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
and successful entry into college or career. This requires that students developa full understanding of the career opportunities available, obtain the education necessary to be successfulin their chosen pathway, and a plan to attain their goals throughout their education (known in the state asthe Personalized Education Plan, or PEP). Thus, these standards are based on 16 Career Clusters, or groupsof occupations and industries based on commonalities identified by empirical evidence. Input was alsoobtained from local workforce and post-secondary leaders, the Board of Education, and teachers. [1]Virtually every career in all clusters, regardless of education level, requires CS. Prior to 2021, some of the state’s districts had made a CS
, Mexico City Campus. She obtained a Ph.D. in Computer Science from the Tecnol´ogico de Mon- terrey. She is co-leader of the Advanced Artificial Intelligence research group. She is responsible for the Cyber-Learning & Data Sciences Lab. She belongs to the National Research System of Mexico (SNI level II), the IEEE Computer Society, the IEEE Education Society, the Mexican Society of Artificial Intel- ligence, and the Mexican Academy of Computing. She got 3 awards (2 Gold winners and 1 silver winner) for her participation in the Project ”Open Innovation Laboratory for Rapid Realization for Sensing, Smart, and Sustainable Products”. QS Stars Reimagine Education. She obtained seven first-place awards for Ed- ucational
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
themselves.Introduction"At this moment of our historical trajectory, it is a moral imperative to embrace decolonizingapproaches when working with populations oppressed by colonial legacies." [1, p. 1].As of 2021, the United States (US) Census Bureau [2] estimates that roughly 62.6 millionpeople, or 19% of the nation's population identify as having Latin American ancestry. These areindividuals with origins within Latin America, from Mexico down to Chile, as well as the islandslinked to Latin America who within the context and history of the US have used various labels toidentify themselves. Starting in 2014, the term Latinx started to appear in contrast to otherself-identifying labels like Hispanic and Latina/o. Labels that in themselves create a
University ofNebraska-Lincoln and offers four degrees: a Bachelor of Science in AE (BSAE); a fifth yearABET accredited Master of AE program following the BSAE; a Master of Science in AE(MSAE); and a Doctor of Philosophy in AE (PhD-AE). The BSAE and the fifth-year Master’sprogram combine to create a 4+1, 5-year accredited degree program.The 4+1 curriculum has traditionally consisted of coursework in calculus, physics, chemistry,core engineering courses like statics, dynamics, mechanics of materials, and architecturalengineering discipline courses. A full listing of all course topics covered in this curriculum ispresented in Table 1.Within the AE program, students select a specialization option in building structural systems,mechanical systems and
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
integration.Aside from lectures, the course relies heavily on project-based learning. The students are dividedinto teams to propose, design, and implement realistic, hands-on projects. When there is anopportunity for a large-scale project such as Project 1 discussed in this paper, the entire classparticipates with sub-disciplines organized around a specialty such as structural design or electricalinterconnect of solar energy with the local utility. Safety and NEC (National Electrical Code)compliance are also discussed to satisfy course objectives. In summary, the class project ismanaged to mirror real world project implementation treating the class as design-build entity andsub-groups as sub-contractors. During the implementation phase of the project, the
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
is feasible for smaller class sizes. This method becomes impractical asthe class size increases. It creates an additional workload for the instructors and brings certaindisruptions to the orderly implementation of normal teaching and administration. It maycompromise the course content [1]. Furthermore, during the covid pandemic, educationalinstitutions utilized web meeting technologies in place for in-person meetings, i.e., onlineteaching. During online teaching, when instructors want to interact with students, they can callout their names without knowing them priorly. We are proposing to use face recognitionalgorithms to bring the convenience of web meeting technologies to in-person educationenvironments. This will help instructors to know
poster on their project that ispresented at a symposium. In the senior year, students take a 2-credit hour course in the fall andspring, undertaking the research developed and proposed in their junior year. For the projectdescribed here, students performed an independent research project in Costa Rica. Through thisproject, students analyze a technology‐based problem, develop alternative solutions, recommendthe best solution, and provide a written and oral technical report. As part of this internationalexperience, students are able to demonstrate their ability to define and manage a project, identifygoals, track and report progress, deliver results on time, and clearly report results. Specifically,students have: 1. Develop innovative
domain-specific programs: material science and engineering andarchitectural engineering. This project is broken down into the following objectives: 1) facilitate datascience education and workforce development for engineering and related topics, 2) provide opportunitiesfor students to participate in practical experiences where they can learn new skills through opportunities innew settings to transform data science education, and 3) expand the data science talent pool by enabling theparticipation of undergraduate students with diverse backgrounds, experiences, skills, and technicalmaturity. The paper will focus on the topics, deployment strategies within courses and curricula,establishing data sets, representative examples of work-in-progress
, including children in early childhood education, must be consistentlyexposed to data science concepts to meet future industry requirements [1, 2]. Students wholearn data science at a young age are better equipped to implement the concepts at later stageswhere they will have more chances to practice and develop their skills [3]. However, currentdata science research for early childhood is very limited, and although previous data scienceframeworks for K–12 education have claimed that the content is suitable for kindergarteners,application has proven that, in reality, the content is more appropriate for students in grade 4and beyond [4]. Therefore, this paper proposes a data science framework suitable for the developmentalstages of young
challenges for students andinstructors alike. One major challenge is the allocation of time for lab assignments, as theprovision of starting code and an automated testing tool (auto-grader) often leads to studentsover-devoting their time to complete the assignments. This can result in students prioritisingcoding labs over other courses as research has indicated that students often experiencedifficulties in balancing the demands of multiple courses and may prioritise assignments basedon deadlines and perceived difficulty, leading to reduced engagement in other subjects [1].Studies have also shown that the use of automated grading systems in programming courses canlimit the effectiveness of formative feedback and lead to a narrow focus on syntax
