ethical considerations. The findings suggest that thoughtful incorporation of bothsustainability and automation boosts productivity and economic benefits and leads toenvironmentally and socially responsible manufacturing. This paper is intended for academicsand researchers interested in the future directions of sustainable manufacturing in the era ofIndustry 4.0.IntroductionIndustry 4.0 signifies a substantial revolution in manufacturing, where cutting-edge technologymaximizes efficiency while reducing resource usage. Industry 4.0 is a German initiativeintegrating production with information technology [1]. The contemporary industrial revolutionutilizes sophisticated digital technologies, for example, artificial intelligence (AI), big
thesehave changed over time. This information will help librarians to better support MET students andfaculty by allowing for targeted information literacy instruction and outreach.IntroductionInformation behavior is a general term that serves as an umbrella for describing the many waysthat people interact with information including information seeking, information use, andinformation creation, among others [1]. Bates also explains that the concept of informationbehavior includes, but goes beyond, information literacy which is more narrowly focused on“finding and effectively evaluating desired information”. Instead, information behaviorresearchers have developed a wide range of theories and models to better understand the ways inwhich people
engineering years ago [1].According to Pew Research Center, employment statistics for STEM job clusters (definedSTEM jobs specific to the applicable industry), Caucasians, Asians, Blacks, and Hispanicsrepresent 67%, 13%, 9%, and 8% respectively of STEM jobs—Caucasians and Asians areoverrepresented in engineering and architect jobs at 71% and 13%, respectively—Blacks andHispanics are underrepresented at 5%, and 9% respectively [2]. The increase of women inengineering academia or the workplace has been slow to non-existent over decades. In a surveyposted by the U.S. Census Bureau, decennial census 1970-2000 and American CommunitySurvey public use microdata 2010 & 2021 reported a slow incline of female representation inengineering in the workplace
are motivated, persist through their programs, and learnengineering material [1]- [3] which has led to calls for supporting students’ engineering identitiesalongside traditionally taught competences [4]-[8]. The degree to which students feel recognizedor seen as the “kind of person” who can do engineering has been delineated as the mostimportant element in the development of an engineering identity [9], [10]. An understanding ofrecognition is critical for designing high-impact curricular practices that support identitydevelopment and in guiding program culture that includes students in the community ofengineering. Researchers have explored if students believe others see them as engineers andemphasized the importance of these beliefs [11], [12
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