often lack a complete understanding of the contextwithin which they work and aims to improve both performance efficiency and outcomes byencouraging careful consideration of political, cultural, economic, and other non-technicalfactors that reside within the project population [1]. In this CIP case study, the authors willexamine Enactus-USA, whose clients populations are identified as the communities with whichproject teams seek to address material needs.Enactus-USA is a large entrepreneurial organization with the mission of “building a better worldwhile developing the next generation of entrepreneurial leaders” from among college studentsacross the United States. Founded in the U.S. in 1975, Enactus has since established similarnetworks in an
is perhaps the ability to solveproblems of technical, financial, interpersonal, and other types [1]. Many of these real-worldengineering problems are ill-structured and complex, containing multiple conflicting goals, andrestricted by both engineering and non-engineering constraints. That is why the first skill forengineering graduates that ABET lists in its Criterion 3. Student Outcomes [2] is “an ability toidentify, formulate, and solve complex engineering problems by applying principles ofengineering, science, and mathematics.”Reaching optimum solutions for practical engineering problems requires a systematic approachbased on evaluation, interpretation, and creative decision making. Mature level of criticalthinking (CT) skills are crucial
credits (6 courses), according to the formula described in Table 1.Required elements of a student’s plan of study include courses in naval hydrodynamics, controland autonomous systems, and an approved capstone project on a naval science & technologytopic, which can be either a full-year senior design elective (which also satisfies the ABETcapstone design experience requirement) or a single-semester independent investigation with afaculty advisor.Curriculum and facilitiesThe primary certificate courses are listed in Table 1, and are arranged into the categories of navalhydrodynamics courses, control & autonomous systems courses, and capstone courses. Courselearning objectives focus on technical knowledge associated with the subject as well
predictors in the first year, and race does not become asignificant predictor of dropout until the second year. The factors that influence dropout changeover time which emphasize the importance of dynamic dropout prediction models. The findingsfrom each phase of our analysis highlight the complexity of understanding the causes of dropoutand the importance of personalizing interventions for specific populations within a cohort.IntroductionNearly 20 million students attended American colleges and universities in Fall 2019, and roughly625,000 of these students were enrolled in an undergraduate engineering program[1], [2]. Thirtypercent of engineering students drop out before the second year[3], and more than 60 percent ofdropouts occur in the first two
by 19 students there were 28 cases in whichstudents were unable to correctly solve a problem using traditional methods, while in 17 of those28 cases the students were able to do so using the approach outlined in this paper. There were noinstances in which a student was successful using the traditional approach but unsuccessful usingthis new approach. All students received instruction in both methods.IntroductionThe transient (homogeneous) solution of any first-order system with constant parameters isdescribed by the following expression. Ke−t/τ (1)where τ is the time constant associated with the system and K is related to an initial condition. Inthe
all.However, faculty can and do influence the climate of the department and achievement ofstudents through choosing to implement evidence-based teaching practices like active learningand inclusive teaching [1], and having a growth mindset in relation to the abilities of students [2].It is also possible, for example, that the local climate in our department could cause students ofcolor to be driven from STEM [3], or that a chilly climate could have a disproportionate impacton female students [4].Over the course of the last several months, our department, college, and university have begun tocreate institutional structures to support these efforts. There is a new Associate Dean forDiversity, Equity, and Inclusion (DEI) at the college level, and at the
moved to a blended format and students were coming in-person in theLAB from potential different locations and environmental settings, it could have been disastrousand may spread the virus. Several precautions and security measures were taken to mitigate thesechallenges. Face covering was mandated during LAB hours. Each LAB was equipped with a handsanitizer dispenser and sanitizing wipes stations. Instructors included few extra notices in thecourse syllabi as below, in addition to daily class briefing.1. Students will work in group of 12, rotating between weeks. You MUST show up on yourassigned day and may not join with other groups on alternate days due to social distancing.STRICTLY ENFORCED.2. MUST wear “MASKS” through the duration of LAB
