matching the instructionalapproach of the intervention. Research on implementation factors also adds to the fields inunderstanding how and why teachers in various settings and with various backgrounds makeadaptations as they implement curricula [1]. In their discussion of the importance of flexibilityand fit of interventions, Harn, Parisi, and Stoolmiller [12] argue that "one of the best ways tomatch contextual and intervention characteristics to optimize implementation with fidelity overtime may be to adapt evidence-based practices to better match school-level context." Although research explicitly examining factors influencing the implementation ofengineering curricula is scarce, studies on the enactment of engineering curricula
Graduate StudentsAbstractThe first year of graduate school can produce great angst in students undertaking a fundamentalidentity shift from student to researcher [1]. In interdisciplinary programs, acquiring confidencewith an additional disciplinary framework and threshold concepts brings additional challenges[2]. Solutions often focus on mentoring [3], but students entering highly interdisciplinarygraduate programs may need additional support that helps them integrate the unique challengesfaced by students changing or integrating multiple disciplinary backgrounds and identities. Wepropose that formalizing career path exploration, with an emphasis on surfacing students’ angstabout their options and career paths through a professional development
and diversity,equity, and inclusion (DEI). The authors described how these subcategories would need to becategorized properly in future revisions, but the idea is they heavily dictated a student’sconfidence and sense of belonging.Summarizing this listing, we concluded with a motivational category list of interventionsubcategories as follows: task-value interventions (e.g., utility-value, communal value), framinginterventions (e.g., self-efficacy, belonging), personal value interventions (e.g., valueaffirmations), mitigating stereotype threat, and changing attributions, as shown in Table 1.Donker et al (2014) conducted a meta-analysis on teaching strategies that help studentmetacognition and self-regulation to find which specific tactics
Emerging Technologies through Co-design Workshop (RTP)AbstractArtificial Intelligence(AI) and Machine Learning (ML) touch every aspect of modern life andwill continue to influence us more than ever in the future. Schools and teachers should beprepared to let the children explore ML to help them understand how the world around themfunctions. It has been shown that children as young as three years old can not only interact withML technologies but also produce ML data sets and models[1].In this paper, we explore factors influencing the growth of teacher confidence in implementingemerging ML technologies within engineering educational settings. Five teachers from St. Louis,USA, engaged in a co-design workshop to explore an emerging ML toolkit and to
such as lead time andthe number of attempts. In addition, student perception was evaluated through the use of voluntary,anonymous mid-term and final course surveys. Qualitative faculty observations are included aswell. Student response to the unlimited attempts on homework assignments was overwhelminglypositive. Initial data show that students achieve higher final scores on homework assignmentswhen they attempt 1) the assignment earlier and 2) accomplish more attempts with a moderatecorrelation for both. It appears that 5% bonus points for early completion has a slight increase inmotivation, for roughly half of students.Background & Prior WorkThis work intends to build on previous work on effective course design [1] [2] [3]. The
mindset. To achieve thisobjective during the first offering, this course utilized active learning techniques, personalreflection, and the development of an individualized career-impact roadmap by each student. Inorder to work in conjunction with programming available from existing career centers andacademic advising, this interdisciplinary course placed an emphasis on personal reflection andthe roles of innovation and technology commercialization in creating societal impact. This paperdescribes the logistics of developing and implementing this 1-credit hour course and providesdetails of the assignments used to assess student learning. This course can serve as an example toother institutions who seek to more fully empower their students to
)and its intersection with Internet of Things (IoT) hardware technologies, a vital focus must beplaced on fostering the growth and development of its specialized technical workforce in theElectrical and Computer Engineering (ECE) and other related fields [1]. This strategic focus iscrucial given the escalating demand for proficiency in critical domains like embedded systemspaired with machine learning, sensor-driven big data analytics, edge computing, andcybersecurity [2]. The combination of AI and IoT, known as AIoT, embodies the convergence ofadvanced technologies that rely on seamless collaboration between AI algorithms and IoTinfrastructure. This integration drives innovation and efficiency across various industries,highlighting the urgent
