expectancy. We analyze the data of 600 engineering students enrolled in a CS1 courseand find that gender and PPE are statistically significant factors that influence students’ learningself-efficacy. We also find that learning self-efficacy and GPA are statistically significant predictorsof outcome expectancy. We believe these results will help advance our understanding of engineer-ing students’ motivational beliefs and help instructors identify specific groups of students that mayneed additional support and assistance.1 IntroductionAs the importance of acquiring computational skills increases, there is a growing emphasis onadding more programming and data analysis courses in the undergraduate curriculum, especiallyfor engineering majors [1
inspired underwater robotics Leigh McCue, Adrian Hagarty, Jill Nelson, Cameron Nowzari, Ali Raz, Michael Riggi, Jessica L. Rosenberg, Daigo Shishika, Cynthia Smith, James YangAbstractFollowing our work-in-progress paper and presentation in 2022 [1], this paper documents effortsto develop a STEM outreach program in biologically inspired underwater robotics. This STEMoutreach program includes a prototype kit, a standards-aligned written curriculum for classroomimplementation, and supporting demonstration videos, assessed via focus group testing. The kitincludes three different hull shapes, emulating different maritime species, and two differentpropulsion mechanisms, e.g., propellers and flapping, in a lighter-than-air (blimp) platform
-Computer Science (non-CS) major students. This demand is more paramount as many studentsmay not have been introduced to fundamentals of programming in high schools. According to anational survey, only 53% of high schools offer computer science courses. The scarcity of theavailability of courses at high school level results in more difficulties, and no prior computerprogramming experience. For such students the deficit in base continues to grow in college withtwo important facets: 1) such students are reluctant to pursue engineering and computing majorsand 2) these students find typical college programming courses more challenging and harder thanmany others who took programming in their high school, leaving them behind in courses.Considering
formalizing extensive pre-trip activities prior to research abroad improved participant outcomes. The findings support the conclusion that exposing undergraduate and graduate students to the challenges of an international research environment has impacts that carry on to the future workplace. Index Terms International programs, Intercultural competence, Research evaluation criteria I. I NTRODUCTION Engineering challenges and problems are increasingly global in nature necessitating an international effort to address variedissues pertaining to sustainability, health, and security [1]. This globalization of
IntroductionResearch shows that cognitive functions are crucial components of mental processes and play acrucial role in our ability to perform a variety of tasks (e.g., [1], [2], [3]). In computer-aided design,cognitive functions such as perception, retention, visuospatial skills, etc. are relevant to using 2Ddrawings and 3D models in virtual reality (VR) environments. For example, the student mustrecognize and interpret a three-dimensional model from its orthogonal two-dimensionalrepresentations on a blueprint. Additionally, they must be able to store and recall information,which is essential in remembering prominent features of designs [4], which, in return, developsthe ability to recognize objects and identify their features based on visual information
mainly involved in identifying the research questions for the projectsand making decisions about how the results of the research-focused projects will beimplemented. This paper presents a replication of a model focused on university-communitycollaboration, student engagement and Science, Technology, Engineering, and Math (STEM)attraction and retention using three research-focused projects addressing community needs. Thethree projects are (1) empathic design project aimed at improving quality greenspaces andpedestrian streetscape experience, (2) food justice project to study the disparities in food accessbetween local regions, and (3) analyzing water quality in a local creek. The projects provided aunique opportunity for students to directly
academicresources and maximizing opportunities in their college environment have a relationship withstudents’ academic achievement and the progress they make with their learning [1]–[3].Satisfaction with college outcomes has also been found to have a relationship with studentengagement in academic activities [4]. Active classroom learning strategies have facilitatedstudents’ involvement in course learning. Such pedagogical strategies that have improvedstudents’ engagement with course learning and academic achievement in engineering classroomsinclude project-based learning, problem-based learning, flipped classroom, cooperative learning,questions, and discussions [5], [6].Furthermore, it has been found that motivation has the strongest relationship with
