely difficult to accomplish and requires a concerted change management

Owner organizations in the architecture, engineering, and construction (AEC) industry are presented with a wide variety of project delivery approaches. Implementation of these approaches, while enticing due to their potential to save money, reduce schedule delays, or improve quality, is extremely difficult to accomplish and requires a concerted change management effort. Research in the field of organizational behavior cautions that perhaps more than half of all organizational change efforts fail to accomplish their intended objectives. This study utilizes an action research approach to analyze change message delivery within owner organizations, model owner project team readiness and adoption of change, and identify the most frequently encountered types of resistance from lead project members. The analysis methodology included Spearman's rank order correlation, variable selection testing via three methods of hierarchical linear regression, relative weight analysis, and one-way ANOVA. Key findings from this study include recommendations for communicating the change message within owner organizations, empirical validation of critical predictors for change readiness and change adoption among project teams, and identification of the most frequently encountered resistive behaviors within change implementation in the AEC industry. A key contribution of this research is the recommendation of change management strategies for use by change practitioners.
ContributorsLines, Brian (Author) / Sullivan, Kenneth (Thesis advisor) / Wiezel, Avi (Committee member) / Badger, William (Committee member) / Arizona State University (Publisher)
Created2014
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Description
The 21st century will be the site of numerous changes in education systems in response to a rapidly evolving technological environment where existing skill sets and career structures may cease to exist or, at the very least, change dramatically. Likewise, the nature of work will also change to become more

The 21st century will be the site of numerous changes in education systems in response to a rapidly evolving technological environment where existing skill sets and career structures may cease to exist or, at the very least, change dramatically. Likewise, the nature of work will also change to become more automated and more technologically intensive across all sectors, from food service to scientific research. Simply having technical expertise or the ability to process and retain facts will in no way guarantee success in higher education or a satisfying career. Instead, the future will value those educated in a way that encourages collaboration with technology, critical thinking, creativity, clear communication skills, and strong lifelong learning strategies. These changes pose a challenge for higher education’s promise of employability and success post-graduation. Addressing how to prepare students for a technologically uncertain future is challenging. One possible model for education to prepare students for the future of work can be found within the Maker Movement. However, it is not fully understood what parts of this movement are most meaningful to implement in education more broadly, and higher education in particular. Through the qualitative analysis of nearly 160 interviews of adult makers, young makers and young makers’ parents, this dissertation unpacks how makers are learning, what they are learning, and how these qualities are applicable to education goals and the future of work in the 21st century. This research demonstrates that makers are learning valuable skills to prepare them for the future of work in the 21st century. Makers are learning communication skills, technical skills in fabrication and design, and developing lifelong learning strategies that will help prepare them for life in an increasingly technologically integrated future. This work discusses what aspects of the Maker Movement are most important for integration into higher education.
ContributorsWigner, Aubrey (Author) / Lande, Micah (Thesis advisor) / Allenby, Braden (Committee member) / Bennett, Ira (Committee member) / Arizona State University (Publisher)
Created2017
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Description
The higher education sector is always changing and seeks for robust methodologies to make education more effective and produce higher quality products which are the future professionals. While each student has different preference in learning, numerous forms of instructional strategies are adopted to engage students in varied ways. Existing

The higher education sector is always changing and seeks for robust methodologies to make education more effective and produce higher quality products which are the future professionals. While each student has different preference in learning, numerous forms of instructional strategies are adopted to engage students in varied ways. Existing literature has studied the impacts of various teaching strategies on students’ performance. Previous studies did not figure out if personal characteristics such as honestly, emotionality, etc. have any impacts on the students’ academic performance. This master thesis uses the detailed information gathered through surveying construction students and analyses such data to determine the relationship between various personal factors and understand if there is any relation between students’ academic performance and personal characteristics. This work has used HEXACO factor scales and Emotional Intelligence (EI) as a basis of its analysis. Results of this analysis indicated that there is no significant correlation between students’ academic performance and HEXACO and EI criteria. Although the analysis process tried to provide the most accurate and robust results, but findings could potentially be affected by a number of factors such as excluding some survey responses from data analysis due to confusing responses or being outlier.
ContributorsDadvar, Atefeh (Author) / Sullivan, Kenneth (Thesis advisor) / Smithwick, Jake (Committee member) / Lines, Brian (Committee member) / Arizona State University (Publisher)
Created2017