Paper ID #21337Student Career Decision Making Approaches and Development of Profes-sional Engineering TrajectoriesDr. Joyce B. Main, Purdue University, West Lafayette (College of Engineering) Joyce B. Main is Assistant Professor of Engineering Education at Purdue University. She holds a Ph.D. in Learning, Teaching, and Social Policy from Cornell University, and an Ed.M. in Administration, Planning, and Social Policy from the Harvard Graduate School of Education.Nichole Ramirez, Purdue University, West Lafayette (College of Engineering) Nichole Ramirez is a postdoctoral researcher in the School of Engineering Education at Purdue
Paper ID #18435Investigating National-Scale Variation in Doctoral Student Funding Mecha-nisms Across Engineering DisciplinesDr. David B Knight, Virginia Tech David Knight is an Assistant Professor and Director of International Engagement in the Department of Engineering Education and affiliate faculty with the Higher Education Program, Center for Human- Computer Interaction, and Human-Centered Design Program. His research tend to be at the macro-scale, focused on a systems-level perspective of how engineering education can become more effective, efficient, and inclusive.Dr. Maura Borrego, University of Texas, Austin
IL Female Male IN MD MO NV TN WI Figure 1: Number of Applicants for 2018 Cohort broken by various categoriesAs shown in Fig. 1, nearly half of the applicants were from outside the State of Texas. Likewise,over one third of the applicants were from underrepresented population groups mainly Hispanicand African American.3.2 Students selection processA multiple criteria methodology was adopted in making selection decision of the REUparticipants. Those criteria included: a) having a major in a STEM field. b) Cumulative GPA of3.0 or more (out of 4.0) c) at least one semester remaining after the summer program, and d) U.S.citizenship or permanent resident
: a case study in the central adriatic continental shelf,” Environmental Science and Pollution Research, vol. 22, pp. 6034–6049, 2015.[4] B. J. Tewksbury, C. A. Manduca, D. W. Mogk, R. H. Macdonald, and M. Bickford, “Geoscience education for the anthropocene,” Geological Society of America Special Papers, vol. 501, pp. 189–201, 2013.[5] “Fossilsketch website,” https://fossilsketch.org/.[6] H. A. Armstrong and M. D. Brasier, “Foraminifera,” Microfossils, Second Edition, pp. 142–187, 2005.[7] A. J. Smith, D. J. Horne, K. Martens, and I. Sch¨on, “Class ostracoda,” in Thorp and Covich’s freshwater invertebrates. Elsevier, 2015, pp. 757–780.
Paper ID #22137The Diversity of College Engineering Degrees: The Role of Geography andthe Concentration of Engineering Degree ProductionDr. Rajeev Darolia, University of Kentucky Rajeev Darolia is Associate Professor of Public Policy at the University of Kentucky. He holds a PhD from George Washington University.Prof. Cory Koedel, University of Missouri Cory Koedel is an Associate Professor of Economics and Public Policy at the University of Missouri.Dr. Joyce B. Main, Purdue University, West Lafayette (College of Engineering) Joyce B. Main is Assistant Professor of Engineering Education at Purdue University. She holds a Ph.D
definitivefindings from this multi-year panel-type longitudinal experiment will only be available once allmeasurements (M1-M5) for all three cohorts (blocks) are made, validated, and analyzed.6. References[1] R. T. Palmer, D. C. Maramba, and T. E. Dancy II, "A qualitative investigation of factors promoting the retention and persistence of students of color in STEM," Journal of Negro Education, vol. 80, no. 4, pp. 491-504, 2011.[2] G. L. Cohen, J. Garcia, V. Purdie-Vaughns, N. Apfel, and P. Brzustoski, "Recursive processes in self-affirmation: Intervening to close the minority achievement gap," science, vol. 324, no. 5925, pp. 400-403, 2009.[3] S. L. Clark, C. Dyar, N. Maung, and B. London, "Psychosocial pathways to STEM
2019 as described in more detail elsewhere [10]. Students in onesection of the first author’s course at Arizona State University (ASU) (N = 64) were randomlyassigned to groups A and B. Group A was required to use Circuit Tutor for the topic of DCsuperposition, and to do similar problems in WileyPLUS (for the Irwin & Nelms textbook [17])for the topic of DC source transformations as part of one homework assignment. Group B didthe reverse, so that both groups used both systems for part of this homework. Videos ofproblems being worked were available in both Circuit Tutor and in WileyPLUS, but CircuitTutor did not have introductory tutorials available on these topics at the time of this experiment.Students relied on lectures and the textbook
exercises builtaround PC-based control software such as LabVIEW and educational lab hardware such asbalancing an inverted pendulum (Figure 2a,b) or a ball-on-beam. In the mechatronics courses,each school has chosen to emphasize particular aspects of this interdisciplinary field. Most ofthese courses include labs. They tend to use small DC brush motors, introduce basic electronics(OpAmps, transistors, LEDs, etc.), interfacing circuits and programming microprocessors at theboard level to build popular projects such as LEGO robots (Figure 2c), line-following robots ormaze solving robots. Many of these courses are offered jointly with electrical engineeringprograms. (a) (b) (c)Figure 2
