spaces; is it the same or different?Our studyThis research project is investigating three very different universities with engineering programsthat have embraced the maker culture: University B, University A, and University C. Each ofthe spaces are different, reflecting the differences in the institutions. University B is first andforemost a technological institute with the majority of undergraduates majoring in engineering.Its maker space, housed within the Department of Mechanical Engineering, is operated by a 70person team comprising of 65 undergraduate volunteers and 5 non-student members. The makerspace comprises five rooms totaling 2,500 square feet that includes a rapid prototyping suitewith six 3D printers having various material
activities are described in detail in this section. The associated circuit layouts are shown inFigure 1. The example output involves the production of light, sound, and motion that are relatedto the operation of everyday devices, e.g. telephone, appliances, and toys. a) b) Figure 1. a) Flashing LED Circuit with Buzzer Output; b) Switching Circuit with Motor OutputA. Activity: Flashing LEDLight emitting diodes (LEDs) are used in several products as indicators to let the user know thatsomething is happening, such as the device is on. The 555 timer outputs a 3-Hz square wave thatcauses an LED to flash at a rate of 3 flashes per second while power is applied. This activity hasthree parts: 1) base circuit
existing, assigned, paper-basedengineering graphics problems. Students solve paper based problems while being able to see and“touch” the model with the MR application that is compiled for the Moverio see-through glasses.The Mobile App projects the model in front of the students’ eyes, allowing them to see the threedimensional (3D) representation of the objects in the problems right in front of them. This is asimilar experience to giving a real model of the problem to their hands which is not always possiblein large classes. Moverio has a mobile touchpad unit that is used to control the model and movethe user in a game-alike application. (A) (B) Figure 4 (A) Moverio
. Table 2: Mapping of courses and student outcomes in the problem state Outcomes Courses a b c d e f g h i j k 101 105 109 210 240 250 261 262
skills, and modern tools of the discipline to broadly-defined engineering technology activities b. an ability to select and apply a knowledge of mathematics, science, engineering, and technology to engineering technology problems that require the application of principles c. an andability conduct standard to procedures
exhibited nosignificant difference in responses, upper-division mechanical engineers at this institution go onto develop a greater overall physics identity and opinions of their design efficacies than doupper-division civil engineers. Future work will explore whether these differences persist acrossa broader range of disciplines and institutions. Further data analysis will be conducted on thissample to disentangle the potential effects of gender and race on the findings. Finally, the surveywill be given to the same students next year to monitor longitudinal retention rates and changesin engineering identity.References 1. Carlone, H. B.; Johnson, A. Understanding the Science of Experiences of Successful Women of Color: Science Identity as
97.6% 100.0 26 100.0 .3 Biology, Calculus AB, Calculus BC, Chemistry, Computer Science A, Physics C: Electricity & Magnetism, Physics C: Mechanics, Statistics, Physics B, Physics 1, Physics 2 SCPA CPS Urban 96.6% 99.2 20 29.7 1.7 Biology, Calculus AB, Chemistry Clark
Need drives innovation through collaboration INNOVATION TECHNOLOGY REAL NEED Clinical Lab Validations Translation into Applications Future Markets 0Magnetic Levitation Magnetic Levitation A frog levitated in very high magnetic field (>10 T)http://www.youtube.com/watch?v=A1vyB-O5i6EMagLev for Tissue EngineeringDisruptive Technology 4 4 Disruptive Technology Equilibrium position depends on: a) Cellular density
, and marine aquaculture. c American Society for Engineering Education, 2016Implementation and Evaluation of Visual Algorithm to Teach Benefit-to-Cost Ratio AnalysisIn the recent past, we developed a novel, visual, simple algorithm to teach incremental benefit-to-cost ratio (BCR) analysis to first- and second-year engineering students. The impetus behindthat endeavor was twofold: (a) BCR analysis is the most used technique for economic analysisand decision making in the public sector, and (b) to accommodate to the visual learning stylethat dominates in the engineering student demographics. In the present follow-up work, we: (1)carried out statistical analysis to assess the reception and