-generation category. Weanalyzed survey responses assessing sense of belonging, self-efficacy, and institutionalsupport. The survey explores three dimensions: 1) general belonging, 2) belonging ineducational interactions, and 3) self-efficacy, each with eight items. The survey coversvarious aspects of the institution's student services, including psychological support,academic planning, tutoring, health and well-being services, sports, and supplementary areaslike leadership, diversity, gender, and participatory meetings. It totals 29 items. Respondentsexpressed their views using a 5-point Likert scale, from "strongly agree" to "stronglydisagree." Our findings reveal that all surveyed students exhibit a strong sense of belonging(both in general and
subsequently completed his Ph.D. in Applied Physics at the University of Yaound´e 1, also in Cameroon. Currently, he holds the esteemed position of Associate Professor at the University of Cincinnati.Dr. So Yoon Yoon, University of Cincinnati Dr. So Yoon Yoon is an assistant professor in the Department of Engineering and Computing Education in the College of Engineering and Applied Science at the University of Cincinnati, OH, USA. Dr. Yoon received her Ph.D. in Gifted Education, and an M.S.Ed. in Research Methods and Measurement with a specialization in Educational Psychology, both from Purdue University, IN, USA. She also holds an M.S. in Astronomy and Astrophysics and a B.S. in Astronomy and Meteorology from Kyungpook
different between femaleand male students, except for black/white shading in the cartoon drawings. There were nosignificant differences between the AE scores for female versus male students. Our results do notsupport the existence of a correlation between multilingualism and travel with artistic creativityand innovation self-efficacy attributes. Overall, we did not find that the students’ artisticcreativity or life experiences revealed through the self-portrait activity provided insights intoinnovation attitudes.IntroductionCreativity and innovation are crucial skills for engineers, as they enable the development ofnovel solutions to complex problems and drive technological advancements [1-4]. The NationalAcademy of Engineering (NAE) in the United
electrical engineering coursesIntroductionIn this Work In Progress, we present a pilot study to investigate how instructors see the role ofemotions in their student's learning process and argue that instructors’ emotional connectionssubstantially impact teaching methods and practices, consequently influencing the students’learning process. Research conducted by educational psychologists and cognitive scientists hasdemonstrated the importance of emotional connections in the learning process. Wheninformation is tied to an emotional association for the student, it tends to be better retained andrecalled over an extended period [1]. In fact, the complex and dynamic processes associated withlearning cannot be dissociated
thematic analysis of the twentydata entries, four distinct themes emerged from the generated codes: identity, traits, supportbehaviors, and outcomes. The code application patterns were interpreted to provide insight on thecollective meaning within the network of being a mentee and a mentor, professional similaritiesand aligned values, and mentorship methods and motivations. The insights produced may not begeneralizable to any mentorship social network, however they identify interesting characteristicswhich could lead to intriguing lines of inquiry for future work on this topic.1 IntroductionThe need for engineering students to develop and value leadership, transferable skills, andprofessional development alongside technical skills is gaining
have a greatimpact on student’s self-efficacy.BackgroundThe development of abilities of societal decision-making has received little attention fromengineering educators, who have prioritized teaching technical skills. Educators must choose thebest content, methodology, curricular models, and outcome evaluation techniques to integrateethics into the curriculum [1]. Conversations on ethics in engineering are typically guided by theNational Society of Professional Engineers’ (NSPE) Code of Ethics but they are often notrealistic to the workplace where an individual faces contrasting demands.Entrepreneurial mindset (EM) and ethical dilemmas are more commonly associated with otherfields like business, philosophy, and medicine (especially the latter
' attitudes. Transcripts of the interviews were analyzedusing thematic and content analysis methods. The thematic analysis identified eightfive main themes: (1) expectations and academic growth; (2) communication skills;(3) challenges in hands-on learning; (4) virtual learning experience; (5) personalgrowth and workplace readiness. Students' attitudes towards the three types oflaboratories were varied. Hands-on laboratories were favored for essential practicalexperiences, while remote and virtual laboratories were perceived as efficient andconvenient options. In conclusion, personal experiences, gender differences in labpreferences and experience, technological comfort, and individual learning styles allinfluence these attitudes, and the findings of
theindividual layers takes a lot of time, material, and precision. However, the labor and maintenanceinvolved is minimal, making 3D printing a great cost effective option for manufacturing designmockups and other plastic parts [1-2]. 3D printing creates less waste because material is beingadded to manufacture the part instead of removed. In addition to increasing efficiency, manufacturing engineers must consider how toreduce manufacturing cost. Some ways to achieve this is by reducing the amount of materialneeded or by reducing the amount of labor time per part. Using an infill pattern instead ofprinting a solid part addresses both of these methods. The layers cover less area and thereforetakes up less time and material to complete each layer of