-progress paper focuses onhow a learning experience in augmented reality can help students gain the required skills neededfor industry.To date, academia has tried to help students develop strong technical skills by incorporatingdifferent analytical and problem-solving skills into the curriculum. As a result, academia hasintroduced different learning techniques to better prepare students for work after graduation. Onesuch technique is authentic learning with the use of augmented reality. Augmented reality (AR)is a technology that blends computer-generated elements with live video in real-time [1]. Virtual(computer-generated) objects appear to coexist in the same space as the real world are producedby the AR system. While many academics go beyond
their work life. Industry practitioners can help immenselyby adopting more inclusive language toward professional skills and providing internshipopportunities to incorporate these skills for students to gain real-world experience.Tags: curriculum, professional skills, real-world experiences, “soft skills,” workforcedevelopment1. IntroductionIn 2011, at the ASEE annual conference, the Educational Research and Methods Division (ERM)Division ran a conference session titled “They're Not "Soft" Skills!” [1] with the tagline,“There’s nothing "soft" about these difficult skills.” This session was hardly the first time thiscase had been made. Since that session in 2011, over ten years ago now, a casual search on theterm “soft skills” on the ASEE PEER
and executing these pillars, the CIRCUIT program is a model for accomplishing na-tionally recognized goals of increasing diversity in STEM — in both recruitment and retention.Supporting trailblazing students increases the quantity and quality of the STEM workforce overallas students have the confidence to apply for relevant positions and the technical credentials to ex-cel. In this work, we share our model and longitudinal student outcomes developed over the pastsix program cycles.IntroductionProgram OverviewOur program originated in 2017 as part of a computational neuroscience project 1 to satisfy the mis-sion need for talented, engaged proofreaders at a scale not possible with conventional approaches 2 .Since then, we have expanded this
lecture and two 110-minute labs perweek for fifteen weeks. Topics addressed in the course include visualization, sketching,orthographic, isometric, section, and auxiliary views, dimensioning standards, and parametricCAD using Creo. Because hand sketching has been shown to be important to improvingvisualization abilities and long-term student success not only in engineering graphics but across avariety of engineering courses [1], [2], [3], the first five weeks of the course are spent handsketching and it is continued throughout the semester even after CAD has been introduced.Whilst the content in the course is regularly updated to reflect changes in engineering graphicsstandards and CAD software used, the basic format remained the same for several
Cornerstone Projects will becompared. Project 1 took place during the spring of 2022 and was comprised of a windmillpower generation system. Students constructed this windmill and used Arduino programming tointerpret sensor data and calculate system performance. Project 2 took place during the 2022summer semester and was comprised of a water filtration system. In this project, students utilizedthe Arduino to both observe system information and control its behavior.At the end of each of these semesters, students took a survey in which they provided theirperceptions of the programming instruction they received, in addition to expressing theirconfidence in programming. Results of these questions from Spring 2022 (Project 1) andSummer 2022 (Project 2
(PBL) of aerospace and aviationdesigns, specifically focusing on UAS integration. The validation of peer-to-peer interaction as aperformance measure has led to the development of a framework to enhance flight operation.The four KPIs for measuring the overall effectiveness of the project solution are based on theuser guide for rotorcraft systems and include:: • Indicator 1: Investigation of key performance measures and the flight analysis data related to the ability to create an interactive model according to the user’s decision- making approach; • Indicator 2: Interpretability of the system design requirements and the UAS integration to performance the necessary input to execute in various conditions and limitations; • Indicator 3
learn from mistakesto create value [1]. Ohio Northern University developed “expanded KEEN student outcomes” (e-KSOs) that translate KEEN’s broad student goals into “specific, authentic, and actionablelearning objectives.” The e-KSOs define outcomes related to curiosity, connections, creatingvalue, communication, collaboration, and character [2]. As such, these e-KSOs could be easilyincorporated into course and assignment-specific learning objectives in any engineeringdiscipline.Computer-aided design (CAD) is a tool for EM projects integrated into design-based courses.Typically, these projects use CAD software to communicate design details [3, 4] or to develop amodel suitable for additive manufacturing [5, 6]. However, 3D modeling courses are
learning. AI is proving to be an effective tool for educators teaching anywhere from K-12 [1] or in sec-ondary education [2] to enhance teaching and provide students with personalized learning experi-ences. State-of-the-art AI technologies have been able to analyze vast amounts of data to identifypatterns, adapt to student needs, and provide real-time feedback with little up-front implementa-tion costs. As such, it has been shown that this tailored instruction and support to each studentcan improve their learning outcomes [3], [4]. Moreover, AI has been used to automate routinetasks such as grading, assessment, and administrative duties, freeing up educators’ time to focuson higher-level tasks. In this way, AI has been the catalyst in a
