can support producing small, intelligent, robust, multifunctional,and low-cost devices. Examples of MEMS devices are pressure sensors, inertial measurementunites (IMU), microphones, micro speakers, micro mirrors, switches, etc. Because MEMSintegrate microelectronic and mechanical components on a single chip, they have been used inmany applications such as biomedical [1], defense [2], aerospace [3], automotive [4], power [5],etc., and the need for such devices is rapidly growing. In addition, the number of companiesproducing such products are growing due to increasing demand from consumers and otherindustries. Some of the same microfabrication techniques used in integrated circuits (IC) are utilized tofabricate MEMS devices. These devices
, material propertyselection, and interpretation of model outputs as they relate to model selection and failurecriteria.The primary objectives of this work are to 1) discuss the challenges of learning the numericalmethod versus application of FEA with commercial tools in a single semester and 2) highlightthe importance of covering both topics by providing in-class and laboratory examples ofdeveloping and employing finite element analysis. Future work will be completed to assess theeffectiveness of these activities in enabling proper modeling techniques by students. The long-term goals of these efforts are to improve practical and ethical simulation for engineeringstudents and to further integrate these themes throughout the course.IntroductionThe
orvalues to be found by calculation. A problem archetype is created and encoded in such a way thatan automated algorithm may be able to create a set of random variables specific to the problemfor both sets of given information and information to be found.Figure 1: Flow diagram of randomized algorithm to generate fresh and correct problem inputs,outputs, solutions, diagrams, and textNext, numerical values are chosen for each variable of the parameter set that is to comprise thegiven information in the problem. Some values are chosen from uniform random variables andsome from gaussian distributed random variables. Each parameter has defined minimum andmaximum values based on what might be reasonable for a problem. A test for fidelity or efficacyis
that thegovernment investment and the professional categories have increased, as well as the scopeof college students raised year after year [1]. However, higher engineering education in Chinastill faces some problems, among which the most prominent problem is the separationbetween curricula setting and students' practical application [2-3]. On the one hand, thecurriculum setting still follows the typical deductive teaching approach to make sure that thestudents can understand and memorize each abstract concept. The basic theory courses,professional core courses, and practice courses are always well designed by variousspecialized teachers. On the other hand, this tightly sequenced and highly technical teachingoverlooks how the undergraduates
experiments,students analyzed the real beam system by characterizing the damping coefficient of the beam.They observed and measured the frequency changes of the beam with various loads applied.Students also observed and measured resonant frequency of the beam due to rotating unbalance.At the end, the experimental results were compared to the theoretical results. The newlydeveloped experiments have received positive feedback from students, as they have expressedthat these labs have helped them better understand course concepts.1. IntroductionEducators have developed various ways to teach the difficult topics of the dynamics behavior ofmechanical systems. Today, simulation software programs are available that accurately emulatemany technical and
of the EAMU vector is described and data collected from the 2018-2019 academic year is presentedto show both an increase in the fidelity of the assessment data and the creation of meaningful student performancedata trends over time.The ABET accreditation visit found no shortcomings in Criterion 3 – Student Outcomes. For this reason, this paper isapropos, as it may reduce challenges for any other mechanics-based programs seeking initial accreditation or thoseprograms seeking to revise their assessment framework in preparation for ABET accreditation.Introduction and BackgroundQuality assurance in engineering education is paramount [1], [2]. Programmatic and peer review contribute to boththe quality and relevancy of engineering programs by
which is a high-stake design-build-test whose themevaries from term to term. This paper describes three semesters of the course: Term 1 is Fall 2018, 1Term 2 is Spring 2019, and Term 3 is Fall 2019. The course currently underway is Spring 2020and referenced as Term 4.Students are tasked with a design-build-test of a mechanical device for the end-of-term“competition” to showcase their high-stake design project. This class employs a team of 20undergraduate teaching assistants (TAs) to help facilitate various aspects of the course and tostaff the laboratory around the clock during business hours. Two to three graduate TAs are alsoassigned to the course
ambiguity involved in determining damping in avibration system poses difficulty for mechanical engineering students to understand this conceptand capture its associated properties (damping coefficient, damping ratio, damping force, etc.).New instructional tools need to be developed for vibration classes to help the students to betterunderstand the role of damping in vibration theory and how damping elements function invibration systems.The role of damping in vibration theory had been fully demonstrated by Crandall [1] and a methodfor damping measurement was proposed by Carfagni et al. [2]. Engineering educators havedeveloped different approaches to enhance learning in vibration courses [3-8] but few attemptshave been dedicated to strengthen
