during their academic journey. The work alsodelves into different mentoring approaches, including group-based and mentoring by individualfaculty. This study provides the engineering and STEM education community with a deeperunderstanding of the advantages of undergraduate research experiences in enriching STEM andmentoring practices that can increase students' participation and mold their academic andprofessional character.1. IntroductionUndergraduate research plays a significant role in advancing student development in differentdisciplines. It provides students with an opportunity to apply theoretical concepts learned inclassrooms to real-world problems, thus enhancing their critical thinking, problem-solving, andanalytical skills. Through
, and diverse strategies used by universities [1].Craney et al. [2] surveyed 465 undergraduate research participants from varied disciplines andbackgrounds, discovering high satisfaction and significant gains in professional development,deeper subject understanding, and better preparedness for graduate studies and careers. Similarly,Lopatto [3] found that 85% of UR participants in science continued to postgraduate education,with those not pursuing further studies reporting lesser gains. Haddad and Kalaani [4] introduceda model to integrate research into traditional curriculums via summer workshops and designatedcourses, aiming to boost participation through the creation of an Undergraduate Research Office.Lopatto's further research [5
, thereby enabling educators to gain valuable insights to inform effectiveinstructional strategies.IntroductionThe importance of student engagement in the first year of engineering education cannot beunderstated, as it plays a critical role in fostering students' engagement [1]. Ohland [2] discussesthe complexities of engagement and its influence on student perseverance and satisfaction withinthe engineering discipline. The study presents evidence for the imperative of integrativeeducational practices that are sensitive to the challenges unique to early engineering education.These findings underscore the importance of tailored educational strategies and supportmechanisms that cater to the unique challenges faced by novice engineering students
(VTECC). Her research focuses on communication, collaboration, and identity in engineering. ©American Society for Engineering Education, 2024 Understanding Ecosystems of Interdisciplinary Graduate Education through an Ecological Systems ApproachAbstract esponding to decades of calls for interdisciplinary scholars capable of addressing complexRsocietal challenges[1], [2], [3], this conference paper addresses persistent gaps in interdisciplinary graduate education reform. Despite extensive research on transformational interdisciplinary graduate education, little change has been made in reshaping governing funding, policies, and program structures as well as disciplinary
groups, being attuned to emerging globalissues, and having the ability to adapt to a changing world in order to compete in the globalarena [1], [2], [3], [4].Study abroad has been highlighted by the U.S. Department of State as a way to prepare a diversegroup of future Americans leaders to excel in a globalized economy, collaborate internationally,and enhance international diplomacy. In his first address as U.S. Secretary of State, AntonyBlinken remarked that “People-to-people exchanges bring our world closer together and conveythe best of America to the world, especially to its young people” [5]. The U.S. Department ofEducation’s inaugural international education strategy in 2012 emphasized the importance ofglobal competencies in a domestic
engineering faculty’s lack offamiliarity with non-ABET professional skills, like entrepreneurial mindset and cultural agility,the difficulty of making changes in technical classes, and the limitations in assessing professionalskills. The researcher aims for the recommendations derived from this pilot study to raiseawareness of professional skill development within engineering curricula, fostering collaborationwith industry, and stimulating further research into enhancing the engineering curriculum with afocus on these essential skills.IntroductionTo succeed in the 21st-century workplace, engineering graduates need more than technical skillsor risk losing their jobs to automation [1, 2]. Professional skills complement a technicaleducation and are part
inalignment with team science-based strategies. MTS are comprised of individual teams with theirown goals, tasks, and mandates that are interconnected and work collaboratively toward a larger,common goal [1]. Attitudinal (cohesion, trust, commitment), behavioral (coordination,communication, shared leadership), and cognitive (situational awareness, shared mental models)competencies support MTS effectiveness [2], [3]. Multisector MTS are even more complex, asteam members bring aspects of their organizational culture as well as their personal andprofessional lived experiences into the MTS, and if priorities and practices are not well aligned,team function and effectiveness can suffer. Thus, for multisector MTS to work, they must beginwith a foundational
INTRODUCTIONEngineering has a considerable role in addressing many of the challenges facing society. Engineeringschools and the engineering professional bodies have increasingly recognized that for the engineeringdiscipline to reach its full potential, all segments of society must be included. Engineering mustactively engage and help promote the pursuit of engineering education and engineering careers withthose individuals who have been historically under-represented within the field. For example, femaleparticipation in the engineering profession is considerably below the proportion of females in societyat large (Figure 1). As a result of this differential, Engineers Canada launched the 30 by 30 EngineersCanada initiative which aims by 2030 to increase to 30