determine whether or not they were successfully entrenched into theSTEM pipeline.1 American Society for Engineering Education. (2014). Engineering by the Numbers. Washington, DC: Yoder, B. L.2 Bidwell, A. (2015, February 24). STEM Workforce No More Diverse Than 14 Years Ago. Retrieved from://www.usnews.com/news/stem-solutions/articles/2015/02/24/stem-workforce-no-more-diverse-than-14-years-ago3 Crosby, F. J., Iyer, A., Clayton, S., & Downing R. A. (2003). Affirmative action: Psychological data and the policydebates. American Psychologist, 58(2), 93-115.4 Peckham, J., Stephenson, P., Harlow, L., Stuart, D., Silver, B. & Mederer, H. (2007). Broadening participation incomputing: Issues and challenges. Proceedings from ITiCSE 2007: The 12th
Engineering Experience (FYEE) Conference, Pittsburgh, PA, August 8-9, 2013.6. Yoon, S., Imbrie, P., Reed, T., “First Year Mathematics Course Credits and Graduation Status in Engineering,” 6th First Year Engineering Experience (FYEE) Conference, College Station, TX, August 7 – 8, 2014.7. Tewari, D., “Is Matric Math a Good Predictor of Student’s Performance in the First Year of University Degree? A Case Study of Faculty of Management Studies, University of KwaZulu-Natal, South Africa,” Int J Edu Sci, Vol 8, No. 1, pg. 233-237, 2014.8. Hamlin, B., Riehl, J., Hamlin, A., Monte, A., “Work in Progress - What are you thinking? Over Confidence in First Year Students,” 40th ASEE/FIE Frontiers in Education Conference, Washington, DC
mathematical operations to convertthe rotation rate to a flow velocity. The created VI, shown in Figure 1, calculates both the linearvelocity of the fluid, the mass flow rate, and the volumetric flow rate. The VI also displays theoutput from the sensor on a chart. (a) (b) Figure 1: VI in LabVIEW™ to measure flow rate from sensor. (a) User Interface (b) Program code.Task 2: Water Flow RateIn the study of fluid mechanics one of the fundamental equations, = vA, relates the massflow rate, , to the velocity of the fluid, v, by multiplying the velocity by the area, A, of thepipe, and the density of the fluid, ρ. Students investigate the
) of women into engineering careers. Finally, assessment to trackfuture career and majors participants select will be collected using post-surveys administeredonce participants graduate high school.References 1. Backer, P. R. and Halualani, R. T. (2012). Impact of self-efficacy on interest and choice in engineering study and careers for undergraduate women engineering students. In: 119th American Society of Engineering Education Annual Conference and Exposition, San Antonio, Texas. 2. Beede, D., Julian, T., Langdon, D., McKittrick, G., Khan, B., Doms, M. (2011). Women in STEM: A gender gap to innovation. U.S. Department of Commerce: Economics and Statistics Administration. 3. Blickenstaff, J. C. (2005
, where approximately half the course is in 2Dconcepts, and the other half covers 3D concepts. This study pursues the assessment of anybenefits on spatial visualization by students having 3D concepts in addition to 2D concepts intheir curriculum. The study was completed at two institutions, in institution (A – University of Wisconsin,Waukesha Campus) there is now a hybrid semester course where half of the course usesAutodesk’s AutoCAD, and the other half of the semester is done utilizing Autodesk’s Inventor.The other participating institution (B – Western Michigan University) offers a semester coursewhich is based on instruction utilizing solid modeling packages, first Siemens’ NX and thenDessault Systemes’ CATIA. Table 1 summarizes the
demonstrate and stress the importance ofengineering problem solving and system investigation processes integrated with contemporarycomputer programming tools. Some of them are: a) Projectile motion problem solved by MATLAB m-file script using for/while loops then modeled using interactive GUI. b) Projectile motion problem solved using Simulink. Nonlinear equations can be solved with Simulink or by assuming constant acceleration over small increments of motion and writing a complex m-file. Both approaches are presented. c) A feedback control system (the plant is a basic spring-mass-damper rotational system) where the control is proportional, proportional + derivative, and proportional + derivative + integral
tubular structural engineering, Corby, UK, 1965 5. Right figure: Mr Joe Chilvers, an undergraduate student during a lecture at the University of Surrey, Guildford, 2014. b. Using physical models in a ‘making and learning process’ which implies that students will learn about structural concepts during the process of making physical models. In this case, the scale and the material used to make the models are some key factors of the method. Making small scale models is an
