Processes and their Applications; the course at ITESO, of 22 students total with 14 industrial engineering and therest business administration majors, was Manufacturing Services and Strategies. The course was required for graduation for all engineering majors and optional for business majors. The project was split into 5 major team deliverables, mapping a COIL framework as follows: in week 1, emphasizing team building and the development of trust; in weeks 2, 3 and 5, comparative discussion, team organization; and in week 9, collaborative project work. Different speakers from industry facilitated discussion on international teamwork and supply chain. There were individual reflections in week 1 and 9, before and after the project
-12classrooms in the US due to insufficient numbers of high quality engineers that will meet thedemands of the 21st century jobs [1], [2]. The incorporation of engineering in K-12 classroomshas grown in popularity since the publication and widespread adoption of the Next GenerationScience Standards (NGSS) [3] and its supporting Framework [4]. This focus on “engineering inK-12” has spurred invigorated educational research endeavors seeking to understand the impactof engineering activities on students' learning outcomes and interest in STEM careers [5]. The overarching goal of this study is to share results of a systematic review ofengineering education research published broadly across the K-12 education research field over arecent 10 year period
uses in her research. © American Society for Engineering Education, 2022 Powered by www.slayte.comReading the World of Engineering Education: An Exploration of Active and PassiveHidden Curriculum AwarenessAbstract This paper seeks to better understand the distinct, and sometimes intersectional ways thatparticular identities receive the hidden curriculum (HC) (unacknowledged and often,unintentional systemic messages that are structurally supported and sustained) in engineering [1].From the validated instrument (UPHEME; [2]), 120 participants communicated, in written form,that the HC they received was either active (intentionally and explicitly transmitted) or passive
unfortunately, students caneasily lose their understanding of their personal abilities as learners when they feel powerless inthe face of a monolithic factory model of education that appears indifferent to their individualstruggles and successes” [1, p. 15, emphasis in original]. The history of the development of thecurrent factory model of Western engineering education is eloquently explained by Tsai, et al.[1]. This factory-like system is ideologically supported by the metaphorical “pipeline” model ofengineering education, in which students are assumed to enter and exist their educationaljourneys in a uniform manner [2]. However, as Pawley and Hoegh point out, “in a country wherepublic education systems (both K-12 and higher education) still seem
computers. Mobiledevices comprise cell phones and tablets, while desktop computers include laptops. Mobile devices arepreferred over desktop computers because of their accessibility and convenience. Figure 1 shows acomparison of global mobile device users and desktop users. Number of Global Users (Millions) 2500 2000 # OF USERS 1500 1000 500 0 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 YEAR Desktop MobileFigure 1. Desktop and mobile user comparison. Average Daily Media Use in
, faculty recognized the absence of explicit messages but acknowledged the existenceof institutional structures that could support them if necessary (such as counseling services orprofessional societies). Finally, when comparing their experiences with those of currentundergraduates, faculty identify issues with excessive technology, imposter syndrome, lowextracurricular engagement, and low functionality among the elements against the newergeneration's wellbeing.Keywords: engineering culture, health, wellbeing, faculty, student success.ContextThe ongoing mental health crisis in U.S. colleges and universities [1] has only been exacerbatedby current societal challenges such as the COVID-19 pandemic [2] and racial reckoning [3]. Inresponse to these
identified relatedness as key to feelings of belonging inengineering and imposter syndrome as a key barrier to belongingness.IntroductionIn this work we seek to describe undergraduate engineering student wellbeing in a co-op basedprogram through the analysis of reflective prompts on general health, wellbeing, and engineeringbelongingness. We take an exploratory qualitative approach, backed by theoretical foundations ofself-determination theory [1], engineering identity [2] and belongingness [3].Student success has often been measured by academic outcomes; in this work we frame studentsuccess more broadly using the framework of Engineering Thriving [4], which takes a moreholistic approach to student success considering many different perspectives
human mind is called conation, which focuses on the individual's inner talent, will, drive,determination, and perseverance to learn [1],[2]. The conative domain has been ignored formany years, as it is often intertwined with the cognitive (knowing) and affective (feeling)domains [1],[2]. Defined as the conscious drive to perform the volitional act that encouragesan individual to strive towards attaining the goals, conation is very important as it describeshow a person naturally approach a challenging situation [1],[3]. Human beings are born with conative talent. Depending on their life experiences,conation may be diminished once they grow up. While learning, students will engage ordisengage their will to learn based on their perception
