(4) * h exit ? h inlet / j s h inlet / h exit , s + (5) Ã 1 ÔÃ 60 Ô Torque ? m% r *h inlet / h exit +Ä ÕÄ Õ (6) Å N ÖÅ 2r ÖThe pressure loss through the condenser was specified at a constant value and the exit pressurewas found by subtracting the loss from the inlet pressure. In the actual condenser there is apossibility for the refrigerant exiting to still be superheated, saturated, or liquid. At this stage itwas assumed that the exit enthalpy of the
68HC11 processors. TheMC9S12DT256 features the core cpu along with a variety of ancillary components on the chip,such as: ADC(s), asynchronous serial port(s) (SCI), Motorola sponsored synchronous serialperipheral interface(s) (SPI), Pulse Wide Modulation interface (PWM) plus others.One of the Bluetooth3 devices used to define the communications channel of the project was theConnectBlue OEMSPA 13i serial module. It is mounted on a development kit board that allowsfor convenient prototype wiring. The module supports RS232 signal interfacing (TxD, RxD,plus handshaking) and direct UART signal interfacing (TxD, RxD, plus handshaking). Themodule has 64KB of SRAM and 512KB of flash. Resident on the device is a Bluetoothembedded host stack. The other
found that only 61% of the students who took ourfirst semester engineering course (ENGR 101) continued as an engineering major in thesubsequent year. We believe that many of those who left engineering after the first year wouldhave continued in engineering if they had a more encouraging, helpful, personal, and stimulatingfirst year experience. Many other universities have recognized the importance of the first yearexperience as well and have revamped their first year introductory engineering course(s) [1-5].The goals of this introductory course are to provide students with basic skills for success, toenhance their interest in engineering and to cultivate their sense of belonging. Because of therecent decline in engineering enrollments [6], this
temperature response for the two fluids which areinvolved in the process. Moreover, the response of the system is analyzed in real-time with the useof MATLAB® and Simulink® software, including the Simulink S-Function block. This block isused to generate real-time solutions for nonlinear systems which can be modified and updated bythe user as the simulation is being conducted, similar to a physical system.The virtual crossflow heat exchanger simulation software incorporates three MATLAB ® scriptsincluding an initialization script, a calculation script, and an S-Function script, in addition to aSimulink® data file containing the user interface and the block diagram of the system. As shownin Figure 2, the simulation sequence is performed beginning with
concepts explained the following application of Reynolds transport equation is effectively the formulation of the Second Law of Thermodynamics :- Page 11.227.7 S%in / S%out - (m% s ) in / (m% s ) out - S% gen ? S%CV Second Law of ThermodynamicsNet Direct Entropy Transferred in(i.e. Via heat conduction) Net Energy accumulated in the control volume
failed to benefit from their mentor. The selection processused to pick mentors and mentees was also investigated with the research questionnaire to furtherunderstand student preferences and specific needs of those majoring in STEM fields.The sixty-four (N=64) participants represents a diverse sample of graduate students who pursueundergraduate STEM degrees. Students reported their mentors helped with the following: 1) providingfunding, setting goals, providing positive and constructive feedback on their work, and being supportiveof ideas which allowed the mentee to follow his/her own ideas for their work. Alternatively, someparticipants reported unmet expectations by their mentor(s), such as wishing the mentor had: 1)provided more exposure to
(2005).7. National Academy of Engineering. The Engineer of 2020: Visions of Engineering in the New Century. (National Academies Press, 2004).8. Page, S. E. The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies. (Princeton UP, 2007).9. Seymour, E. & Hewitt, N. M. Talking about Leaving: Why Undergraduates Leave the Sciences. Contemporary Sociology 26, (Westview Press, 1997).10. Moller-Wong, C. & Eide, A. An engineering student retention study. J. Eng. Educ. 86, 7– 15 (1997).11. Imbrie, P. K., Lin, J. J.-J. & Reid, K. Comparison of four methodologies for modeling student retention in engineering. in ASEE Annual Conference and Exposition, Conference