connections, presentingdata from an external evaluator from the perspective of mentors.IntroductionAlthough more than half of all PhDs are obtained by women, representing a large pool in academia,this women's talent pool has yet to transform into a sustained representation in engineering facultyand leadership positions in academia. Research shows [1], [2] that women and URM facultyencounter various obstacles that set them back from promotion at all stages of their careers and/orremove them from academia. In these regards, the cross-disciplinary collaborations and strongdiverse network connections offer a powerful pathway for individuals from traditionally under-represented groups to make their voices heard, contribute to knowledge creation, and drive
, innovation, and ethical considerations in preparing individuals for thechallenges and opportunities presented by AM. The findings contribute to a deeper understandingof how AM education is evolving to meet the demands of the future.IntroductionA concise overview of AM and its pivotal role in various global industries is imperative toestablish the foundation for AM education [1]. AM is a sequential manufacturing process thatproduces parts in a layer-by-layer fashion [2][3]. AM has seven categories under its umbrella,however, only a few of those categories are suitable for AM education when consideringoperation complexity and cost [1][4]. Those are Material Extrusion (MEX), Stereolithography(SLA), and Powder Bed Fusion (PBF) [5]. AM is an attractive
include experimental geotechnics, numerical modeling, liquefaction assessments, and dam safety. She is also interested in issues related to women in engineering and has published numerous articles in ASEE conferences.Maribel Viveros, University of California MercedBianca Estella Salazar, University of California, MercedChangho Kim, University of California, Merced Changho Kim is Assistant Professor of Applied Mathematics at the University of California, Merced. He is participating in the ”Why, What and How” Calculus project as co-PI. ©American Society for Engineering Education, 2024Interest & Engagement Tactics for Success 1
review will be used toadvance pedagogy and educational strategies to advance the student–centered educationalenvironment.Keywords: Facial Expressions, Cognitive Engagement, Cognitive Skills, Emotions, Problem–SolvingIntroductionCognitive engagement involves actively employing mental processes in tasks or problem–solving,utilizing attention, memory, reasoning, and decision–making. Simultaneously, facial expressionentails the orchestrated use of facial muscles for emotional communication, classified by the FacialAction Coding System (FACS) into specific action units, e.g., raising eyebrows (AU1) or smiling(AU12) [1]. This systematic framework enables standardized analysis of facial expressions. Theintegration of cognitive engagement and facial
engineering course. We characterized ChatGPT usage as either productive or unproductivefor learning and defined four general reasons why students engaged with AI in this course:ChatGPT as 1) A learning aid 2) A coding resource specifically 3) An inevitability 4) A personal perspectiveWe discuss some of the ways that students can use AI responsibly as an asset to their learning.Their responses also show student awareness and current understanding of the positives andnegatives of AI use for acquiring and applying foundational programming skills. The results alsoshow that the majority of students who chose to use AI did so to enhance their learning ratherthan replacing their original work.Introduction and
Social Cognitive Career Theory (SCCT; Lent et al.,1994) and Critical Race Theory (CRT; Crenshaw et al., 1995), our study explores career pathwaysacross ME, EE, and CE, extending the inquiry to discern differences in career interests, mental andphysical health, and the experiences of minority stress and a commitment to racial justice—twopivotal aspects crucial among underrepresented racialized minority (URM) doctoral students inshaping their career interests (Monroe-White & McGee, 2023; McGee et al., in press).Statistics from the ASEE reveal that mechanical, computer and electrical engineering were amongthe top disciplines in 2020 in terms of the number of doctoral degrees awarded. Table 1 belowsummarizes these numbers. While the table below
“Research guided only by the controlling yardstick of profit undermines the role of the universityas a public sphere dedicated to addressing the most serious social problems a society faces.Moreover, the corporate model of research instrumentalizes knowledge and undermines forms oftheorizing, pedagogy, and meaning that define higher education as a public good rather than as aprivate good” [1]. -Henry GirouxIntroductionWhat has been coined as a crisis in graduate education, is evidenced primarily by 1) highattrition rates and 2) a mental health crisis among graduate students [2], [3]. The issue of attritionis of interest to various stakeholders including faculty