analysis of variance (ANOVA) procedureto compare the three sections and investigate significant differences between them through studentgrades. The results of this research have potential to provide direction for usage of remote collaborativetechnology for in-person, academic settings. Future implications of research include investigating theimpact of similar technologies on student engagement and learning outcomes; contributing a validatedinstrument to measure students’ engagement with their programming tasks and teams; and provideeducators with potential methodologies to improve student engagement in team-based coursework.IntroductionEngineering has historically suffered high student attrition rates [1], [2], [3], with a significantportion of
, MiguelAndr´es is validating his framework of a Blended & Flexible Learning approach that focusses on STEM courses and its practical adaptation to overcome barriers brought up by the COVID-19 pandemic. ©American Society for Engineering Education, 2023 Work in Progress: Exploring Impact on Students Dropout rates of Introducing a First-Year Hands-on Civil Engineering Course Estefanía Cervantes1, Miguel Andrés Guerra2*1 Instructor, Universidad San Francisco de Quito USFQ, Colegio de Ciencias e Ingenierías, Departamento de Ingeniería Civil, Casilla Postal 17-1200-841, Quito 170901, Ecuador.2 Assistant Professor, Universidad San Francisco de Quito USFQ, Colegio de
was used to create a module on concept evaluation and selection foran engineering design course.The method provided a unique way to engage the learners using customizable and immediatepost-processing of information they submit and could be useful for a wide variety of topics.However, the learning curve for both the instructor and the learners may not always justify theinvestment, learner responses may vary enough that they don’t provide the evidence expected tosupport the learning objective, and no formal assessment has been completed yet on itseffectiveness.IntroductionActive learning techniques are an important method to keep students engaged during class andimprove learning outcomes, such as in undergraduate engineering education [1], [2
review.IntroductionThis project began in 2019. While it is still a work in progress, the authors wanted to focus onthe methodology chosen to undertake this study, as well as the current status of the researchbeing conducted. The topic itself arose from several conversations at the 2019 ASEE conferencein Tampa where the authors were curious about the landscape of engineering librarianshippublications, focusing on what research methods were typically being used by engineeringlibrarians in their research and how appropriate and well were these approaches being explained.Explorations of the types of studies typically conducted by librarians has been discussed, studiedand editorialized from many years [1]–[4] but the focus in most of the papers examined seemedto be
, anexperiment was performed where people viewed three Navy job descriptions in their respectiveSTEM fields and were asked their level of interest. This paper will show that women who do nothave a background in the jargon are less likely to apply on jargon-filled, STEM job descriptionsthan men. Conversely, when women have a background with the jargon, this paper will showthat these women have a higher interest in the jargon-filled job advertisements than men do.KeywordsDiversity, Jargon, STEM, Job Advertisements, Gender.IntroductionResearch has shown that science, technology, engineering, and mathematics (STEM) careers aremale dominated [1]. Among first-year college students, women are much less likely than men tosay that they intend to major in STEM
. Gregory L. Long Ph.D., Massachusetts Institute of Technology Gregory L. Long, PhD is currently the Lead Laboratory Instructor for NEET’s Autonomous Machines thread at the Massachusetts Institute of Technology. He has a broad range of engineering design, prototype fabrication, woodworking, and manufacturing experiNathan Melenbrink, Massachusetts Institute of TechnologyDr. Amitava ’Babi’ Mitra, The Pennsylvania State University Amitava ’Babi’ Mitra linkedin.com/in/babimitra|+1-617-324-8131 | babi@mit.edu Dr. Amitava aˆ C˜Babiˆa C™ Mitra is the founding Executive Director of the New Engineering Education Transformation (NEET) program at MIT ©American Society for Engineering Education, 2023The
- tion in computing. ©American Society for Engineering Education, 2023 Understanding the impacts of extra credit modules on student learning experience in a 100-level Electrical and Computer Engineering CourseAbstractThis Complete Evidence-based practice paper investigates students’ perceptions regarding thepresence of two extra credit (EC) modules on parallel computing topics in an introductoryelectrical and computer engineering course. Prior work investigating these EC modules showed ahigh participation rate (48-60%) across and high performance (80-88%) on the end-of-module ECquiz across three semesters [1]. The presence of extra credit has long been a topic of
