Paper ID #28822A faculty-directed Continuous Improvement regimen with intentionalABET/SO 1-7 scaffoldingDr. Vallorie Peridier, Temple University Vallorie Peridier is Associate Professor and Associate Chair of Mechanical Engineering, Temple Univer- sity (Philadelphia, Pennsylvania). She holds a BA in physics (Bryn Mawr College), a Ph.D. in engineering mathematics (Lehigh University), and she worked in industry seven years prior to joining the engineering faculty at Temple University. Dr. Peridier is also the BS ME Program Assessment Coordinator for the College of Engineering c American Society for
. Overall studentperformance in major assignments shows improvement in the blended class as compared to theregular class, thus indicating better knowledge retention in the redesigned course. Finally, theredesigned course shows active class engagement as obtained from video analytics data.1. IntroductionIn recent years, education in the STEM field has transitioned from traditional face-to-faceinstructional models to newer learner-centered approaches. An important aspect in these newerpedagogical models is integration of technological tools with traditional methods. As reported inliterature, the positive outcomes of technology-reinforced learning in STEM education includepositive attitudes toward content learning, greater retention of direct content
real-time polling software Poll Everywhere (2019) asked one quantitativeand one qualitative question regarding the qualifications reflected in the resume before them.FindingsA total of 36 students participated in this exercise. Students who received Candidate 1’s resume(first name on resume: “Julie”) were asked “You are the recruiter at a defense contractor seekingto fill an entry level structural engineering position. How likely are you to offer Candidate 1 aninterview?” Students were provided response options on a 5-point Likert-type scale, which wasdisplayed as a bar chart in real time for the class. As shown in Figure 1, no students indicated a“Very high likelihood” of offering Candidate 1 an interview and one student indicated a “Verylow
assignments such as, theselection, quantity, tasks associated with each simulation, grading criteria, credit assigned, andstructure. All of these might influence student skill building, understanding of material, andproblem-solving performance. This paper aims to address: (1) comparison of student load relatedto assignments, and (2) assessment of student understanding of select theoretical concepts. Forthe comparison of student load, highlighted differences in the course sections include: (a)number of simulation assignments (3 - 10), (b) number of application assignments (none or 3),and (c) the credit given to these assignments (2.5% or 15%). Surveys were administered to assessstudents’ confidence in the usefulness of each simulation assignment, and
grade. However, homework also represents a primary way that student’slearn new material. Additionally, homework that achieves elements of metacognition has beenproven to increase learning[1].This is a study of a method that enforces self-evaluated and revised student homework that wasused at the United States Military Academy (USMA) over the course of four years in upper levelmechanical engineering classes. Students completed a homework assignment by the due date.They then scanned and digitally submitted their work to the instructor (via email or an onlinesubmission portal through a Learning Management System). This established a record of whatthey accomplished on their own. After the initial due date had passed, the instructor published
Illustrator, Microsoft Word, Excel, Origin American c Society for Engineering Education, 2020 Paper ID #31061AWARDS • Chancellor’s Award at University of Wisconsin, Milwaukee • Texas A&M University Engi-neering Scholarship • Dean’s Honor List at Korea UniversityACTIVITIES/COMMUNITY SERVICE • Volunteer Judge at Texas Science and Engineering Fair • Trea-surer of International Christian Fellowship at Texas A&M University • Volunteer Teacher at Vision Ko-rean School in College station, TX • Volunteer Teacher at Saenal Night School in SeoulPUBLICATIONS 1. H. Kim, X. Huang, I. Guo, S. Cui, Z
domains.IntroductionConcept maps, as facilitative tools for learning, was developed by Novak and others in the late1970s [1]. The idea was to represent ‘knowledge domains’ in a visual, logical sequence with anemphasis on the relationship between the various elements or ‘concepts.’ At the very least,concept maps help to organize the contents of a knowledge domain. At its best use, concept mapshelp students recollect prior knowledge, link the various courses in liberal arts, science and math,engineering, and economics and summarize their learning. A list-based syllabus does not connectthe previous knowledge to the one pursued in the current course. The syllabus also does notenlighten the student about the holistic nature of transdisciplinary education in the
while satisfying the need for institutional accountability.ePortfolios help to facilitate deeper understanding of course content, make the curriculum morerelevant for students, and build connections between classroom and professional learningcompetencies. Of importance to this investigation is the emphasis placed on 1) personalreflection in the context of developing required competencies in engineering practice and 2) theinterconnected roles of emotional engagement and cognitive engagement. Results from studentevaluation questionnaires suggest that ePortfolios effectively connect teaching, learning, andindividualized assessment, making them a valuable pedagogy in engineering education.IntroductionePortfoliosEmployers nowadays focus less on
