theoretical perspective onthe integrative nature of identity and its developmental mechanism” (p. 2037). Given that wewish to eventually examine STEM-persistence as a byproduct of the integrative nature of theLION STEM Scholars multiple role identities (Low-Income/College-Student/Future-Engineer),DSMRI (see Figure 1) serves as our theoretical framework. Specifically, this paper will begin toexplore the (1) ontological and epistemological beliefs, (2) purpose and goals, (3) self-perceptions and self-definitions, and (4) perceived-action possibilities within and between thevarious role identities that the LION STEM Scholars possess prior to their first semester ofcollege and before their participation in Engineering Ahead.The objective of the DSMRI is
programming concepts, database design and implementation,graphical user interface design, and web application development. Students complete three im-mersive simulation-based learning (ISBL) modules as course assignments. ISBL modules involvetechnology-enhanced problem-based learning where the problem context is represented via a three-dimensional (3D), animated discrete-event simulation model that resembles a real-world system orcontext, in this case, we have three simulated systems/contexts around which ISBL assignments aredefined: an airport, a manufacturing system, and a hospital emergency department. The researchexperiments involve four groups: (1) students with no choice who use the same assigned simulatedsystem for all three ISBL assignments
increasingly more minority students are enrolling in college, the number of collegegraduates with STEM degrees is still not favorable to minority students such as Latinx [1]. Inparticular, Latinas enrolled in STEM programs continue to experience hostile environments inmen-dominated spaces such as Engineering, even in Hispanic-Serving Institutions (HSIs) [2, 3].HSIs are all degree-granting higher education institutions with 25% or more full-time Latinxundergraduate students [4]. Institutional strategies, financial assistance, faculty representation,mentorship opportunities, and culturally responsive research opportunities are all critical inretaining and graduating students, especially minority and underrepresented students [5]. We aimat increasing
EducationResearch through Collaborative Secondary Data Analysis” [1].The Mini-ProjectsSecondary Data Analysis as a Mechanism for New Insights and Future Researcher PreparationThe first project aims to explore the potential of SDA for training of newer researchers to thefield. The data originator is an experienced researcher with a large dataset resulting from acompleted NSF funded project. While the original project had delivered on its goals, there wasscope for further analysis of the interviews that had been conducted with undergraduateengineering students. Our project involves a researcher from another undergraduate-focusedinstitution, who wanted her undergraduate researchers to get experience doing qualitativeresearch on an already existing dataset
completion within six years in comparison with other races, Black students have thelowest completion rate (41 percent) and are more likely to discontinue enrollment or stop outthan to complete a college credential [1]. Over time, these trends have largely remained the samewhen comparing Black and Latinx collegiate students with other majority races and it has causedsome to ask the question: What are colleges and institutions doing to address this? One of theanswers researchers have given is putting an institutional emphasis on inclusive teaching. Research has illustrated that student academic and social success can be improvedthrough instructors creating inclusive classroom environments that facilitate a sense of belonging[2], [3]. Though
academic and professionaljourney. Unfortunately, this decision is often plagued by uncertainty and indecision, leading to ahigher attrition rate among students who think they have made a definite choice. [1]Selecting an academic major is a complex process that is influenced by various factors such aspersonal interests, family and peer pressure, and access to reliable information. The informationavailable to students can be outdated, unreliable, or inaccessible to underrepresented groups,leading to ill-informed decisions. To address these challenges, we must understand engineeringstudents' information-seeking behaviors when making their major selection.This research paper aims to delve into the academic major selection process among
from our professional development, summarizing learning objectives, presentationcontent, and activities. Additionally, we present comments shared by instructors related to ourprofessional development, including common barriers to implementing educational innovationsin their courses. Our work will provide insights to practitioners interested in promoting inclusiveclassroom practices in engineering education and researchers who are translating research topractice, especially through professional development.Keywords: Faculty professional development; inclusive pedagogy; asset based practicesIntroductionDespite many years of effort to increase participation, engineering suffers from unequalparticipation based on race and gender [1], [2] and
computational thinking. Analysis of pilot data gatheredfrom five sections of a life science course in a northeastern U.S. urban high school during the2022-2023 academic academic year will inform the next iteration of the module.Background and MotivationThe thought processes associated with formulating problems and solutions such that they can beefficiently and effectively carried out by both machine (i.e., computer) and human is known ascomputational thinking (CT) [1]. While the construct of computational thinking originated incomputer science, CT practices like abstraction, pattern recognition, and modeling arerecognized to be incorporated in all science, technology, engineering, and math (STEM)disciplines [2], [3] and have revolutionized how
curriculum modules were implemented in the firstoffering of the course. Preliminary assessment results from the first offering of the course arediscussed.1 IntroductionSmart products can sense their environment, analyze lots of data (big data), and connect to theInternet and other smart products over a network to allow exchanging data. Today, there are manyconsumer smart products in our lives such as smart door locks, bike locks, smart kitchenappliances, irrigation controllers, smart thermostats (e.g. Nest), and Amazon Echo just to name afew. Such physical objects (things) connected to the Internet is called the Internet of Things (IoT)[1].Smart products are becoming ubiquitous and STEM workforce demands are shifting rapidly, butthe current