engineering education; Higher engineering education; China; Policyshift; Path evolutionIntroductionEngineering is about using technology to solve problems for society [1 , and aboutapplying changing technologies to meet the demands of the increasingly knowledgeable,interconnected, and interdependent human enterprise. Today, human society is facingenormous challenges in terms of climate change, cybersecurity and safety, carbonemission and wars. These, alongside the sci-tech revolution and industrial globaltransformations, have rapidly changed the global landscape of higher engineeringeducation (HEE) [2-3 . Echoing such trends, China is transforming its HEE throughnew engineering education (NEE) initiatives [4 . China has contributed to the
coined by Anthony Klotz, who is an Associate Professor ofManagement at the May Business School at Texas A&M University [1].Wikipedia defines it asthe “ongoing economic trend in which employees have voluntarily resigned en masse, beginningin early 2021. Possible causes include wage stagnation amid rising cost of living, long-lasting jobdissatisfaction, safety concerns of the COVID-19 pandemic, and the desire to work forcompanies with better remote-working policies” [2]. Dictionary.com defines it as the “informalname for the widespread trend of a significant number of workers leaving their jobs during theCOVID-19 pandemic” [3]. Investopedia.com defines it as the “elevated rate at which U.S.workers have quit their jobs starting in the spring of
- neering. His research interests include complex systems, cyber-physical systems, and system dynamics. ©American Society for Engineering Education, 2023 University Coursework as an Alternative to a Professional Certification ExamAbstractThe International Council on Systems Engineering (INCOSE) offers three levels of individualcredentialing, two of which require participants to pass a standardized test, as shown in Figure 1.While the standardized test is an efficient way to test participants' knowledge of systemsengineering, the newly introduced INCOSE's Academic Equivalency (AcEq) Program providesan alternate path to becoming certified systems engineer. AcEq allows participants
. His research includes undergraduate engineering education with focus on engineering design, problem-based learning, co-curricular involvement and its impact on professional formation, and the role of reflection practices in supporting engineering undergraduates as they transition from student to professional. ©American Society for Engineering Education, 2023 Using the CAP model to Equitably Redesign a First-Year Engineering SeminarIntroductionThe student body in higher education keeps changing, making it critical to pay attention to newgenerations' challenges toward achieving their academic goals [1]. Generation Z students are the core ofthe current student population at colleges and
per backward design [1], but they rarely use them as the basis forregularly identifying students’ learning challenges and needs. Learning Objectives (LOs) arewritten statements that describe specific competency in knowledge, skills, and abilities (KSAs)that students are expected to demonstrate [2] in a course. They are typically introduced tostudents at the start of a class session, unit, or assignment to frame the intended learning. Afterwhich, they are seldom referred to again [3], but herein lies an incredibly missed opportunity.Clearly articulated LOs can be used as the basis for assessment, particularly in criterion-referenced assessment strategies like Standards Based Grading (SBG) [4], also referred to asSpecifications Grading. In this
. Aftercalculating the required sample size with the established parameters, the sample was estimatedby groups of educational level. For this purpose, the participation of each group in the analysiswas established as it is displayed in Table 1: Table 1. Sample characteristics Students Total % Sample Ph.D. 58 1.5% 23 Master 1603 42.7% 39 Undergraduate 2096 55.8% 32 Total 3757 100% 94Once the size of the population was determined, the sample size was calculated, using
printing system consisted of 4 different subsystems - thestructural subsystem, the XY axis subsystem, the Z bed subsystem, and the bottom plate thathouses the components of the electrical system. Using the separate part files, the Monarch Xteam was able to construct a complete model in Fusion 360. The complete model can be seen inFigure 1 and consist of the 4 integrated subsystems where black components represent thestructural system, yellow components represent the printer head as well as the electricalsubsystem, red components represent the battery packs, blue components represent steppermotors, and gray components encompass the Z bed plate and the base mounting plate of the fullsystem. Figure 1: Overall Physical 3D
research workforce, but not inengineering. According to national statistics, only 32% of undergraduate students in STEMdisciplines are female and this percentage is decreasing as women dropout from STEM asthey move forward in their education. The analysis of the interviews revealed the mainbarriers, challenges, and issues influencing females and ranked their importance. A keyoutcome of the study is the importance of support, mainly from family and teachers, as it hasthe biggest impact on building confidence and retaining female engineers in their careers.Keywords: Transitional economy, STEM Education, Gender Gap, Female Engineers,Kazakhstan.1. IntroductionThe study of science, technology, engineering, and mathematics (STEM) fields can be