librarians at Northeastern University partnered with the First Year Engineeringprogram to develop and refine an interactive in-person workshop series designed to introducenew engineering students to key research resources at the start of their degree programs. Theprogram has grown rapidly, serving more than 500 first year engineering students in fall 2019with positive outcomes including high perceived value by students, high participation rates, andfaculty noting improvement in the quality of students’ research. When the COVID-19 pandemicforced Northeastern University to adopt a hybrid learning model, the team redesigned theworkshop for remote delivery with the goal of maintaining high participation rates and positivestudent outcomes.This paper (1
originally constructed for in-person student groups to work on their projectseither in pairs or individually. Providing remote access was not originally planned but after themove to remote instruction the laboratory stations were modified to accommodate the newreality.The diagram below shows the layout of the laboratory station equipment required for the remotecourse. The following sections provide descriptions for each of the major components. Figure 1: Laboratory Station ArchitectureThe laboratory plays an important role in this course due to the technologies used in the projectassignments. The workstation computers provide the computation, memory, and storagerequirements needed to build a full, cross-compiled Linux
requiresthe material covered up to a point in the course. A project phase is assigned once a topic iscovered in the lecture and reinforced through homework and quizzes.IntroductionEngineering design, defined by ABET [1], “is a process of devising a system, component, orprocess to meet desired needs and specifications within constraints. It is an iterative, creativedecision-making process in which the basic sciences, mathematics, and engineering sciences areapplied to convert resources into solutions. Engineering design involves identifyingopportunities, developing requirements, performing analysis and synthesis, generating multiplesolutions, evaluating solutions against requirements, considering risks, and making trade-offs toobtain a high-quality
enhance the curriculum of a graduate-level engineering ethics course, Engineering Ethics and the Public, at Virginia Tech, a large land-grant, Research 1 university. The course is a three-credit elective course offered annually to engineering students. The overall course itself was originally co-conceived and co-developed by an engineer, one of the authors of this paper, and a medical ethnographer, with the support of the National Science Foundation (NSF) [1]. The learning objectives, topics, and assignments are presented in Table 1. The course aims to address relationships between engineering, science, and society by incorporating listening exercises, personal reflections, individual
continue to collect research data in subsequent cohorts in (cur-rently) Spring 2021 and (upcoming) Fall 2021 sections, our early studentresponses show that new design has improved overall course reviews, whileachieving curriculum guideline goals for common computer organization andarchitecture course design. In addition, course materials that include coreknowledge areas (KAs) have been kept intact, and student feedback showsthat they understand each KA at comparable levels to classical computerorganization and architecture course content.2 MethodIn typical computer organization and/or computer architecture courses,knowledge areas are composed of the following concepts [1]: • Digital logic • Digital systems • Machine level
education. Thisredesign demonstrates that a mastery-based course structure is consistent with our updated modeland TPS principles. In this redesign, a continuous and iterative process was employed to ensurecontinuous improvement, and it follows a closed loop pattern of diagnosis, analysis, design,implementation, and evaluation (diagnosis).I. IntroductionThe factory model for education is based on Taylorism and principles of ‘scientific management’[1]. This factory management system was developed in the late 19th century and emphasized ontop-down management and power, and standardization and simplification of tasks in order tomaximize efficiency [2], shown in Figure 1. Parts and materials enter an assembly line andundergo numerous processes applied
unrealistic. To address the problem, we developed a novel virtual lab environmentthat sheds light on computer networking by showing students components of typical computernetworks with both hosts and backbone infrastructure using Wireshark and Mininet. The tools weutilized are a packet sniffer and emulated networking testbed. Even though students do notphysically build a computer network as was done in the real lab, they still got insights into apacket’s journey from a source host through routers before getting to the destination host. Ourdata analyses provided the information about the perceptions of these tools for online computernetwork laboratory from students’ perspectives and its associated factors.1 IntroductionThe computer networking
, undergraduate and graduate. In 2002 he established Leaders of Tomorrow, a student leadership development program that led to the establishment of ILead in 2010. He is a Professor in the Department of Chemical Engineer- ing and Applied Chemistry and ILead. American c Society for Engineering Education, 2021 A Leadership-Development Ecosystem for Engineering Graduate StudentsAbstractThere is a rapidly growing body of literature on engineering leadership education forundergraduate students [1, 2, 3]. However, there is little published about leadership developmentfor graduate students. There have been calls from national bodies to create and expandprofessional development