shown in Figures 1a and 1b that chart the decomposition of one part of a commonhumorous phrase. A B Figures 1a and 1b: Illustrating the ambiguity of possible syntactic POS parsing trees for a common humorous phraseTo a human reading the sentence: “Fruit flies like a banana”, humor arises as a result of the twosimultaneous existing and conflicting meanings of the sentence. Is the subject a tiny, butenormously aggravating insect or the general flight characteristics of fruit? After slightreflection, it is easy for a person to settle the conflict and judge the correct meaning based on thecontext of the conversation but it is much harder for a software program to do so. In order for amachine to proceed
were enrolled in some or all of the junior-level core courses in thefall of 2015, but this paper presents data only for the 48 who met the criteria of one of the“cohorts” described above. Two sections were offered for each of the fall junior-level corecourses, and each section contained exactly seven of the 14 summer cohort students and 16-18 of the 34 academic-year cohort students.Data: Course GradesTable 1 presents a comparison of the two cohorts using average course grades as the solemetric for student performance. The university scale for converting letter grades to gradepoint averages is A = 4.0, B = 3.0, C = 2.0, D = 1.0, F = 0.0. The university does use plus andminus modifiers (though there is no A+, F+ or F-), which are reflected in
knowledge and skill outcomes, (b) domain-specific efficacy in relation to situated learning,and (c) student engagement (deep vs. surface learning) and team dynamics. In this paper, quantitative andqualitative data collected over the past three years was analyzed collectively, triangulated, and related torelevant research and theories. This process allowed us to work toward: (1) providing a more generalizabledescription of our overall findings, (2) gaining a greater understanding of the underlying classroom and coursefactors and their impact on the development of domain-specific efficacy among minority students, and (3)developing a set of guidelines to effectively incorporate participatory design based on the situated learningframework. The
Instructor B were on aninstructional team together, teaching the same course in two different sections; Instructor Ateaches the lecture and Instructor B teaches the lab session. Instructor C and Instructor D werealso on an instructional team together with ten colleagues. Instructor C and D taught the samecourse in two different sections; Instructor C taught one lab session and Instructor D taughtanother lab session.Design Heuristic lesson resourcesEach instructor had access to Design Heuristics resources on a public website24, which includeda 28-minute lesson video, lesson slides in PowerPoint (PPT) (Figure 1) and links to researcharticles. Each instructor was also provided with multiple decks of Design Heuristic cards (Figure2). It was up to each
project evolved from a System Requirements Review to the Preliminary,Critical, and Final Design Reviews. This senior design project was especially notable for three factors:(a) the emphasis on an early implementation which facilitated multiple passes along the design spiral, (b)the close synergy between the evolution of the hardware and the simulation models, and (c) theinter-disciplinary nature of the design which provided opportunities for electrical engineers to consideritems such as material properties, forces on the barrel, temperature effects, aerodynamic drag, railablation, and velocity measurements. In the process of the design, students were able to leverage theircircuit analysis skills and build on their simulation experience in both
, R= rate, N= number of years.This rule is precise, but is most precise when you stay in the interest rate range of 7-9% as can beseen in Figure 4. Figure 4: Rule of 72 Error Percentage PlotSome Rules of Thumb that engineering students may be familiar with are: a. For every hour you spend in class, you need to spend two hours studying. b. Moore’s Law on Technology: “The number of transistors in a dense integrated circuit doubles approximately every 2 years.” …. And the list goes on.80/20 RuleHave you ever noticed that the majority of the work gets accomplished by a small group ofpeople? Another well-known Rule of Thumb is the 80/20 Rule which states that 80% ofoutcomes can
framework of this study, andrepresentation mapping model proposed by Hahn and Chater [42]. The postdoc and theinvestigator independently analyzed the first interview identifying the episodes and the type ofreasoning used by the participants. Then, they met to discuss and revise the differences in coding,and any disagreements among coders were resolved for the first interview. Problems were codedand evaluated according to the following steps: a) The cognitive supply of the participant and the instructor of the course were assessed by parsing episodes of reasoning in the individual's explanation. b) The structure and logic of the episode were decomposed to determine the type of