requires students to develop knowledge and skills in mathematics, science,engineering topics, and professional skills such as information literacy and communication [1].Most programs put a larger focus on knowledge developed through coursework, but professionalskills are not systematically incorporated in the curriculum although professional skills areextremely important for meaningful employment. To prepare graduates for engineeringprofessions, the University of Michigan-Flint developed a professional skills workshop forengineering students. The workshop consists of seven hours of weekly sessions consideringtopics that are important but not presented in any courses. The workshops included threeimportant areas: engineering standards, investigating
from FORTRAN to Visual Basic to Maple andcurrently MATLAB. And while having used mostly a talk-and-chalk mode in the classroom inthe last century, the course has been taught formally in active-learning modes of blended andflipped learning since 2003.The blended modality in the course itself evolved over the years, and now approximately one-third to one-half of the class time is spent on active learning activities such as think-pair-share[1], conceptual exercises via handouts or clickers, in-class procedural exercises, and outlining ofprogramming projects and applied exercises. Many of these exercises are collected for a grade inthe class. Some applied exercises, though, are taken home by students and graded aftersubmission, as are the
numerous elements. The System Engineering and Freshman Designcourse at the University of Southern Indiana is intended to help students develop qualities neededto prepare them for the remainder of their collegiate courses and for their career. In addition,freshman students gain exposure to engineering design early in their college education which is 1essential to continuing in the engineering courses. Researchers suggest that the learner-learnerinteraction can enrich learning outcomes [1]. Thus, peer-oriented educational activities such as thecreation of a functioning miniature racing car are critical in the learning journey of engineeringstudents
uniform and consistent but alsoreduce the grading time, resulting in a higher grading efficiency. The rubric is a step towardsspecifications grading or ungrading—the term used to describe getting rid of grades—byemploying minimal grading as discussed by Elbow [1], which seeks to provide feedback ratherthan rank students. Tobin [2] presents a reading list of articles about ungrading. Though therubric studied still uses numbers, the aim is to communicate to students how well theyunderstood the concepts in a problem. This in turn allows the students to use their numericalgrade to determine if more time is needed to learn certain topics in the course material. Grigg [3]performed a study in which effort was made to use a newly developed assessment
instructors, and are distracted by competingdemands on their time. We found differences with regard to perceptions of student motivation,student abilities, and student engagement. Our findings are both consistent with and expandcurrent literature.IntroductionFundamental engineering courses serve as the foundation upon which advanced discipline-specific and professional courses are built. These courses are commonly required across multipleengineering disciplines and serve as pre-requisites to higher-level courses. Fundamental coursesintroduce and develop critically-needed concepts and skills [1], [2]. Students take severalfundamental courses concurrently, often during the early years in engineering programs, which isalso a period in their academic
problem properly addresses the topics desired, problems are oftendesired to be sufficiently unique or exciting, they must be error free and solutions to problemsmust also be calculated.There are several sources that faculty members can draw upon to find new problems. Textbooksare the first source that come to mind and each publisher painstakingly compiles hosts ofproblem sets in each and new editions with augmented problem sets are published yearly. Manypublishers also supply online learning systems for their textbooks that offer computer-basedmodules that contain problems. Often, the problems contained within the online learning systemscan even have their input values generated randomly [1]. Some educational groups have alsocompiled repositories
works have been presented at previous ASEE Conferences related with naturalfrequencies either calculated with a Matlab code, testing or using FEM including [1-3] thepresent work presents all three alternatives and the main difference with previous publications isthat the objective of this work is to pinpoint good practices using commercial finite elementcodes. The good practices in the implementation of a finite element analysis (FEA) presented inthis work are: a) Have a good understanding of the theory related to the problem to be solved. For this reason the solution of a cantilever beam is presented in this work in order to have an example whose analytical solution can be easily obtained. This is achieved solving for