, 2022 Powered by www.slayte.com Engineering and Data Science for Environmental Justice (Resource Exchange)Description:Engineers use their knowledge and skill to protect and improve the safety, health, and welfare ofpeople and the environment and are guided by the ideals of sustainable development [1].Similarly, one of the Environmental Justice (EJ) Principles [2] “mandates the right to ethical,balanced, and responsible uses of land and renewable resources in the interest of a sustainableplanet for humans and other living things.” Engineering ethics intersect with the right toenvironmental justice for all. However, communities of color have historically been and
of Exploratory Factor Analysis (EFA) inengineering education research. EFA is a commonly used method across many social sciencesdisciplines, including education, political science, psychology, and marketing [1]. The goal ofthe technique is to reduce an amount of data, such as a list of survey items, to a moreparsimonious form, such as a small number of factors which the survey items describe in bulk[1], [2]. These factors which summarize a larger number of items are called latent factors. Inengineering education research, the technique is frequently and powerfully applied to thedevelopment and validation of novel quantitative scales, with some recent examples from thefield including measures of students’ responses to instruction [3], quality
better understand students’ perceptions of oral exams, created with differentstructures, with the ultimate goal of improving such structures to have a more positive impact onstudents’ engagement and learning.Literature reviewSystems of assessment are well-evidenced to be able to significantly influence student learning[1-7]. The mechanism of such influence is explained with reference to properties of assessment,such as probing power, quality and timeliness of feedback, authenticity, reliability, equity, andresistance to academic misconduct [8-13]. Assessment types that fare well with respect to theseattributes are more likely to motivate students and positively shape their approaches to learning[4, 6, 14, 15]. High-quality assessment modalities
skills [1]. The process of code comprehension is unlike comprehendingnatural languages because it involves complex cognitive processing. During cognitive processing,a programmer is required to develop or use the appropriate mental models of programmingconstructs, which makes code comprehension difficult for novice programmers [2]. Along withcognitive processing, it is important to analyze how students feel during code comprehensionbecause the literature suggests that emotions influence different aspects of cognition such asattention, reasoning, learning, memory, and problem-solving [3]. Novice programmers mayexperience a variety of emotions while comprehending code. These changes in emotions maysubsequently influence their academic performance
. Unfortunately, objective and rapid evaluation of AUT responses for levels oforiginality and usefulness is difficult. Recently, an automatized method for generating scores hasbeen developed, the freely accessible Semantic Distance (SemDis) tool [1]. Given the linguisticand cultural diversity of engineering students in the U.S., it seems fair to question how well thistype of automatic rating system, based on prototypical language models, captures the creativityof engineering students who may be nonnative speakers of English. We extensively trainedhuman raters to score the AUT responses of multilingual engineering students living in either anon-English environment or in the US, and the AUT responses of monolingual Englishengineering students. We found
their answers toproblems, and the second time to engage in some reflective activity comparing their approach ortheir answers with solutions provided by the instructor. This study identifies 14 suchapproaches, looks at what they have in common and how they differ, and summarizes theirresearch findings.1. IntroductionAs almost everyone in academia now knows, web sites like Chegg and CourseHero enablestudents to download homework answers, rather than doing the problems themselves. Thismakes it challenging for instructors to get their students to undertake enough practice to learnconcepts thoroughly. Several recent ASEE conference papers report on strategies thatincorporate metacognitive activities into homework assignments, so that students cannot
students’ choice of activities can help inform universityprogramming and advising to support students in these choices.IntroductionThis research paper investigates engineering students’ participation in different types ofextracurricular and co-curricular activities and the factors that inform these choices for students.We further describe distinct types of participation to capture the breadth and variety of studentextracurricular and co-curricular experiences. Participation in extracurricular and co-curricular(hereafter extra-/co-curricular) activities has been associated with retention and graduation,leadership and professional development, and engagement and sense of belonging, among otherpositive outcomes [1]–[4]. Despite general support of the