engineering courses. Research suggests amismatch between the skill demands of industry and the offerings of educational institutionsresulting in a skill gap [1-6]. As a major contributor to the United States economy and thesecond-largest labor sector with 8% of the total workforce Field [7]), the construction industry istaking a massive hit from this skill deficiency. Many scholarly publications and reports regardingemployability in the construction industry have reported employers’ concerns and dissatisfactionwith the low level of skills of their newly hired construction graduates [8-13]. As expressed bymany employers, one of the downstream implications of these skill gaps is project failure due todecreased work performance, productivity, and
focused on thedevelopment of skill that future architecture and engineering professionals need to design resilientand sustainable infrastructure [1] This paper describes the semester-long project that was assignedin the “Design-Build” course, which is the last course of the curricular sequence. Through this course,students were asked to develop an interdisciplinary design project. The course follows the academicmodel of integrated project delivery [2], where teams of students were asked to design a projectbased on the development of an emergency housing complex. The project consisted of designing aset of four emergency dwellings. The project derived the purpose of being a mini capstone [3] whereinterdisciplinary groups of students were able to
region.Antarjot Kaur ©American Society for Engineering Education, 2023 Integrating Design Thinking and Digital Fabrication Into Engineering Technology Education Through Interdisciplinary Professional LearningIntroduction. Makers by Design is a National Science Foundation(NSF) AdvancedTechnological Education funded professional learning (PL) fellowship designed to advanceparticipating educators’ ability to integrate design thinking into their classroom instruction.Design thinking is a non-linear iterative approach to problem solving using a human-centeredapproach [1]. 17 educators were recruited to this project from the northern Virginia region,including K-12 teachers, postsecondary faculty, and public
Teachers’ Technological- Content Knowledge and Lesson Plan Development OutcomesThis study was conducted at a Research Experiences for Teachers (RET) Site in a university onthe northern Gulf Coast. The National Science Foundation (NSF) Division of Computer andNetwork Systems funded the RET site to offer a research-intensive program in artificialintelligence (AI) computing systems. Since the summer of 2021, Science, Technology,Engineering, Mathematics (STEM) middle- and high-school teachers have participated in anannual six-week summer program [1]. They participated in technology and instructionalworkshops, work sessions, and authentic artificial intelligence (AI) research activities with theuniversity faculty, graduate, and undergraduate
of collaborative teams is a critical first step in team-project-based design courses asteam composition directly affects not only teamwork processes and outcomes, but also teamworkskills and experience.This NSF sponsored project aims to enhance students’ teamwork experiences and teamworklearning through 1) understanding how to form better student design teams and 2) identifyingexercises that will effectively improve team member collaboration. We do this by comparingstudent team characteristics and design task characteristics with the quality of the design teamoutcome and examining the resulting correlations. Student characteristics cover six categories: 1)background information, 2) work structure preferences, 3) personality, 4) ability, 5
existing curriculum constraints. In particular, teachers found that the NextGeneration Science Standards [1] practice of “computational thinking” was the best lens fordeveloping their aligned big data instruction. After exploring a taxonomy of computationalthinking in mathematics and science [2], the teachers collectively eventually settled on a core setof four computational thinking skills [3] most likely to be productive for their teaching focus;algorithmic thinking, decomposition, abstraction, and pattern recognition. This paper reports onthe variety of connections teachers developed with the practice of computational thinking, fromdata clustering as an active practice for simulating early generation of the periodic table in achemistry class
aspects of our institution and student body. We willalso report preliminary analyses of student journal data collected from the first cohort throughoutthe Fall semester, where students described their initial expectations/hopes and concerns for thesemester; their activities and emotional responses during the semester; and finally, theirreflections on their experiences, positive or negative, throughout the semester. The paper willconclude by offering lessons learned from the first year of this project as well as directions formoving forward.Literature ReviewThe Vertically-Integrated Projects (VIP) model [1-4] engages students in multi-scale, long-termresearch project teams led by faculty and their graduate students. The VIP teams
skills through START internshipIntroductionA shortage of 3.4 million skilled technical workers by 2022 (or 13% of the U.S. workforce ages25 and older) was predicted by the National Academies of Sciences, Engineering, and Medicine[1]. With the increasing demand for spatiotemporal computing skills in the real-world jobmarket, project-driven internships have become an important source of work experience forstudents with interests concerning geographic information systems (GIS) and related geospatialtechnologies [2]. However, while GIS internships offer benefits to college students, rarely do 2-year college students being trained in this field, even rare to see such internships being evaluated,especially during the