student’s schedule.Universities generally staff career services offices for their students, offering a host of resourceson finding internships, writing resumes and cover letters, and practicing effective interviewstrategies. However, nearly 40% of students never even visit their universities’ career servicesoffices [1]. Disseminating useful information on career and professional development, therefore,must occur through the individual department. And, the timing of such exposure should be suchthat the student can contextualize any career advice received; giving students advice in interviewstrategies, for example, when they are in the midst of finding internships is more effective thanadvice given pre-college, which is naturally proffered in the
using several questions designed to addressstudents’ self-efficacy as well as core knowledge competence. The data from all surveys areanalyzed and conclusions are drawn regarding the effectiveness of the remote laboratoryimplementation.1 Introduction Incorporating active learning in STEM based disciplines has been shown to improvestudent engagement and overall classroom performance [1], [2]. In particular, improvements instudent performance in engineering courses has been linked to the integration of an activelearning environment into the classroom [3], [4], [5]. This is well documented and it should notbe surprising that an active learning approach is especially beneficial for engineering students.One of the primary means of
. The later includedpresentations at the Undergraduate Research & Creativity Colloquium. Assessment was based onstudents’ (1) work; (2) peer evaluations using Comprehensive Assessment of Team-MemberEffectiveness (CATME), a web-based tool; (3) surveys during the CP experience; and (4)surveys in post-requisite courses. The comparison of these assessments provides cross-sectionaland semi-longitudinal results. Cross-sectional results obtained in post-requisite courses indicatedthat CP students in comparison with non-CP students, typically had a higher level of agreementthat they understood thermodynamics; had built professional camaraderie with some of theirengineering classmates in thermodynamics; were excited to do undergraduate research; and
practice.IntroductionLearning to consider the broad context of their work can help engineers develop better solutions.These solutions may also be more sustainable, economically feasible, and socially just and makepositive change in the world. Helping students recognize that engineering itself is sociotechnicaland consider the global context of their work is a goal of both University of San Diego and anelement of ABET requirements [1]. It is also a significant challenge. Material that addressesthese issues can be challenging to integrate into many traditional engineering courses.Faculty at the University of San Diego’s Shiley Marcos School of Engineering are developingnew ways to meet this challenge. In recognition of the University’s work in social innovation,peace
tether to winch itself up the wall. The mind maps werefound to be effective in assisting the development of concepts for wall-climbing capability andthe resulting two prototypes showed definitive feasibility of the two wall-climbing concepts.1 INTRODUCTIONThe capability for a robotic system to climb walls has many advantages. In addition to providingenhanced ability to gather intelligence, surveillance and reconnaissance (ISR) information, manytimes there is a need for the robotic system to move from level to level inside a structure.Robotic systems that fly can, of course, accomplish this “wall-climbing” capability. However,flying systems have at least two significant drawbacks. First, they most often consume far morepower than a
electrical and computer engineering majors[1]. The SEC was developed through Rose-Hulman's participation in the Foundation Coalition,an NSF-funded engineering education coalition [2]. By 1998, this curriculum grew to includemechanical engineering majors and later added biomedical engineering majors. The curriculumoriginally consisted of eight courses representing 30 credit hours in a 10-week quarter system.By restructuring the material, the SEC tried to explicitly demonstrate common threads within thetopics typically covered by a course on statistics, two courses on differential equations, and fiveengineering science courses: Fluid Mechanics, Thermodynamics I, Dynamics, Circuits I, andSystem Dynamics. Over its 23-year-life, the SEC has evolved and
completing all thirty problems. As was mentioned previously, each extracredit point (including the bonus points just mentioned) was added to students’ exam pool. Witha maximum of 35 bonus points attainable this amounted, considering the weighting of exams tothe overall course grade, to a maximum of 5.25% for both classes.The end of the challenge period roughly corresponded to the end of the semester at which pointstudents were asked to complete a voluntary survey to gauge their level of participation in thechallenge and whether or not they felt they had benefitted from it. In both courses, students wereasked the same survey questions. Some of the questions surveyed the students about theirvoluntary participation in the challenge asking them (1) why
ethics and effects of students’ useof solution manuals on their performance during exams [1-6]. One study surveyed the facultyand students in a large mechanical engineering department to seek their perspectives on theethics and the educational values of employing solution manuals in solving textbook homeworkassignments. Many instructors had ethical concerns regarding the students’ use of solutionmanuals, while many students did not consider the use of solution manuals as scholasticdishonesty [1]. Few studies have shown that the use of solution manual has an adverse effect onstudents’ learning [2-4]. Other studies have suggested few new strategies for assigninghomework problems [5, 6].The authors of this paper have been teaching engineering
