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
many prestigious awards, and fellowships such as university's distinguished professor award. © American Society for Engineering Education, 2022 Powered by www.slayte.com Innovative Industry-Related Research Projects for Civil Engineering Undergraduate Students Mohammad Jonaidi1 and Simin Nasseri2 (1) Department of Civil and Environmental Engineering, (2) Department of Mechanical Engineering Kennesaw State UniversityAbstractThis paper covers the important aspects of new research methodologies, including the methodsand tools, for
. © American Society for Engineering Education, 2022 Powered by www.slayte.com Students Utilization of Discord Messaging Platform in an Introduction to MATLAB CourseIntroductionEngineering courses are increasingly utilizing technology tools to enhance and support learningof engineering content. Some of these tools include virtual labs [1], [2], concept or clickerquestions [3], [4], and online and interactive textbooks. Yet, we know adding technology to aclassroom does not always improve learning [5]. The COVID-19 pandemic and the move toemergency online instruction only increased the use of such tools as other avenues to connectwith students and enhance online instruction. An
-intensive institutions. She earned her Bachelor and Master of Civil Engineering degrees from the University of Delaware in 2000 and 2002, respectively, and PhD in civil (structural) engineering with a minor in seismology from the Georgia Institute of Technology in May 2007. Dr. Head specializes in structural engineering, solving problems related to 1) seismic-resistant design and retrofit of reinforced concrete structures, 2) bridge load testing and evaluation using digital image measurements, and 3) evaluating the performance of structures rehabilitated with composite and advanced materials to enhance strength and ductility. The broader impact of her research includes performance-based design (PBD) methodologies validated
effect on student performance and will thus be repeated/evaluated in the ME 252 coursein the subsequent semesters for continuous improvement.Goals and ObjectivesFigure 1 shows that ME 252: Engineering Dynamics course is a prerequisite to ME 356: FluidMechanics, ME 384: Computational Method, and ME 460: Controls. These courses areprerequisites to other Mechanical Engineering (ME) courses such as ME 411, ME 420, ME458, ME 480, and ME 481. Thus, for students to attain success throughout the MechanicalEngineering curriculum, they must develop a solid understanding in ME 252. The need toimprove their knowledge is highly crucial because every semester, nearly 25% of students inthis course earn a “D”, “F” or “W” grade and must repeat the class
competence,team leadership competence, individual characteristics, and risk managementcompetence. This study deepens people's understanding of the connotation andstructure of the intrapreneurs' competence in China, and to some extent promotesuniversities to discover and cultivate intrapreneurs' competence in college students.Key Words: Intrapreneurs' Competence, Connotation and Structure, UCINET,Questionnaire1. IntroductionIntrapreneurship was first proposed by Pinchot, an American scholar, in his 1985 book“Innovator and Enterprise Revolution”. The core of intrapreneurship is to study how toconduct entrepreneurial activities within large, established organizations.[1]Intrapreneurship theory was first focused on the field of enterprise management. It
and validated iSTEM observation protocol (Dare et al., 2021) from 2,007 iSTEMlessons were used. Through preliminary analyses, we determined that the assumptions for MLRhave been sufficiently met. Three categories of the outcome variable, student cognitiveengagement, reported on were lessons that provide opportunities for students to (1)analyze/evaluate STEM concepts, (2) use/apply STEM concepts, and (3) know/understandSTEM concepts (which was set as the baseline or reference category). All predictor variablesexcept for curricular opportunities for collaboration and data practices were statisticallysignificant in the model. The final MLR model has a total of 12 predictor categories. Thedeviance goodness-of-fit test indicated that the model was
STEMlabs (Work in Progress) (Diversity)IntroductionDue to increasing demands from industry and society, European and American educationsystems share the common goal to develop pre-college students’ knowledge, skills, andcompetencies in the fields of Science, Technology, Engineering, and Mathematics (STEM)[1], [2], [3]. However, contemporary research depicts conceptual differences in the definitionsof STEM teaching across engineering-related educations and highlights the need for a sharedunderstanding of what STEM educations should contain [4]. Even though businesses andgovernments are promoting STEM in the educational systems, new inquiries andrecommendations are necessary to mitigate the expected lack of STEM graduates in the futureand to
IntegrityIntroductionAs post-secondary institutions offer more hybrid and online classes, more students are takingonline courses and programs [1]–[3]. These courses are also becoming a more common part ofthe education of traditional student populations [4]. As such, it is important to address challengesand provide support for secure remote assessments of student content mastery [5].A major benefit of online learning is the flexibility in time and access [6]. Some remoteproctoring services use automated artificial intelligence to provide examinees with flexible testwindows [7]. However, instructors view remotely proctored exams as less effective at preventingcheating as they perceive it allows more opportunities to cheat [8], but the use of remoteproctoring is
in1979 and taught in Industrial Engineering until retirement in 2014. He has published books on Manufacturing Processes, Geometric Programming and Strategic Cost Fundamentals. He has been a member of ASEE since 1968. © American Society for Engineering Education, 2022 Powered by www.slayte.comDesign Equations Developed by Geometric ProgrammingHistory of Geometric Programming Dr. Clarence Zener is credited for the first paper related to geometric programming andis considered to be “the father of geometric programming” and is also known for thedevelopment of the Zener Diode. His publication in 1961, “A Mathematical Aid in OptimizingEngineering Designs[1] in 1961 is
Project Management Associate for a Habitat For Humanity housing project in the USA. (ii) RESEARCH: Miguel Andrés' research focuses on (1) decision-making for the design and construction of infrastructure projects, (2) the planning of sustainable, smart and resilient cities, and (3) the development of engineers who not only have solid technical and practical knowledge, but also social understanding for, through infrastructure, address local and global challenges on humanitarian, environmental, social and equity issues. (iii) EDUCATION RESEARCH: Related to STEM education, Miguel Andrés is developing and applying contemporary pedagogies and tools for innovation and student empowerment to address climate change. Currently