to be a useful tool for connecting and organizing course topics forboth students and instructors.IntroductionConstructivist learning theory, in which learners create their own meaning of new material andmake connections with prior knowledge, is the basis for a variety of active learning approaches[1], [2]. Creating a concept map is one way for students to represent connections between ideas.Concept maps, or mind maps, are visual representations of the organization and connectionsbetween pieces of information [3]–[5]. Relationships between various concepts are shown byconnecting lines or arcs. Concept mapping has been used as an educational tool for more thanthirty years, but has recently gained attention in STEM (science, technology
. Theevaluation of wide-ranging curriculum changes also provides a good opportunity to considercurrent and future trends, both in technical content as well as the various needs of stakeholders(students, faculty, industry). In their early history, engineering schools focused on practicaltechnical skills for industry but later shifting the emphasis to engineering science [1]. Morerecently, trends have focused on increasing hands-on learning, design/build/test, and increasedflexibility in curricula.This paper focuses on using curriculum benchmarking of other engineering programs as aninitial step in a larger curriculum review process, as applied to the Mechanical Engineeringprograms at the University of Pittsburgh (Pitt) and Carnegie Mellon University (CMU
systems to differentexcitations help students understand the characteristics of various responses, such as transientresponses and steady-state responses, resonance and damping effect on the responses excited byharmonic forces. As an application, an airplane has been modelled by using a three-DOF system(fuselage and two wings) in this paper for studying its inherent properties and vibrationresponses to various inputs.1. Introduction Vibrations are undesirable and harmful in most cases in mechanical systems and structures[1]. Noise, vibration and harshness (NVH) control, for example, has long been an importantresearch in automotive industries. Vehicle NVH characteristics influence customer’s perceptionof quality and comfort. The annoying
. Overall, the course aims to teach students analog/digitalsensing technologies, actuation hardware, Proportional-Integral-Derivative control, andmicrocontroller software implementation from a system-level teaching approach ensuring cross-functional debugging skills for each lab. This approach can be advantageous towards studentscompleting their semester project in the design and development of their own mechatronicsystem.IntroductionFrom agricultural to space exploration, mechatronics is an important branch of engineering forunderstanding and solving complex multidisciplinary problems. The engineering workforce hasdemanded more of engineers acquiring mechatronic skills as our society expands for moreintegrative technical products and services [1
learning is becoming more common in engineering education. Litzinger et al.argue that expertise is developed through significant learning experiences such as applyingknowledge to real-world problems [1]. Solving real-world problem increases student motivationas well as promotes deep learning and development of expertise. Improvement in engineeringeducation can be realized by the introduction of more “authentic” learning experiences.Authentic learning is social as well as cognitive and includes interpersonal communication, self-directed research, and a focus on the customer just like in a real workplace [2]. Business contextis another element of authenticity. Projects that enhance the ability to create value areworthwhile for both budding
, 2020WIP: The predictive power of engineering undergraduate students’ academicself-efficacy and test anxiety for their academic performance in a dynamicscourse Introduction Self-regulated learning (SRL) is a vital factor that positively affects students’performance in academic settings, as a wealth of study findings have shown [1], [2]. SRL hasreceived increasing attention from the engineering and technology education researchcommunities as of late [3]. Considering that low academic performance is one of the reasons thata large number of engineering students leave engineering majors and transfer to another major[4], it is important to explore factors that contribute to academic performance in
. Furthermore,increased long-term retention of engineering content can better prepare students to havesuccessful and fulfilling careers after graduation, particularly in technical fields.There are numerous studies in the literature that discuss a variety of strategies to increase studentengagement in engineering courses, which in turn help them learn the material more effectively,allow them to better persevere in an engineering curriculum, and consequently graduate in atimely manner [1]–[3]. In this study, we focus on the role of assessment in helping studentlearning because of the demonstrated connection between teaching, assessment, and learning [4].The literature on educational assessment makes an important distinction between “assessment oflearning
vibration analysis courseBackgroundThe origins of mastery-based-learning (MBL) find a root in the idea that, with enough time, allstudents with the appropriate prerequisite understanding could master any new topic [1]. In atraditional grading scheme, all students progress through topics and the same rate. At the end ofa unit, an exam is used to assess student mastery. All students then move on to the next unitregardless of their performance on the previous exam.In a typical mastery-based approach, an individual student must demonstrate mastery of onetopic before progressing to the next topic [2, 3, 4, 5]. An MBL approach built upon a largenumber of tiered specific skills guarantees all students earning a particular grade in a course