graduates to fill these new jobs.There is currently a large gap in the number of K-12 level teachers available in the area of careerand technical education. One possible solution to this problem may come from a specificsegment of the workforce, veterans. This paper will provide an overview of different challengesthat many veterans are facing after joining career switcher programs for future teachers.IntroductionDigital transformation is leading to a shift in many current jobs. Cybersecurity has become partof any virtual job [1], which became quite clear during the Covid-19 pandemic. The pandemicalso led to more openings for cybersecurity professionals, as well as a huge growth of thatspecific industry sector since there was a large rise in the
for remote instruction that supports student agencyAbstractUnder the new ABET accreditation framework, students are expected to demonstrate “an abilityto develop and conduct appropriate experimentation, analyze and interpret data, and useengineering judgment to draw conclusions” [1]. Traditional, recipe-based labs provide fewopportunities for students to engage in realistic experimental design, and recent research has castdoubt on their pedagogical benefit [2]. At the same time, the COVID-19 pandemic has forcedinstitutions to move to remote learning.To address these challenges we developed a series of online labs for an upper-division mechanicsof materials course. The first three labs consist of video demonstrations of
solve the problems under a time constraint to provide them practice forexam conditions. With these ideas in mind, AMechanics Race was created.BackgroundTo make introductory engineering courses more engaging, the author has previously reported onthe success of using pop culture and themes in the classroom [1]. One way to make an associationis by including characters and scenarios from current television shows or popular movies intoengineering content. For instance, Selby published that she had more enthusiastic responses fromstudents when she related concepts in her Environmental Engineering class to the MarvelCinematic Universe [2].The Amazing Race is a multi-Emmy Award-winning reality series on the CBS network, havingcompleted 32 seasons as of
transition.And some were learned during the implementation of the hybrid model.PartnershipsThe value of campus-community partnerships has been well documented as an important supportin STEM outreach programs [1], [2], [3]. The partnerships formed among Angelo State University(ASU), Tom Green County Library (TGCL), and area community-based organizations provided awealth of resources which were essential to the program’s success. ASU and TGCL provided thecornerstone partnership needed to establish and build the program. While both institutions sharegoals of acquiring and disseminating knowledge, they have very different characters. Angelo Stateprovides technical expertise within STEM fields and extensive laboratories. However, many of itsresources are
energy technologies (especially focusing on solarenergy and wind energy), a student project assignment has been developed wherein studentsdesign, build, and test a model passive solar home. Following an in-class lesson on passive solardesign strategies, students choose a location on Earth where their model home will be “located.”Next, the students must design their passive solar home so that it incorporates good passive solardesign principles and includes, at minimum: 1) roof overhangs that are long enough to shademore than 2/3 of the home’s south-facing windows at solar noon on the summer solstice, butshort enough that they shade no more than 1/3 of the home’s south-facing windows at solar noonon the winter solstice, and 2) at least one other
change at the atomic and molecular level.It is a central process in materials science and engineering (MatSE) as well as in chemistry,chemical engineering, molecular biology, and any other science dealing with atomic scalephenomena. Therefore, all students of atomic-scale sciences ideally should acquire a deepunderstanding of diffusion, but such understanding has proven difficult to achieve across age-groups and subjects [1]–[5]. One core reason for the difficulty is that it is not obvious how themacro-scale behavior—net movement of particles from regions of high concentration to regionsof low concentration—emerges from random-walk behavior at the submicro-scale. This leads to“levels-slippage” [6] in which a person assumes the behavior at the
or ECE, such as Control Theory, Digital Signal Processing or StructuralDynamics.The curricular goals of ESA are to further develop students’ skills and expertise in theengineering analysis process, increase their self-directed and peer learning abilities, and toconvey content that is common to ME and ECE programs. The focus on quantitative analysis ispart of a broader effort to educate students in this area. The course material is built around ahands-on project to control an inverted pendulum on a cart, a classic problem in control theory[1] which is often included in Signals and Systems and System Dynamics courses [2], [3].To this end, we developed a project using an affordable system based on an Arduino-likeplatform, the Balboa 32U4