support faculty in their attempt toimprove teaching. Next steps for this research is to use continuing data from courses taught thispast year to see if the trends do indeed continue, or analyzing additional evaluation questions.References1. Anderson, O. S., & Finelli, C. J. (2014). A faculty learning community to improve teaching practices in large engineering courses: Lasting impacts. Proceedings of 2014 ASEE Annual Conference & Exposition, Indianapolis, IN.2. Barr, J., Benton, S., Li, D., & Ryalls, K. (2016). Response to bias against female instructors. IDEA Editorial Note No. 2. Manhattan, KS: Kansas State University, Center for Faculty Evaluation and Development.3. Benton, S. L., & Ryalls, K. R. (2016). Challenging
make sure that we continually connecthigher with the lower knowledge. This is the wayo Integration of Physics in the State-of-Art technology courses:• MMIC Design and Fabrication In this course, the author covers a variety of topics including connecting ABCD parameters ofcircuit theory, S-parameters in microwaves, Low noise, High power and broadband amplifiers, oscillatorsand connection of S-parameters with device physics parameters such as trans-conductance. However,examples are chosen from transmission line losses, input impedance and stability of amplifiers based onS-parameters.Example 1: A lossless transmission line is connected to a load with 𝑍! =0. The characteristic impedanceof the line is 50Ω. (a) Plot 𝑉 𝑥 as a function
Press, 2007).5. Freeman, S. et al. Active learning increases student performance in science, engineering, and mathematics. PNAS Early Ed. (2014). doi:10.1073/pnas.13190301116. Hake, R. R. Interactive-engagement versus traditional methods: A six-thousand-student survey of mechanics test data for introductory physics courses. Am. J. Phys. 66, 64–74 (1998).7. Hora, M. T., Ferrare, J. & Oleson, A. Findings from classroom observations of 58 math and science faculty. Madison WI Univ. Wis.-Madison Wis. Cent. Educ. Res. (2012).8. Fiore, L. & Rosenquest, B. Shifting the culture of higher education: Influences on students, teachers, and pedagogy. Theory Pract. 49, 14–20 (2009).9. Hjalmarson, M. et al. Developing interactive teaching
, chemistry, and mathematics. Each respondent alsomet the following requirements: 1) The student identified his/her race/ethnicity as Black/AfricanAmerican on his/her application to Tech College; 2) The student stated that s/he was educated ina high school either in the U.S. or in a sub-Saharan African country; 3) The student enrolled atEC prior to transferring to Tech College; 4) The student was at least 18 years of age at the timethat s/he participated in the research study. A roster of Black transfer students was generated by the Admissions office at LandingUniversity (Landing University is the main campus on which Tech College of Engineering andseveral other academic colleges is housed). After obtaining this roster, undergraduates who
) q[n] DCC s[n] RFFE A/D (N) q(t) q[n] s[n] t n nFigure 2: Illustration of the software defined radio receiver and its operation in converting an in-tercepted analog passband signal r(t) to a digital baseband signal s[n]. The analog-to-digital con-verter (A/D) identified in the illustration is emphasized at the beginning of the course to highlightthe importance of the translation between the analog and digital domains.Cyber-Physical Systems (CPS) and Internet-of-Things (IoT).In
Paper ID #18647ECE Teaching and Learning: Challenges in Teaching Digital Signal Process-ingDr. S. Hossein Mousavinezhad, Idaho State University is the principal investigator of the National Science Foundation’s research grant, National Wireless Re- search Collaboration Symposium 2014; he has published a book (with Dr. Hu of University of North Dakota) on mobile computing in 2013. Professor Mousavinezhad is an active member of IEEE and ASEE having chaired sessions in national and regional conferences. He has been an ABET Program Evaluator for Electrical Engineering and Computer Engineering as well as Engineering Education