1 0.5 0 0 1 2 3 4 5 Mean grade: Math 103 and Chem 101 Figure 2. Relationship between final cumulative major GPA and the mean of each student’sgrades in freshman math and chemistry courses (p < 0.005, n=88). Course grades are converted to standard 4-point scale (A=4, B=3, C=2, D=1). 4.5 Final cumulative major GPA 4 y = 0.3504x + 2.0219
the Industrial Engineering (IE) program cover the knowledge, skills,and abilities required for Icesi’s students to achieve the program’s PEOs within a few years aftergraduation. These outcomes are based on ABET definitions for student outcomes. The studentoutcomes for the IE program are: a) an ability to apply knowledge of mathematics, science, and engineering b) an ability to design and conduct experiments, as well as to analyze and interpret data c) an ability to design a system, component, or processes to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability and sustainability d) an ability to function on multidisciplinary teams
(1989). In addition, Triad classification of the participants aredetermined to obtain the qualitative and quantitative results presented in this work.Key Words: Riemann integral, area, functions, concept image, concept definition, APOS theoryIntroductionAn important application of Riemann integral is determining the area between a single variablecontinuous function and the input axis. Given a continuous function f on the interval [a, b], thearea between the function and the input axis can be calculated by using the formula b Area = ∫ f ( x)dx aThis definition of area by using integral concept requires a well
conductivity characterization of supported and suspended graphene while publishing in such journals as Nano Letters, Applied Physics Letters, Journal of Heat Transfer, Physical Review B, and Science. As a Thermal Ad- visory Engineer for IBM’s Systems & Technology Group from 2011 to 2013 he designed and developed electronics thermal management solutions from the die level up to full server systems. Dr. Moore joined the mechanical engineering faculty at Louisiana Tech in September of 2013. He holds a joint appointment with the Institute for Micromanufacturing (IfM) where he works on advanced materials and devices for energy applications with an emphasis on nanoscale thermal energy transport. His graduate school focus
, students whoattended 1-3 sessions (few), and students who attended 4 or more sessions (regulars). Studentswho regularly attended sessions were 22±3% more likely to pass the course with an A, B, or Cthen those who do not go to any sessions (4). As the data were updated for another years’ worth ofcourses, the same general conclusions were made (Figure 1). The middle group of this figure(students who attended few sessions), has remained intriguing to the coordinators and authors.Effort was placed in trying to find out why students would choose to only go to a few sessions.The assumption, published in the author’s previous paper, was that this group of students onlyattended exam review sessions (4). This paper will illustrate the analyses performed in
students to how their understanding and enthusiasm were effected by using K’nexFinally the students were asked to respond to the following multiple choice question: What statement below most accurately reflects your opinion of using K’nex pieces in atechnical engineering course? a. They are useful and enhance the learning experience b. They are not particularly useful but they are fun and enhance the learning experience. c. They neither supported nor detracted from my learning experience d. The requirement to use K’nex posed a needless constraint that detracted from my ability to conduct a seismic experiment
, only one question was asked in thechemical engineering course, near the end of term: 1. If your goal was to separate chemical A (specific chemical included) from chemical B, which column design would you recommend be built? Why?The simulation questions were chosen to take a homework assignment and transform it into apotential real-life scenario. These open-ended questions required students to give an opinionabout their solution and sometimes forced the students to search for information that was notpresented in class. Solutions were not always obvious or straightforward, but in every casestudents did have the tools to arrive at the correct answer/recommendation. That is, no questionwas beyond the scope of their existing knowledge, but