at three U.S.institutions have collaborated as part of the National Science Foundation's InternationalExperience for Students (IRES) Site Track-1 project to develop a program to improve the globalcompetencies of undergraduate engineering students through a 6-week summer internationalresearch training program in collaboration with Universiti Teknologi PETRONAS (UTP),Malaysia focusing on applications of data science and artificial intelligence to solve energy andrelated infrastructure problems. This paper presents a case study of a collaborative IRES programfocusing on implementation challenges stemming from the pandemic and university policies andpractices. The COVID-19 pandemic has transformed/disrupted university and workplaceactivities
Ethics Reasoning Instrument (EERI), and concept map assessment to characterizewhere students “are at” when they come to college, the results of which can be found in past ASEEpublications. Additionally, we have developed a suite of ethics-driven classroom games that havebeen implemented and evaluated across three universities, engaging over 400 first-yearengineering students. Now in its third year, we are modifying and (re)designing two of the game-based ethics interventions to (1) more accurately align with the ethical dilemmas in the EERI, (2)allow for more flexibility in modality of how the games are distributed to faculty and students, and(3) provide more variety in terms of the contexts of ethical dilemmas as well as types of dilemmas.As
quantitative description of students’ community and belonging at IRE.1.1 Iron Range EngineeringIRE students complete lower-division coursework at community colleges around the nation [1]. Thenstudents join IRE for one semester on campus for preparation focused on developing students’professional, design, and technical skills. After this first semester, students earn their degree whileworking in a co-op and earning an engineering salary (average $21.5k per semester). Students remain fulltime students through the co-op based learning format by taking 1-credit hour technical competencies anddesign, seminar, and professionalism coursework, and earn course credit for coursework related to theirvaluable co-op experience by applying and further developing
expected withother variables in the dataset.IntroductionEngineering, along with other STEM fields, remains slow to design learning environments thatsupport minoritized students and their interests in or talents for STEM work. This troublesomediversity issue takes shape through participation barriers that filter out promising contributions tosolving some of society’s most complex problems [1]. Importantly, people from minoritizedbackgrounds broaden the variety of perspectives working on these pressing issues and the STEMworkforce benefits from their participation [2]. Newer lines of research are revealing how sexualorientation and different gender identities shape participation in STEM [3], adding to theimportance of understanding and counteracting
elements (i.e., peers, instructor, and in-class instruction) were discussed in 55% of thereflections as positive “surroundings.” Within the classroom ecosystem, feelings about positiveCoI “surroundings” balanced 54% of respondents who discussed the physical room attributes asnon-supportive to learning. Interestingly, when students identified their CoI as a type ofsurrounding, they less-frequently identified physical attributes of the classroom as non-supportive.Thus, the presence of a Community of Inquiry may have diminished the perception or impact ofphysical room features. Overall, our results preliminarily suggest the positive influence that aninteractive flipped classroom structure can have on students’ perceptions of their “surroundings.”1
pursuing higher education, particularly in demanding STEM majors, is notsimple. Some young people in lower socio-economic status (SES) households have many morethings to consider than ‘am I qualified?’ Their decisions generally involve other family membersand home responsibilities [1] [2]. To work through these considerations and to prepare for anacademically demanding collegiate major, and then be denied admission into it at their local stateinstitution can be emotionally crushing [3] [4]. It is particularly upsetting when it is known thattraditional engineering admissions metrics discriminate against otherwise qualified students fromchallenged backgrounds [5] [6]. Researchers at Purdue University attempted to design analternative means of
question. The results suggest that nestedness is linearly proportional tousage, both increases and decreases. As such, tracking the nestedness of a makespace over timecan serve as a warning that unintended restrictions are in place, intentional restrictions and/orpolicies may be too severe, or whether a space has effectively recovered from temporaryrestrictions.Introduction and BackgroundEngineering makerspaces in academic settings are becoming significantly more common asresearch continues to hail their benefits for engineering education [1-4]. Network modeling ofthe spaces have successfully identified critical tools within the space, however the effects oflarge-scale events affecting usage over time has not yet been explored[4]. The importance
kitchen appliance), and the “design” ofthe students’ academic career pathways. The purpose of this paper is to present the progress onthe project supported by NSF award 2225247.The main objective of this project is to help freshman engineering students develop problem-solving skills that can be applied to their academic success. The college readiness, and hence theacademic success of incoming students at UTRGV College of Engineering and ComputerScience (CECS) needs to be improved. Statistics, shown in Table 1, indicate low levels ofretention and graduation rates particularly for CECS.Table 1. UTRGV College of Engineering and Computer Science First Year Full Time Freshman 1st Year Retention Rate
older than 25, a single parent, financiallyindependent from their parents, and/or working full-time [1]. The Department’s primarydemographic is non-traditional and Underrepresented Minority (URM). These individuals sufferfrom reduced retention rates and longer timeline to graduation [2, 3, 4, 5]. Non-traditional studentsoften use non-curricular work to finance their education. This employment is most often temporarynon-STEM jobs [6]. Working less than 15 hours per week can be beneficial to an educationalprogram [7]. Non-traditional students often work at least 20-40 hours per week. The same reportidentifies these longer work hours as a risk for academic success. Low-income students withsubstantial work hours that are not major related have an