stories of engineers and programs that have had exemplarysocietal impacts. A particular emphasis is placed on individuals historically underrepresented inthe engineering profession, including people of color, women, and people with disabilities,bringing their experiences and achievements to the forefront. Slated to be released in mid-2024,the report’s findings, conclusions, and recommendations are not yet available. However, thisarticle aims to shed light on the various ways that the NSF and NAE have conceptualizedengineering’s impacts on society by 1) exploring the history of engineering at NSF, 2) analyzingfoundational material from the NSF/NAE that informed the work of the committee such asNSF’s Broader Impacts and NAE’s Grand Challenges in
describes work performed at a large midwestern university in the U.S. examining the link between spatial skills and design performance. Spatial skills are vital to success in engineering education and their relation to efficient problem-solving is well- researched. This study is part of a larger project focusing on understanding the link between spatial visualization skills and solving engineering design problems. In the current study, we made use of an eye-tracking device to determine the visual focus of participants while they solved an assigned design task. High and low spatial visualizers in undergraduate engineering were identified through Phase I testing. In Phase 1, students completed four
institutions andstakeholders by providing them with strategies that could help motivate students and contributeto their academic success.Keywords: Academic Performance, Academic Success, Higher Education, Lack of Motivation,Retention, STEM Education, Students’ MotivationBackground and MotivationLow enrollment, inadequate academic performance, slow graduation rates, prolonged time-to-degree, poor retention rates, and high attrition among Science, Technology, Engineering, andMathematics (STEM) students are critical concerns for higher education institutions [1], [2], [3],[4], [5]. Furthermore, the need for STEM graduates is consistently rising at a relatively fast rate[6]. Consequently, promoting greater interest and engagement, fostering diversity
an engineering disciplineand a second language and spend their senior year abroad studying and interning as a mandatorypart of their program, then return to campus as part of their 5th and final year where they takecapstone courses in their respective engineering disciplines and the highest sequence of secondlanguage, culture, and literature courses.Research question 1: Which changes in students’ intercultural development were measured bythe IDI assessment?Research question 2: Which individual factors impacted changes in professional, personal andlife skills development during a year of studying and interning abroad?Literature review In previous influential scholarship, Byram [1], Deardorff [2] and Bennett [3] haveoutlined conceptual
New York Hasan Asif, is a graduate from the University at Buffalo in Data Science, possesses a keen interest in data transformation and gaining insights from data, includes expertise in setting up statistical tests, transforming data, and creating visualizations. He has demonstrated his skills by architecting systems to analyze the longitudinal participation of students throughout their studies. ©American Society for Engineering Education, 2024Exploring Variance in Undergraduate Research Participation: A Quantitativeand Qualitative Investigation Among Students with Differing Levels ofInvolvementIntroductionThis research paper concerns undergraduate research, a high impact experience [1] that
our analysis, we present acomparison of engineering school results to that of campus-wide results to uncover similarities(or dissimilarities) in extra credit accumulation patterns. The results reveal that althoughengineering and campus-wide students accumulate a similar number of extra credits, theircomposition is different. We would like to note that the methods used in this analysis, althoughapplied to the data from a specific university, are generally useful for credit-hour analysis.1 IntroductionCredit hours are a metric of time spent by a student in the classroom [4]: one credit hour equalsone hour in class every week for one semester [21, 11]. As per the requirements of all the regionalaccrediting agencies in the US, a bachelor’s
ofenvironmental engineers includes, “…[using] engineering disciplines in developing solutions toproblems of planetary health,” [1]. Sustainably feeding the human population is one of theproblems of planetary health, which environmental engineers are particularly well suited tocontribute solution [2]. Current agricultural production: 1. contributes to a loss of biodiversity from land use (i.e., sensitive habitat is cultivated); 2. transfers embedded/embodied/virtual water among watersheds (i.e., excessive groundwater pumping for irrigation in dry, warm regions to produce wintertime fruits and vegetables for consumption in wet, cold regions); 3. emits greenhouse gases (i.e., NOx emission from soil microbes during plant growth); 4