stimulating curricular content for highschool agriculture teachers, emphasizing the modern, technology-infused components of theindustry and resulting in a series of Agriculture-based STEM lessons. The background andglobal objectives of the researchers were covered previously [1], but in summary, it was hopedthat some stimulating technology lessons provided during the career formative years of highschool might convince more students to select an agricultural vocation as being leading edge andworthy of consideration as a potential career option. The current employment plight withinagriculture is severe and contains a double-edged sword [2]. Jobs in the agricultural world areperceived as low class and menial, but the technological knowledge necessary
STEMpedagogy. Such initiatives aim to elevate interdisciplinary teaching standards, tacklethe unique challenges faced by rural regions, and promote the all-encompassingadvancement of students in these areas, thereby propelling the progression of STEMeducation at large.Keywords: STEM education; Rural teachers; Teaching beliefs; Classroom evaluationpractice; STEM literacy; Course subject1. Introduction The development of modern society is closely tied to the progress and innovationin science and technology [1]. Rural STEM education becomes instrumental in drivinghigh-quality educational development in rural areas. It’s imperative to concentrate oncultivating high-level innovative professionals and improving educational quality, aprocess that hinges
in instruction has helped to convey difficult aspects of learningto students and has improve engagements and outcomes.IntroductionAI is increasingly permeating across all sectors of the designed world. From transportation to theclassroom, from battle fields to hospitals, from product design to manufacturing, AI presence isfelt. For this reason, it behooves a nation to provide awareness of AI capabilities from the earlybeginnings of education. A recent formation of the AI4K12 is a welcome for providingguidelines for teaching AI in schools [1]. It is worth noting that there is a variety of researchinterest in AI at the middle school, for example, Zhang et al. provides introduction to AI in theirMIT DAILy curriculum [2]; while Akram et al. used
forms and levels of research, deliver educational programmingand create workforce development projects to meet the growing national and regionalrequirements for an advanced computing capable workforce. One of the outcomes foreducational programming was to “Develop modules for one of your courses that demonstrateshow AI/ML can be meaningfully applied to your discipline (e.g. approximately a week’s worthof material for a semester course.)” With this outcome in mind, the Mechanical Engineeringcurriculum was examined for a course where applications in AI could be implemented. Aftersurveying the literature and finding the expansive use of AI in Nuclear Power Plants as outlinedby Lu et al [1], the best fit seemed to be in Thermodynamics II, where
incomprehending classroom material but also provide practical applications of theoreticalconcepts, thereby fostering students' interest in their college education. Interest is a keymotivator for student engagement [1] . However, some hands-on practices may discouragestudents, especially when gaps between fundamental theorems and new technologies on themarket have been widening. Some basic theorems are difficult to be verified by using complexhigh-tech devices or may be too complicated to employ effectively. Students may requiresignificant time to learn how to use these devices and may even waste time if immediateassistance is unavailable. Some students may give up if they face with excessive difficulties.Some old or out-date lab devices are easily used
engineeringeducation, to examine the use of intuition in engineering problem solving. CTA is a class ofobservational protocols that surface tacit knowledge through engaging experts with a task(Crandall, 2006). The purpose of CTA is to capture how the mind works through three primaryaspects: knowledge elicitation, data analysis, and knowledge representation. Many methods ofCTA exist, and best practices call for a combination of CTA methods. In this study we are usingtwo methods: 1) the Critical Decision Method (CDM), which assesses individuals decisionmaking in non-routine incidents through a set of cognitive probes (Klein, 1989), and 2) theKnowledge Audit Method (KAM), which we use to guide our probing questions and identifytypes of knowledge used, or not
consequently be less interested in pursuing a career where these are the only perceivable fieldsthat they can work in. These findings are reflected in waning undergraduate and graduate enrollment in chemical,petroleum, and chemical-related engineering. Year-to-year medium percent change in freshmanenrollment in this major had been steadily declining since 2018 in 96 institutions, with a markable10.4% decrease in 20203. In their 2021 Graduate Enrollment Census, The National ScienceFoundation found that chemical engineering had the smallest 1-year growth of 1.4% in 2020-21,and the large 5-year decline of 29.1% in 2017-21 among other engineering disciplines4. Thesestatistics demonstrate a national declining trend in pursuing chemical engineering, and
understanding the role of AI specifically within the field ofstructural engineering. Lagaros and Plevris [1] state, “AI methodologies have found a wide range ofuses and applications in engineering field, including civil and structural engineering, with impressiveresults.” Additionally, Huu-Tai Thai [2] provides a compressive review regarding machine learningfor structural engineering that includes a large number of applications where AI is already being usedin the structural engineering profession. While these references do list practical uses for AI within thefield of structural engineering, it is apparent that a background in this technology would be requiredto develop or even use some of the engineering applications that are discussed. The reality