visualizationskills, both, for development of imagination and creativity, as well as development ofcompetencies directly related to technical fields such as engineering graphics and design.In this field of graphics and design, which is more linked to STEM education, there are acceptedtest such as the Purdue Spatial Visualization Test - Rotations PSVT:R (Guay, 1977), the MentalCutting Test (MCT) (Sorby, 1999) and the Shepard-Metzler Rotation (S-M) Test (Shepard, 1971)and its modification (Vandenberg, 1978). All of these tests have been used to measure thevisualization skills in an individual at a given time, thus providing a reference for comparison. Theunderlying concept in these tests is the mental rotation of 3D given objects. PSVT:R is perhapsone of the
=conference_papers&space=12974679 7203605791716676178&type=application%2Fpdf&charset=Corbin, J., & Strauss, A. (2015). Basics of qualitative research: Techniques and procedures for developing grounded theory. Thousand Oaks: Sage.Johri, A., & Olds, B. M. (2011). Situated Engineering Learning: Bridging Engineering Education Research and the Learning Sciences. Journal of Engineering Education, 100: 151-185. doi:10.1002/j.2168-9830.2011.tb00007.xJohri, A., Olds, B. M., & O'Connor, K. (2014). Situative Frameworks for Engineering Learning Research. In A. Johri & B. M. Olds (Eds.), Cambridge Handbook of Engineering Education Research (pp. 47-66). NY: Cambridge University Press.Kusano, S., &
to employment. In the future a survey will be made of alumni addressingthat underlying goal as more alumni have performed their capstone projects in this way.AcknowledgmentsThis work was partially supported by a grant from the Student Activities Committee of the IEEEConnecticut Section. The authors would like to acknowledge and publicly thank the section forall of the support provided, both financial and otherwise.References [1] K. Chintalapudi, A. P. Iyer, and V. N. Padmanabhan, “Indoor localization without the pain,” in Proceedings of the sixteenth annual international conference on Mobile computing and networking. ACM, 2010, pp. 173–184. [2] J. Duckworth, D. Cyganski, S. Makarov, W. Michalson, J. Orr, V. Amendolare, J. Coyne, H
Academies Press.[2] T. A. Lamb, K. Petrie, Development of a Cognition-Priming Model Describing Learning in a STEM Classroom. Journal of Research in Science Teaching, Vol. 52 No. 3, 410–437, 2015.[3] Z. Aguirre-Munoz, M. L. Pantoya, Engineering Literacy and Engagement in the Early Years, Journal of Engineering Education Vol. 105 No. 4, 630-654, 2016.[4] S. Carey, E. Spelke, Domain specific knowledge and conceptual change. In H. Wellman & S. Gelman (Eds.), Mapping the mind (pp. 169 – 200). Cambridge, England: Cambridge University Press, 1994.[5] R. Gelman, K. Brenneman, Science learning pathways for young children. Early Childhood Research Quarterly, Vol. 19, 150 – 158, 2004.[6] J. Piaget, The
the relative velocity. Their resulting calculation of Coriolisacceleration is plotted in Figure 3 above. For the experimentally determined Coriolisacceleration, the team reached a value of 0.1305 m / s 2 while their theoretical calculation wasfound to be 0.1608 m / s 2 . A sample is given here from the team’s concluding remarks:“From our data we can conclude that we successfully isolated the phenomenon. We did this bycalculating our theoretical acceleration and comparing it to what the sensors actually recorded.Areas of improvement would be a more rigid base, smoother running surface, a constant angulardrive and linear velocity for the car.”B. Sample 2: “Trebuchet”The students in this project constructed a homemade launching apparatus known
use that information to develop and testinterventions that may accelerate student development of engineering intuition.References1 Raskin, P. Decision-Making by Intuition--Part 1: Why You Should Trust Your Intuition. Chemical Engineering, 100 (1988).2 Gigerenzer, G. Short cuts to better decision making. (Penguin, 2007).3 Kahneman, D. Thinking, Fast and Slow. New York, NY: Farrar, Straus, and Giroux. (Macmillan, 2011).4 Elms, D. G. & Brown, C. B. Intuitive decisions and heuristics–an alternative rationality. Civil Engineering and Environmental Systems, 274-284 (2013).5 Dreyfus, S. E. & Dreyfus, H. L. A Five-Stage Model of the Mental Activities Involved in Directed Skill Acquisition (1980