asmentorship provided to faculty, by other faculty. We specifically propose establishing acomprehensive framework articulating the behavioral, contextual, and structural factors thatinfluence the effective mentorship of junior engineering faculty. Mentorship can serve as acritical resource for junior faculty who are navigating the complex terrain of academia. Facultymentorship is not merely a transactional exchange but a multifaceted relationship thatsignificantly impacts career trajectories and personal growth. Effective faculty-to-facultymentorship has long been associated with positive outcomes, including professionaldevelopment, career satisfaction, and success [1], [2]. The current, extant understanding of whatmakes faculty mentorship effective
ways to make the program sustainable and lasting.This paper provides an evaluation of the different ways to expand and host more programs acrossthe state sustainably by looking at the following areas: 1) methods to recruit interested schoolsand districts, 2) increase program ownership by schools and districts, 3) engage cost-sharingpartnerships, 4) recruit students to participate in programs, 5) research and program assessment,and 6) providing multiple opportunities for students to return to the program.Informal learning environments allow students to explore new concepts, develop new skills,apply classroom understanding, and collaborate with other students across their schools anddistricts. This paper compares the GGEE program across its
Education]1 IntroductionEthics has been widely recognized as essential to effective engineering, highlighting theimportance of ethics education to engineering curricula [1], [2]. However, developing anddelivering effective engineering ethics education is difficult, given the increasingly globalenvironments of contemporary engineering.In contemporary engineering, people from different places and backgrounds are studying andworking together as never before [3]. National and cultural backgrounds can affectunderstandings of appropriate conduct within engineering [4]–[6], as well as conceptions of rightand wrong in general [7], [8]. Further, while much of the research on engineering ethicseducation in the US has focused on ethical reasoning and
Faculty Excellence in Teaching Award for the School of Technology and Engineering at National University in 2023. She had UNESCO Fellowship in the field of Information and Communication Technologies, in 2002. Her Ph.D. is in computer engineering. She is a member of the Institute for Learning-enabled Optimization at Scale (TILOS) which has an NSF grant that began on November 1, 2021, for five years. TILOS is a National Science Foundation-funded Artificial Intelligence (AI) Research Institute led by the University of California-San Diego and includes faculty from the Massachusetts Institute of Technology, the University of Pennsylvania, the University of Texas at Austin, Yale University, and the National
student experiencesand learning outcomes across different levels of delivery synchronicity of an online lab class(relative to an in-person class in the same student body) to help answer questions about how toadminister hardware-based lab learning online and how much synchronous engagement is enoughfor these use cases.The key research goals in the presented exploratory work were to 1) compare student experiencesand learning outcomes across two different levels of synchronous teaching when administering anonline lab class (i.e., asynchronous vs. synchronous) and 2) evaluate the above experiences andlearning outcomes relative to a similar-level in-person class taught to the same general studentpopulation. Accordingly, we collected data from seven
as the advanced large language model (LLM)-basedchatbot ChatGPT, have increasingly been integrated into various stages of academic research.These stages include the creation of study introductions and objectives, conducting literaturereviews, data analysis, and brainstorming methodologies [1], [2]. In qualitative research, there isa growing interest in leveraging AI tools to enhance data analysis processes. This research oftenentails detailed analyses of diverse data types to unearth study participants’ nuancedperspectives. Traditionally, these analyses have depended heavily on manual efforts, which arenot only time-consuming but also vary based on the analyst's expertise and perspective. Theintroduction of AI tools like ChatGPT marks a
collaborative training for construction education using real-world construction industry tools and software. This technology-based training can also inform the CMeducational sector about the opportunity for utilizing this or similar project-controlling software in theclassroom for semester projects to easily share the project information and communicate with studentswhile monitoring their progress.Keywords: Construction management education, Procore®, Real-world industry practices, Studentengagement, Construction lab. 1. IntroductionThe construction industry has been actively adopting new technologies to improve the collaboration andcommunication between the members involved in a project. Effective communication and project controlin the
and then equipping them with the ability to engage that workwith competence and insight. Learning taxonomies are tools that can be used to categorize thecognitive levels at which learners are engaging with material as a means of providing structureand metrics to the educational process, with achievement at higher levels of a taxonomygenerally corresponding to the desired intellectual abilities for practicing engineers [1, 2, 3].The general consensus among engineering educators has long been that creative, practical, andactive educational methods are needed in order to produce engineers who are well-prepared forthe workplace. Presenting students with problems and projects, laboratory experiences, designchallenges, group work, and other