tests may be delivered, and collected online.)The once in a lifetime pandemic we are living through has had many adverse effects on physical andmental health and livelihood of almost all of us. In addition to the challenges familiar to everyone, ourstudents had to experience something that they were not prepared for: online learning. The onlyenvironment they had been exposed to (so far) was face-to-face instruction in a traditional classroom.Our students faced potential loss of housing, food insecurity, financial troubles, physical and mentalhealth issues, and increased isolation from peers [1]. The rapid change of situation in all parts of theirlives, including their education, was made more challenging by the new vehicle of instruction.There
-face, hybridand completely online classes to study students’ perceptions and attitudes as well as challengesrelated to changes in teaching formats during the pandemic. Furthermore, this study assessesstudents’ perceptions about the future of teaching in a post COVID-19 environment. Results ofthis study provide insights into both current and future impacts of the COVID-19 pandemic onengineering and computer science education.1 IntroductionCOVID-19 has had a significant impact on society causing immense physical, social, andeconomic challenges. Worsening the situation is the fact that the virus continues to mutateleading to variants that cause resurgences. One scenario proposed by Kissler, et al. [1] is that aresurgence of COVID-19 could occur
productive beginnings of engineering judgment, that is, the emergence of the setof practices engineers use to mathematize objects, systems, or processes [1]. In particular, wefocus on students’ emerging practice of making assumptions as they develop mathematicalmodels. Engineers create, manipulate, interpret, and apply mathematical models to understand,describe, and predict the behavior of designed objects, systems, and processes [1]-[4]. As part ofdeveloping a mathematical model, engineers make assumptions, or decide which factors toinclude in and exclude from the model. Reasoning about assumptions is essential to proficientengineering judgment and has been documented and described in ethnographies of professionalengineers (e.g., [1], [3-5
-one mentoring, tutoring, leadershipopportunities, research opportunities, periodic curriculum-related and social activities that fostereda sense of community, career counseling, and, in some cases, guidance towards baccalaureate orgraduate and professional studies. The program also examined the outcomes of the describedinterventions, which were used in the context of our urban, public institutional setting.This paper concludes the work-in-progress presented in a paper published in the ASEEproceedings in 2018 [1] and the epiSTEMe8 conference proceedings [2]. This project contributesto the national effort in recruiting, supporting, and educating future STEM professionals for thenational workforce by providing scholarships and curricular support
promotion of engineering education. © American Society for Engineering Education, 2022 Powered by www.slayte.comWork-in-Progress: Balancing It All: Using Photovoice to Visualize Second-YearEngineering Student Experiences1. IntroductionThis work in progress manuscript describes the experiences of sophomore engineering studentsat a large Carnegie-designated R1 Public University. Over the years, researchers have sought tounderstand engineering student retention. These studies have shown that many students drop outof their engineering programs during their first two years [1]. As a result, there has been asignificant focus on first-year retention in the last two to three decades [2
research,thematic analysisIntroductionIn this research paper, we examine episodic moments of professional shame as experienced bystudents when they interacted with faculty members. Anchored in theoretical foundations ofpsychology and sociology [1-4] and in empirical foundations of our prior work [5-9], we useHuff et al.’s [9] conceptualization of professional shame as “a painful emotional state that occurswhen one perceives they have failed to meet socially constructed expectations or standards thatare relevant to their identity in a professional domain” (p. 414).The findings of this study provide suggestions to engineering faculty members on how they canimprove overall well-being outcomes and cultivate systemically inclusive environments
aselection of articles published during the period of 2011 to 2021 by the flagship journal inEER—Journal of Engineering Education. We used three frameworks to guide our exploration:(1) employing a methodological taxonomy (Malmi, et al., 2018) to code the research componentsin ESEO-focused studies; (2) relying on areas of inquiry and paradigms embedded within studentdevelopment theories in higher education to help understand the theoretical groundings of someof these studies; and (3) utilizing an integrative student development theory—Bronfenbrenner’s(1979, 1993) ecological systems theory—to map out the contextual and individual factors instudent experiences. In the sections to follow, we will first provide an overview of two bodies of
upskilling ornew hires. The engineering-related market shortages can disrupt economic growth, reduceoutput, and undermine productivity. If shortages persist in the long run, countries can becomeless competitive because industries lack the talent to innovate [1], [2]. Moreover, to becompetitive, a developed country like Malaysia will also need engineers who can invent andproduce the technology, rather than being limited to sales, installation, configuration, andmaintenance of imported technological products. Identifying engineering-related expertiseshortages as they arise and developing strategies to fill them is essential to maintainingproductivity and competitiveness [3]. Many countries worldwide experience labor shortages,and Malaysia is no