(DGMs): Regenwetter et al. [1] conducted a study focusing on thepotential of Deep Generative Models (DGMs). These models aim to replicate datasets. However,the authors highlighted the limitations of DGMs in addressing engineering design challenges.Through a case study on bicycle frame design, they demonstrated that while DGMs can generatenew frames resembling past designs, they often fall short of meeting engineering performancestandards and requirements. The findings underscored the importance of engineering-centricconsiderations in AI modeling, suggesting that purely similarity-focused approaches may noteffectively translate to engineering tasks [2]. The researchers emphasized the potential of AImodels as design "co-pilots" with appropriate
control algorithms and experience first-hand how the physical response ofthe system changes. Finally, a senior level elective class in Sustainable Energy has benefitedfrom the use of Arduinos. Students have been able to develop hands-on experiments to exploresolar and wind tracking, and measure the power output of alternative energy systems. Repeatedexposure to Arduinos through coursework also contributes to student’s use of Arduino in classeswhere not required. The expanded use of the Arduino microprocessors has allowed faculty toenhance learning through hands-on experiences throughout the Mechanical EngineeringCurriculum.1. Introduction Arduinos were originally conceived of in a classroom in 2005 by a PhD student, HernandoBarragán, under the
. Microelectronics arepervasive in everyday life, from smartphones to life-saving medical devices and GPS navigationto home thermostats. Vulnerabilities in U.S. microelectronics workforce capabilities have been aknown factor within the industry since the early 2000s [1]. While the demand formicroelectronics has surged, the U.S. industrial base has consolidated mainly into a few suppliers[1], [2] with limited technical capabilities in the workforce to scale up. The U.S. is encounteringa growing gap between its need for microelectronics design and manufacturing capabilities andits ability to meet these needs domestically, resulting in an undesirable dependence on foreignsuppliers. Although several U.S. universities, in partnership with U.S. Defense
analyses andcalculated Cronbach’s alpha for all scales in the SEES. Our findings provided supportingevidence for the reliability and factorial validity of the interpretations of each scale in the SEES.Finally, we performed group analyses for gender and race/ethnicity groups, and the differencesaligned with previous theories and established research. We conclude that the SophomoreEngineering Experiences Survey has sufficient validity evidence for assessing the experiences ofsophomore engineering students and, therefore, can be used to 1) offer empirical insights into thecurrent state of sophomore engineering experiences, 2) identify factors that contribute to positiveor negative experiences, 3) further elucidate group differences, and 4) provide
alsoreinforces the importance of using multiple strategies to support students in believing that theycan (self-efficacy) do engineering and should continue to pursue it as a valuable career choice.IntroductionEngagement plays a significant role in determining the level of success that engineers canachieve, both during school and at work. In the workplace, employee engagement has beenshown to increase productivity [1], retention rate [1], job satisfaction [2], and customer loyalty[3]. On a similar note, academic student engagement has been shown to be positively associatedwith critical thinking [4], academic achievement [5], retention in engineering degree programs[6], and persistence [7]. Retention in engineering is especially important as the demand
green channel correlation method for versatile identification.Miah Abdullah Sahriar1†, Mohd. Rakibul Hasan Abed1†, Ratchanok Somphonsane2, Houk Jang3,Chang-Yong Nam3, Saquib Ahmed5,6*1 Department of Materials and Metallurgical Engineering (MME), Bangladesh University ofEngineering and Technology (BUET), East Campus, Dhaka-1000, Bangladesh2 Department of Physics, School of Science, King Mongkut’s Institute of TechnologyLadkrabang, Bangkok 10520, Thailand3 Center for Functional Nanomaterials, Brookhaven National Laboratory, Upton, New York11973, USA5 Department of Mechanical Engineering Technology, SUNY – Buffalo State University, 1300Elmwood Avenue, Buffalo, NY 14222, USACenter for Integrated Studies in Nanoscience and Nanotechnology
visualization for roboticsand automation. The students were given weekly robotics laboratory experiments in the course onrobotics and mechatronics. VR robotics integrated with Internet-of-Things based mechatronicsenables students to explore innovative approaches to integrate theoretical knowledge with practicalapplications, enhancing information retention, and promoting critical thinking.1. IntroductionThis paper presents the student learning result of a laboratory course on advanced robotics andmechatronics integrated with virtual reality (VR) and Internet-of-Things (IoT). Virtual realityindustry is getting more recognition due to its application in various fields other than gaming suchas education, medical, entertainment, military, fashion