expectationsfrom engineering and technology graduates. To stay competitive, engineering andtechnology students need to learn the latest software used in their associated fields as wellas to understand relevant modeling and simulation frameworks. To provide students abetter learning experience discrete-event modeling software based hands-on learningexamples are developed and implemented for the junior level Facilities Planning course.This paper shares examples of the hands-on learning activities that are incorporated intothe Facilities Planning course.IntroductionAccording to the International Facility Management Association (IFMA)’s Profiles 2011Salary and Demographics Research Report, the average facility manager is “personallyresponsible for the entire
given survey was paper and pencil format. The end of course survey consisted oftwo parts: Likert scale items and three open-ended questions. The Likert scale items askedstudents “to what extent do you agree that each of the following topics improved your ability toeffectively interact with your partner(s) in the problem-solving studio?” Eleven topics oninterpersonal skills were given including i.e. constructive feedback, selective attention, effectivelistening. Each topic was given with a 6 point Likert scale ranging from 0 – I don’t recall thistopic, 1 – disagree strongly, to 6 – agree strongly. Student mean scores ranged from 0 – 6. Eachtopic was scored for overall mean therefore, if a student answered zero on the Likert scale thezero was
minutes. Most students correctly solvedthe seventh level on the first try, suggesting they had learned the objective. We took a look atsubmissions by students who made many attempts. One such student needed 4 tries to completelevel 1, 2 tries for level 2, 1 try for level 3, 4 tries for level 4, 1 try for level 5, 10 tries for level 6,and 1 try for level 7. The student spent about 5 minutes in total. Two weeks later, the samestudent worked through the activity again, perhaps preparing for an exam, and completed in justover 1 minute and making only 3 incorrect submissions across all levels. Note: The sectioncovering K-map has multiple challenge activities, and this is just 1 of them.6. Challenge activity: Enter output of an SR latch given input s
] Jackson, V. A., Palepu, A., Szalacha, L., Caswell, C., Carr, P. L., & Inui, T. (2003). “Having the right chemistry”: a qualitative study of mentoring in academic medicine. Academic Medicine, 78(3), 328-334.[8] Sorcinelli, M. D., & Yun, J. (2007). From mentor to mentoring networks: Mentoring in the new academy. Change: The Magazine of Higher Learning, 39(6), 58-61[9] van Emmerik, I. J. H. (2004). The more you can get the better: Mentoring constellations and intrinsic career success. Career Development International, 9(6/7), 578.[10] Schrodt, P., Cawyer, C. S., & Sanders, R. (2003). An examination of academic mentoring behaviors and new faculty members’ satisfaction with socialization and tenure and promotion
parameters for industrial engineering education in South Africa. South African Journal of Industrial Engineering, Vol 28, Iss 1, Pp 114-124 (2017). 2017;(1):114. doi:10.7166/28-1-1584.[6] Palma M, Ríos I de los, Guerrero D. Higher Education in Industrial Engineering in Peru: Towards a New Model Based on Skills. Procedia - Social and Behavioral Sciences. 2012;46:1570-1580. doi:10.1016/j.sbspro.2012.05.342.[7] Ferraras, A., Crumpton-Young, L., Rabelo, L., Williams, K., and Furterer, S., (2006) “Work in Progress: Developing a Curriculum that Teaches Engineering Leadership & Management Principles to High Performing Students,” Proceedings of the 2006 Frontiers in Education Conference, San Diego, CA.[8