courses incomposition and presentation, often being some of the first courses taken. This extends toengineering students, for whom effective communication is an important competency [1] and arequired criterion for degree accreditation (ABET - Student Outcome 3: an ability tocommunicate effectively with a range of audiences). The University of New Haven hasidentified writing skills as a priority and established Writing Across the Curriculum (WAC)initiative to support writing instruction throughout a student’s undergraduate career.In 2011, the College of Engineering at the University of New Haven carried out a survey ofalumni and employers to investigate the skills needed specifically of and by engineeringgraduates. From this, it became apparent
known as constraint-based CAD, allows users to capture design intent and totake full advantage of the desktop computer as a design tool. As a result, required courses in ComputerAided Design have become ubiquitous in undergraduate Mechanical Engineering programs.Typically, students are introduced to the basics of spatial visualization, the theory of variousprojection techniques and the preparation of engineering drawings, all the while mastering themechanics of using a particular software package. As with many courses in today’s credit-starvedcurricula, teaching a CAD course presents a unique set of challenges. Perhaps foremost is the varyingstarting abilities of the students [1]. Some may be distracted by computer graphics, trying to makeparts
the growing demand for online learning fueled by the generationallearning preferences.IntroductionAccording to USNEWS, more students have taken online courses than ever before and thatnumber continues to climb as more programs augment their on-campus offerings with onlinelearning opportunities [1]. Besides the obvious advantages, numerous studies have demonstratedthat online learning can have the same or better learning outcomes as face-to-face courses [2]. Areport on the emerging engineering education leaders identifies blended learning practices as acornerstone of these programs [3]. In fact, an argument can be made that instructors who teachan online course improve their teaching because every element of the online learning experienceneeds
through the volumes worth of materialwritten on the subject in order to simplify the topic of entropy to something that is clear and easyto understand. To accomplish this, the paper contributes by (1) introducing examples ofspontaneous processes that most people should already understand, (2) providing a brief reviewof the general operations of heat engines and the Carnot cycle, (3) framing the Carnot cycle inrelation to entropy, (4) discussing non-ideal heat engines, (5) showing analogies to help thereader understand the significance of the ratio Q/T as a definition for entropy, (6) adding somebrief notes on entropy that are beyond the general scope of this paper, and (7) presentingbrainteasers designed to engage students in the classroom. We
CourseAbstractThis study reports on addition of a simulation module based on Finite Element Analysis (FEA)to Mechanical Engineering Materials and Laboratory course at University of Hartford. The studyaddresses two topics: (1) mastering different levels of knowledge with the help of simulations,and (2) honing new simulation skills. The course has a weekly lab session where studentsperform various materials testing such as tensile, shear, bending, and impact. The lecture portiondeals with the theories behind materials’ formation, bonding and how those relate to the materialproperties. In the recently added simulation module, students were assigned projects to simulatethe mechanical testing procedures performed in the lab. The simulations were done using
were presented with the overall aim of the project:collecting and processing IMU data for a compelling consumer application.Each week of the project had its own goal and deliverable. The deliverable was presented duringa five minute in-class appointment with the instructor each week to help students remain ontrack. Additional details on deliverable assessment are provided in the project assessment sectionbelow. Table 1 presents a brief description of the goal and deliverable for each of the five weeksof the project as taken from the project handout. The complete project handout, as presented tostudents, is also available at the end of this paper in Appendix A.Table 1: The goals and project deliverables by week. Week 1 Goal: Get your IMU up
enthalpy profile basedon inlet boundary conditions (inlet flow and temperature), a nonuniform axial powershape, and a specified operating pressure. The first law is defined as follows1: dEcv V2 V2 Q cv W cv m i hi i gzi m e he e gz e (1) dt i 2 e 2 The pressure drop is based on the equation resulting from a mechanical energy balancefor an incompressible fluid2: pi Vi 2 pe Ve2 zi h ze hTurbine hL (2
questions on the effect of interprofessional PBSLprojects on learning orientation, communication skills, and teamwork. 1. How do various aspects of the interprofessional PBSL project (e.g. it’s interprofessional and service aspects) influence attitude and motivation towards course material? 2. How do engineering students balance interprofessional aspects of their coursework with technical aspects? 3. What communication challenges do engineering students face when collaborating with SLP students on a PBSL project?Instructional designOur action research team included a ME faculty member, a SLP faculty member, and aninstructional designer. Elements of the interprofessional PBSL project were designed to alignwith student outcomes
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