encompass extensive activities, from refining thesummer camps for high school students to conducting monthly advisor listening sessions andsurveys to understand and meet student needs. Furthermore, introducing niche areas for eachacademic advisor has fostered their professional growth and contributed to improved studentsuccess.This paper will delve into the comprehensive details of these initiatives. It serves as a valuableresource for institutions seeking to enhance their student support services, providing separateinsights into the spheres of recruitment, retention, and, most importantly, student success withinthe College of Engineering at Tennessee Tech University.1. IntroductionThe importance of student success support for engineering
engineeringeducation by establishing innovation infrastructures [1]. These initiatives focus on enhancingstudents' innovation competencies, as summarized in the framework researched in [2], whichcomprises skills such as problem-solving, design thinking, creativity, project management,prototyping, teamwork, and leadership, etc. One effective pedagogical approach in this regard ischallenge-based learning (CBL) [3], which engages students in the identification, analysis, design,and implementation of solutions to open-ended sociotechnical problems [4]. CBL is inherentlymultidisciplinary, drawing on diverse perspectives and skills required in product development [5]and design thinking [6]. In complement to the traditionally theoretical richness of
expectations set forth by ABET.IntroductionThe landscape of undergraduate engineering management programs in the United States hasexperienced an evolution captured by the Accreditation Board for Engineering and Technology's(ABET) recognition of the need for traditional engineering disciplines alongside a morecomprehensive discipline that integrates leadership, communication, and teamworkcompetencies as seen in (Figure 1. Engineering Managers manufacture fiscal and enterprisevalue in creating, designing, and implementing technical projects, products, or system solutions[1]. The West Point Engineering Management (EM) Program embodies this approach. It ishoused in the Department of Systems Engineering at the United States Military Academy(USMA) as one of
, which are all vital in their respective fields.IntroductionThe Professional Science Master's (PSM) degree arose in the late 1990s to fill a gap betweenoverqualified PhDs and underprepared undergraduates in science fields [1]. PSM programsprovide graduate-level science training plus professional skills valued by employers [2]. Theadvantages of PSM degrees include career preparation, practical experience, high employability,networking opportunities, specialized knowledge, and lower cost versus a PhD. The PSM alignswith best practices proposed for master's degrees by higher education organizations [3], [4], [5].MTSU's PSM program (MSPS degree) meets the requirements for formal PSM affiliation [6].The interdisciplinary MSPS integrates science and
programs, achieving high effectiveness andfosters the achievement of set goals.IntroductionEfficiently managing large educational STEM programs, particularly interdisciplinary projects,requires a harmonious blend of team dynamics and individual personality strengths [1]. Theseprojects bring together experts from divergent disciplines to collaborate towards common goals,making the team set up a critical determinant of success. While much attention has been givento factors like team composition, size, and tenure, the impact of team members’ personality traitson overall team effectiveness remains unexplored.Interdisciplinary Science, Technology, Engineering, and Mathematics (STEM) projects involvecollaboration across multiple disciplines to address
the current usage and perceptions of industryprofessionals about AI tools in project management tasks. The specific research questions are:(1) What factors influence the usage of AI tools in project management practices? (2) How areproject managers currently using AI tools? (3) What are their perceptions of these tools?Methods: A survey was designed to gauge industry professionals' usage and perceptionsregarding AI's tools in project management tasks and included questions to gather demographicdata. This survey was shared across multiple project management groups on LinkedIn over athree-month duration, attracting 113 responses. A cleaning process was implemented to removeany invalid responses. A correlational analysis was performed on the
Management Science and Engineering from Stanford University, and her Ph.D. in Management from UC Irvine. ©American Society for Engineering Education, 2024 Iterative Learning: Using AI-bots in Negotiation TrainingNegotiation skills are essential in management education and in engineering practice. Traditionalteaching methods, centered around role-playing activities. have often struggled to fully engagestudents or provide the personalized feedback necessary for mastering such a complex skill set.To addressing this pedagogical gap, I developed AdVentures with chatGPT [1] by leveragingartificial intelligence to create a dynamic, interactive learning experience that adapts to eachstudent's needs and performance
practice. The details of the methodology are shown in Figure 1. Stage I - Planning the review Phase 0 Identification of the need for a review Phase 1 Preparation of a proposal for a review Phase 2 Development of a review protocol Stage II - Conducting a review Phase 3 Identification of research Phase 4 Selection of studies Phase 5 Study quality assessment Phase 6 Data extraction and monitoring progress Phase 7 Data synthesis Stage III - Reporting and dissemination Phase 8 The report and recommendations
educational curricula. This study assesses the implications of AI integrationwithin these subfields and its potential impact on students' skill development and comprehension.1 IntroductionIntegrating Artificial Intelligence (AI) into engineering management education significantlytransforms pedagogical methodologies. This study focuses on two primary impacts of AI in thisfield:1. Revolutionizing Learning Paradigms: This study explores how generative AI, capable of creating diverse and interactive content, redefines the educational landscape. This technology facilitates personalized learning experiences and introduces innovative methods for knowledge dissemination, enhancing student engagement and understanding.2. Challenges to Academic Integrity
(Practice Paper Category)AbstractTo meet the challenges and opportunities of educating new generations of engineering leadersfor jobs of the future, Engineering Management programs must evolve with a strategy thatintegrates academic education with workplace application. That strategy must address thechanging demographics of technical industries and their workforces. We can meet that challengeby unifying technical leadership fundamentals into an applied experience, internalizingengineering management coursework with a real-life technical leadership scenario that isapplicable across industries.Education research[1] shows that working professional students learn best through case studies,active learning, and project-based activity. This paper