, 2012.[2] National Academy of Engineering, “Educating the engineer of 2020: Adapting engineering education to the new century.” Washington, DC: The National Academies Press, 2005. Available: https://doi.org/10.17226/11338.[3] M. Besterfield-Sacre, M. Moreno, L. J. Shuman, and C. J., “Gender and ethnicity differences in freshmen engineering student attitudes: A cross-institutional study.” Journal of engineering Education, vol. 90, no. 4, pp. 477-489, 2001.[4] S. Kumar and J. K. Hsiao, “Engineers learn ‘soft skills the hard way’: Planting a seed of leadership in engineering classes.” Leadership and Management in Engineering, vol. 7, no. 1, pp. 18-23, 2007.[5] D. C. Davis, S. W. Beyerlein, and I. T. Davis
received the 2015 Presidential Award for Excellence in Science, Mathematics, and Engineering Mentoring.Miss Dana Corrina Dimitriu Dana Dimitriu is a third-year mechanical engineering student at the University of Texas at San Antonio. She is currently working on receiving her bachelor’s degree in Mechanical Engineering with a minor in Psychology. She has interests in biomechatronics, prosthetics, 3D visualization, and graphic design. c American Society for Engineering Education, 2020 A Simple Method to Help Students Improve 3-D Visualization SkillsAbstractSpatial visualization skills and attention to detail can be effectively improved using variousspecialized methods. Starting in the 1990’s multiple
as an adjunct Professor. Prof. Dasgupta worked for Wentworth University for more than 19 years in the Electrical and Computer Engineering Department. He taught various courses at Wentworth which includes. Motors and Controls, Power Systems, Analog and Digital Control Systems, Analog and Digital Communications, Digital Signal Processing, Electrome- chanical Systems etc. Major achievements during Prof. Dasgupta ’s tenure at Wentworth are as follows: developments of Motors and controls lab, introduction of Power Systems course as an elective, develop- ment of Feedback and Controls lab, development of Digital signal processing lab, development of Analog and Digital Communication lab and introduction of PIC
,” National Science Foundation, National Center for Science and Engineering Statistics,Arlington, VA, 2015.[2] S. Zweben and B. Bizot, “2014 Taulbee Survey,” Computing Research News, vol. 27, no. 5, pp. 2-51,2015.[3] C. Corbett and C. Hill, “Solving the equation: the variables for women’s success in engineering andcomputing,” American Association of University Women, Washington, DC, 2015.[4] N. A. Fouad, and R. Singh, “Stemming the tide: Why women leave engineering,” University ofWisconsin-Milwaukee, Milwaukee, WI, 2011.[5] M. Klawe, T. Whitney, and C.Simard. “Women in Computing, Take 2”, Communications of theACM, vol. 52, no. 2, pp. 68-76. 2009.[6] C. Simard, A. D. Henderson, S. K. Gilmartin, L. Schiebinger, and T. Whitney, “Climbing thetechnical
engagement with students’ course ratings andcourse performance by analyzing learning analytics data (e.g., site access, timestamps, etc.)captured within the learning management system. Additionally, students from both online and in-person sections will be invited to participate in focus group interviews to explore faculty-studentconnections and course enjoyment. Furthermore, a follow-up study will further assess theimpact on student outcomes, student motivation, effort regulation and self-efficacy between thein-person and online sections as part of a retention study.References[1] M. Borrego, J. E. Froyd, T. S. Hall, “Diffusion of Engineering Education Innovations: A Survey of Awareness and Adoption Rates in U.S. Engineering Departments,” Journal
frameworks exist for characterizing individual differences; our choices are basedon the rigor of the underlying theories and the reliability and validity of the related assessmentinstruments. In this paper, we will focus on our use of Kirton’s Adaption-Innovation Theory [27]and the KAI® (Kirton Adaption-Innovation inventory), which measures individual cognitive style[26]. We are also exploring the use of ABAKAS, a validated measure of engineeringinnovativeness based on Ferguson, et al.’s model of that construct [13, 14]; that work will bepresented in future publications. The individual cognitive style data provided by KAI was used inthe current study to supplement the team interaction data provided by IDN to develop a richerpicture of I-Corps™ team