solve complex engineering problems. [1], [2] However, these goals haveevolved from practical-focused to more theory-oriented throughout the decades. Maintaining andupdating instructional labs requires high equipment, space, and human resources cost. [2] Thesereasons lead to traditional engineering experiments often became procedure-orientated andfocused on reinforcing a fundamental principle in a narrow discipline. [3], [4] Holmes et al.demonstrated that labs designed to reinforce concepts show no added value in enhancing students'understanding of fundamental physics material. [5] They compared exam performance betweenstudents who did and did not enroll in a closely-coupled laboratory course. Their results show noimprovement or even worse
typicalclasses, learning activities from levels 1-5 take place before students are asked to tackle level 6 learningactivity. This forms a natural progression in learning. When it comes to programming, this naturalprogression is broken for the sake of accelerated effort to get the students familiar with the field as wellas programming, simultaneously. This approach, while noble in intention, can be compared to trying torun without the ability to walk.In this paper the conventional material to teaching programming to freshman MEs is replaced withnewly developed material which has been designed so that students know and understand everyproblem assigned before they tackle the task of writing code to solve the problem. The problems arechosen in such a way
and curricular resources forachieving engineering literacy for all. This resource exchangedocument will provide a brief introduction to the framework andexplore how the highlighted concepts can build upon each otherto influence more immediate and purposeful instructionalpractice. The complete framework can be downloaded forfree at https://p12framework.asee.org/.Defining Engineering Learning: The framework operationally defines Engineering Learning as three-dimensional which includes 1) the Engineering Habits of Mind (i.e., Optimism, Persistence, Creativity,Systems Thinking, Collaboration, and Conscientiousness) that students should develop over time throughrepetition and conditioning, 2) the Engineering Practices (i.e., Engineering Design
educators can employ to understandcorrelations between STEM learning topics such as climate change, and students’ susceptibilityto AI-driven misinformation. The proposed approach has the potential to guide STEM educatorsas to the STEM topics that may be more difficult to teach (e.g., climate change), given students’susceptibility to AI-driven misinformation that promotes controversial viewpoints. In addition,the proposed approach may inform students themselves as to their susceptibility to AI-drivenSTEM misinformation so that they are more aware of AI’s capabilities and how they could beutilized to alter their viewpoints on a STEM topic.1. IntroductionThe rapid expansion and adoption of communication technologies has led to the dissemination
has had such anexplosive growth in the last ten years. In fact, the FAA predicts that the number of slightlylarger UAS; those over 55 lbs, could exceed the number of general aviation aircraft by the mid-2030s. [1] It is important that academia stay ahead of any emerging technology to help developinnovative graduates and provide the appropriate knowledge and skills to succeed in industry. Itis no surprise then that academic institutions, and STEM programs in particular, areincorporating UAS into their education. As with any technology, this can present bothopportunities and challenges. This paper will outline the growth of the UAS industry anddemonstrate the need for partnerships between academia and the industry. Then, it will discussthe
of social programs.Dr. Cristian Ruz, Pontificia Universidad Cat´olica de ChileMr. Tom´as Andr´es Gonz´alez, Pontificia Universidad Cat´olica de Chile American c Society for Engineering Education, 2021 A Protocol to Follow up Students in Large-Enrollment Courses1. IntroductionIn response to the COVID-19 health crisis, two thirds of higher education institutions quicklymoved to online education [1]. As a result, students faced unexpected difficulties, such aslack of a good study environment, which affected their wellbeing [1]. Aware of thoseadditional difficulties, some institutions promoted a flexible approach, suggesting teachers toincrease communication with their
Society for Engineering Education, 2021 A Provisional History of the Idea of “Soft” vs. “Hard” Skills in Engineering Education soft adj. 1. not hard, firm, or rough. 2. not loud or bright. 3. gentle. 4. (too) sympathetic and kind. 5. weak, foolish. 6. (of drinks) nonalcoholic, 7. (of drugs) not highly addictive. soft option easy alternative. soft-pedal v. refrain from emphasizing --Oxford Mini Reference Dictionary and Thesaurus, p.598 disparage v. suggest that something is of little value or importance. syn. belittle, criticize, decry, denigrate, deprecate, minimize, run down, undervalue
psychology, when "students failed, not institutions" [1]. During the1980s, we began rethinking the causes and cures of minority student attrition when there was arealization that student-focused interventions would impact entering students' success [2]. Thisearly work on student retention ushered in what might be called the "age of involvement" [1],[3]. We have learned that belonging and involvement matter and are critical to success during thecritical first year of college [4], [5]. Further, as a profession, we have recognized we are intransformation (for example, The Engineer of 2020 [6]), and now, more than ever, "criticalthinking," and "learning how to learn" have become recognized as crucial attributes of teachingengineering fundamentals