systems. After describing the hardware stack and the design decisions that led to itsselection, this paper provides results in terms of students’ self-efficacy and attitudes towards theuse of the hardware platform. The results show that the students have been positive about thisnew approach to teaching sophomore design, while offering suggestions for improving theexperience in the future.Much work has been done on the use of Arduino hardware to teach mechatronics and controlsconcepts [1-9]. Among these the most closely related to the current work is [7], which describesthe selection of a hardware kit for teaching feedback control that emphasizes usability. Typicaluses for Arduino-based educational platforms outside of control systems and
educators on how certainproblem-types can be more or less conducive to emotional responses that may deter or encouragestudent learning and performance.IntroductionAcademic emotionsStudents’ academic learning, performance, and persistence has been an ongoing topic ofdiscussion among motivational researchers, educational researchers and psychologists [1]. Inparticular, academic emotions have been a key focal point of discussion [1]. Academic emotionsoccur when students attend a class or participate in class-related tasks (e.g., exams) [2]. Theseemotions entail coordinated and multi-component processes that integrate emotive, cognitive,motivational, expressive, and peripheral physiological subsystems [2]-[5]. For example, a studentmay experience
thisintegrated active learning approach for teaching fatigue theory. 100 percent of students agreedthat they had a much better basic understanding of fatigue theory through this multi-facetedapproach. This paper will present and explain in detail the integrated active learning approachfor teaching fatigue theory. The class survey data analysis is also presented and analyzed.1. IntroductionFatigue is defined as failure under a repeated or varying load. This load never reaches a levelsufficient to cause failure in a single load application. Fatigue damage or failure is initiated andinduced through some defects on the surfaces and/or inside components. The defects could bemanufacturing process induced scratches on the surfaces or dislocations, impurities
portrays a desire tocreate graduates with an andragogical mindset, despite the relative absence of the use of the termandragogy in engineering education literature. Pembridge developed a pilot instrument tomeasure andragogical constructs utilizing different instruments directly measuring the theoreticalframeworks supporting assumptions of adult learning, while also comparing responses from first-year and fourth-year engineering students.1 He found significant differences between the twoyear groups of engineering students, with fourth-year students having improved ability at self-directed learning and a stronger sense of adulthood. It is unknown how these results apply to acadet population, where increased structure and additional military training
connections. In previous terms, students have said it was difficult for them tounderstand how to apply control systems topics in their field. Based on this feedback, Iconsidered course improvements to address this deficiency. I identified two possible causes forlearning difficulties: lack of connections to prior knowledge and lack of motivation for the topic.According to Ambrose, Bridges, DiPietro, Lovett, and Norman [1], sufficient and accurateconnections to prior knowledge can support learning. Therefore, helping students accuratelyidentify interactions with courses topics in everyday life should aid learning. Additionally, basedon the expectancy-value theory of achievement motivation, it follows that a student will likely beless motivated to learn
real-world hydraulic and pneumatic applications. Building on initial work [1], thepresent study adds indirect assessment for both courses, previously unavailable direct assessmentin Thermodynamics, and additional data points for indirect and direct assessment in FluidMechanics.Fluid-power based modules for Fluid Mechanics and Thermodynamics courses were developedfor potential continued future use that utilize active and collaborative learning (ACL), problem-based learning (PBL), and entrepreneurially-minded learning (EML) techniques to teach coreBSME content while also creating awareness and engaging students in the area of fluid power.Active learning requires that students participate and discuss issues or work problems in theclassroom
response of a mass/spring/damper system to a sinusoidal input.An in-class survey revealed that the lack of interest was coming from not understanding theimportance of sinusoidal inputs. The students agreed that mass/spring/damper systems areboth practical and prevalent in the real world. However, roughly half of the students seesinusoidal inputs as no more important than any other input to a dynamic system. Thesurvey results from early in the course are shown in Figures 1-5. The first two questionssought to assess whether or not the students really were disinterested in the lecture. Questions3 & 4 asked whether or not students believed mass/spring/damper systems are important.Question 5 asks about the importance of sinusoidal inputs for system