weinvestigate how the framework transfers to open-ended modeling problems in dynamics courses.This analysis suggests our framework is transferable to dynamics courses, with all fourteen typesof judgement found in the dynamics data set and no additional ways of engaging in judgementwere found.Keywords: Dynamics, modeling, problem solving, engineering judgementIntroductionProfessional engineers solve complex, ill-defined problems with success measured by non-technical metrics [1]. Students are given little practice with solving these kinds of problems intheir undergraduate engineering science courses (e.g. thermodynamics, statics, and dynamics)where they learn standard engineering formulas and techniques. In these courses students aretypically assigned
for Engineering Education, 2022 Powered by www.slayte.com Work in Progress: Development of Virtual Reality Platform for Unmet Clinical Needs Finding in Undergraduate Biomedical Engineering Design ProgramsUnmet clinical needs finding and clinical immersion programs have been widely used in highereducation [1-3]. Unfortunately, they have only been offered to a select number of students (e.g.15-20 students) due to the limited space and extensive safety protocols required for students toaccess hospital operating rooms. Furthermore, in the era of COVID-19, access for non-essentialpersonnel to shadow physicians in hospitals has become increasingly difficult; combined
to the basicconcepts of unmanned aerial vehicles (UAVs) [1]. Students were taught how to design, build andfly their own quadcopter. The program was an ideal learning experience for students as they wereintroduced to key aerospace and aerodynamics concepts such as lift, drag, thrust, engineeringdesign, 3-D printing, mechanical and electrical systems and computer programming. Anotherprogram, the Drone Exploration Academy project at Elizabeth City State University provided6th-12th grade students a series of Friday sessions and a weeklong summer session in which theywere introduced to UAV mission planning, field investigation and designing ground and aerialvehicles to meet specifications [2]. The informal learning environment introduced students
end-of-course student feedback for such evaluations. Literature on the reliability of student evaluationsis presented and recommendations made for alternative methods of TPD program evaluations.Introduction Several studies have attributed low retention rates in STEM disciplines to inadequateteaching explained by mismatches between faculty’s pedagogical approach and how studentslearn; or the lack of attention to students from faculty [1-5]. This initiated several studies on howfaculty in higher education are trained from a pedagogical standpoint. Early studies in thiscontext found “ no one teaches teachers how to teach” [6], [7]. Students in doctoral programs are often at the forefront of the future academic workforce[8], [9
interpretations of relationshipsbetween different aspects of the model, iteration in design was salient to all participants, andwhile this SED Process Model’s visualization does have recommendations, several participantsnoted it does not specify exactly how to achieve those recommendations. Understandingengineering students’ perceptions of this SED Process Model’s visualization can help us (1)iterate on the process model’s visualization and (2) better understand how to leverage multipleprocess model visualizations in engineering curricula.IntroductionDesign process models are valuable tools to support designers in their work. However, no singledesign process model can encompass everything a designer should do in every design situation.Leveraging multiple
, and classroomcultures [1, 2]. Successful and productive collaborations are not guaranteed. Collaboration can begreatly improved by careful design of learning tasks [3, 4], assignment of team roles [5], and theuse of technologies [6, 7].Many evidence-based practices for collaborative learning, such as Context-Rich CollaborativeProblem Solving [8] or Process-Oriented Guided Inquiry Learning [9], were developed forin-person, synchronous learning contexts. With the on-going pandemic, the importance of onlineonly pedagogies has become more readily apparent. Online pedagogies provide new opportunitiesfor increased access to evidence-based pedagogies at potentially lower cost and greater ability toscale. Unfortunately, we do not know much about how
engineering students in two courses namely signals and systems and Electronics 1.Most of the students in Electronics 1 had already taken signals and systems course and somewere co-taking signals and systems. This set up has helped to understand the learning challengesthat persist even when students continue to apply similar mathematical concepts in othercontexts. The responses are analyzed to identify the common mistakes. These common mistakesare further analyzed to understand students’ weaknesses in solving questions related to theseconcepts. The results show that students struggle with understanding signals when theindependent variable is not time, when the signal is complex and contains j, when the signal is acombination of more than one signals