, and its synergy with the existing curriculum, this paper provides guidance for datascience curriculum development, implementation, and evaluation in civil engineering.IntroductionThe need to manage, analyze, and extract knowledge from data is becoming a necessity for everysector of society including industry, government, and academia. Engineers routinely encountermassive amounts of data, and new techniques and tools are emerging to create knowledge out ofthese data [1]. The compounded accessibility of data has considerably altered the civilengineering and the construction profession, and data analysis skill is recognized as a crucialexperience desired in engineering graduates [2-4]. Data science in civil engineering has a verywide scope. Data
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
-related need. However, despite the emphasis on design-focused projects throughout thecurriculum, students tend to have higher electronics/coding competency than in physicalprototyping skills.Because it is a convenient way to quickly have a physical product in hand, many students feelmost comfortable with designing prototype components that are 3d printed, withoutconsideration to other types of fabrication. This limitation is apparent in our senior design (SD)classes, as many teams don’t have familiarity with appropriate material selection or basicfabrication techniques. It has been reported that it may be the majority of engineering studentswho do not have prior shop fabrication experience [1]. When students reach their capstonecourses, not only
cause of dysfunctional teams [1]. A critical first step for first-year students to achieveteam success is to understand what types of negative conflicts could emerge, as well as trainthem to understand how to cope with and/or resolve the conflicts. In this experience-basedpractice paper, peer-to-peer evaluations were used to improve students’ team-based learningexperience. The research question of this study is: How could course instructors utilize a contentanalysis of a peer feedback system to improve guidance for first-year students on resolving negativeconflicts?At New York University, six hundred first-year engineering students participate in free-choiceopen-ended semester-long projects annually. The primary aim is to allow students to
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
struggle in graspingGeometry by its fundamental principles. Although numeracy should not be undermined for itsmathematical importance, Geometry and spatial sense are best acquainted for effectiveinterpretation and understanding. Virtual reality (VR), which has been defined to be “the sum ofthe hardware and software systems that seek to perfect an all-inclusive, sensory illusion of beingpresent in another environment” [1], deals mainly with spatial sense. This technology continuesto show massive potential in improving the quality of education at various levels and disciplines.It is wise to capitalize on VR's potential in optimizing our human engagement and integrate itinto Geometry education. This will remove the disunion between students and the
the program and encourage faculty across the country to adopt our modelof embedding computing experiences in lower division courses.IntroductionAdvancements in digital technology have radically changed our daily lives and routines, from theway we educate students and navigate traffic to how we treat patients and collaborate withcoworkers. This infusion of technology brings with it an increased need for interdisciplinaryprofessionals with both domain knowledge and computing skills. Including more women andindividuals from historically marginalized communities will further diversify and grow thedigital workforce to meet this increased need. As interdisciplinary computing jobs command anaverage 14% salary premium [1], an increasingly diverse
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
framework could help educators make better decisions on how to effectively integratethese new technologies within the curriculum to enhance and augment the learning ofengineering concepts for students.Introduction Extended Reality (XR) is an umbrella term for various types of electronically enabledrealities like Virtual Reality (VR), Augmented Reality (AR), and Mixed Reality (MR) [1].Extended reality (XR) devices and applications are being utilized to augment training andeducation within engineering and beyond. These include a broad spectrum of devices rangingfrom immersive virtual reality headsets with handheld controllers to augmented reality headsetswith finger tracking and smartphones with intelligent machine vision. Fig. 1 shows
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
would embed data science topics related to data retrieval, instrumentation, andapplications related to hardware equipment has not been developed yet, and emergingtechnologies have not watched the pace in the typical engineering technology curriculum that isfocusing on electronics and data acquisition.Data science has dramatically expanded with high demand in many industries, from energy,healthcare, finance, manufacturing, and many more 1 . As a result, there is a growing call for datascientists and engineers who can work with large amounts of data and extract meaningful insightsto support decision-making in all industries, and in particular in manufacturing and processingengineering applications. To meet this demand, the development of a data
practice. Leaders in industry and government began to recognize this in the 1980sand 1990s [1] [2], and major employers, spearheaded by Boeing, made concerted efforts duringthis time to pressure universities into better equipping engineering students with skills codifiedas most valuable for career-readiness [3].Tensions between industry needs and higher education came to a head in the mid-1990s when“American industry successfully lobbied the National Science Foundation to fund reform ofeducation” and influenced the Accreditation Board for Engineering and Technology (ABET) tooverhaul the basis for accreditation in 1996 with Engineering Criteria 2000 (EC2000) [4].Although EC2000 has been mostly successful in improving engineering education, the
of educationaltools for teaching computational thinking. The entire solution will be used in summer camptraining to teach programming skills to a young audience in Colombia. New projects havederived from the results, like the development of instructional guides for practices that use thesolution, and the development of enhanced versions that can reduce the costs of production andintroduce wireless communication.I. IntroductionIn “The Future of Jobs Report 2020” [1], the world economic forum (WEF) built a list of tenskills that will be most required in jobs by 2025, one of them being “technology design andprogramming”. Having technological skills is becoming crucial to find better job opportunities indifferent domains, but that poses a
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