year to students who are pursuing bachelor'sdegrees in Applied Chemistry, Applied Computational Physics, Applied Mathematics,Biomedical Informatics, and associate degrees in Computer Science and Chemical Technology.Students continue to receive support if they maintain a qualifying GPA with a full-time creditload. Based on evidence from research studies, successful programs at other universities, andevidence of success from our current and previous NSF S-STEM grants, we are implementing aholistic programmatic approach [10, 11, 16] to support STEM students in the following ways: a)increased student exposure to research experiences [14]; b) student participation in variousprograms as a cohort; c) a mandatory academic advisement and one-on-one
-funded Athena Institute for Artificial Intelligence (AI). Her career in higher education began at Howard University as the first Black female fac- ulty member in the Department of Computer Science. Her professional experience also includes Winthrop University, The Aerospace Corporation, and IBM. She is a graduate of Johnson C. Smith University (B.S., ’00) and North Carolina State University (M.S., ’02; Ph.D., ’05), becoming the first Black woman to earn a Ph.D. in computer science at the university and 2019 Computer Science Hall of Fame Inductee.Prof. Shaundra Bryant Daily, Duke University Shaundra B. Daily is a professor of practice in Electrical and Computer Engineering & Computer Sci- ence at Duke University
. Joseph David Richardson Joseph D. Richardson is an Assistant Professor in the William B. Burnsed, Jr. Department of Mechanical, Aerospace and Biomedical Engineering at the University of South Alabama.Tom ThomasNicole Carr ©American Society for Engineering Education, 2023 Engaging Transfer Students in a College of EngineeringAbstractThe LINK scholarship program at the University of South Alabama is funded by an NSF S-STEM grant, awarding scholarships to low-income students transferring from communitycolleges in the Gulf Coast region to complete degrees in chemical, civil, computer, electrical, ormechanical engineering. The program provides financial support and academic mentoring tofoster student
role," Psychological science, vol. 24, no. 9, p. 1831, 2013.[7] Y. Maeda, & Yoon, S. Y., "A meta-analysis on gender differences in mental rotation ability measured by the Purdue spatial visualization tests: Visualization of rotations (PSVT: R)," Educational Psychology Review, vol. 25, no. 1, pp. 69-94, 2013.[8] C. L. Miller, Bertoline, G. R., "Spatial Visualization Research and Theories: Their Importance in the Development of an Engineering and Technical Design Graphics Curriculum Mode," Engineering Design Graphics Journal, vol. 55, no. 3, pp. 5-14, 1991.[9] L. L. Thurstone, "Primary mental abilities," Science (New York, N.Y.), vol. 108, no. 2813, p. 585, 1948.[10] E. Towle, J. Mann, B. Kinsey, E. J. O
4 1 0 3.25(b) I/O Addressing Format Exam I(c) Addressing Mode2. Understand and ConstructLadder Logic Programs NSF -ATE Labs 2, 3,(a) Instruction Set Relay, Timer, Module 1-10: 70.7 Final Exam 82 82.2 3 4 1 0 3.25 4,6,7Counter, Arithmatic, Exam IIComparison, File Instruction,3. Manipulate data using PLCinstruction sets NSF -ATE(a) Relay, Timer
) instructors encourage/provide authenticity, autonomy,support, interest, and novelty (three sub-themes comprising the meaningful components ofproject contexts theme) in their innovation projects and (b) embrace the unique and unexpectedstudent outcomes that innovation projects can provide.Analyzing Engineering Students’ Understanding of Innovation through Process MapsIn addition to interviews, we developed a process mapping activity to explore students’conceptions of innovation at a more abstract and procedural level. The process mapping task 1provided an open-ended way for students to identify the components and processes they wouldemploy when developing
, b) training videos teaching viewers toconduct classroom observations using a protocol, and c) a series of sample classroom videos andvalidation keys for each of the sample videos. This paper serves as a user manual for the Toolkit,which can be accessed at http://bit.ly/diyclassobtoolkit.Introduction“Improving Student Experiences to Increase Student Engagement” (ISE-2) was funded by theNational Science Foundation, through EEC-Engineering Diversity Activities, at Texas A&MUniversity. The primary grant activity in ISE-2 is a development program for faculty teachingfirst- and second-year Engineering courses. The development program focuses on reducingimplicit bias and deficit thinking related to students and increasing active learning in
for every unit increase collaboration) ● Are provided help by the TA (0.088 unit increase in confidence for every unit increase in TA help)Students place lower value in completing a DC when they: ● Perceive the task as difficult (0.042 unit decrease in confidence for every unit increase in TA help)Regression Analysis for ConfidenceTable 3. Regression model for confidence.Variable UnStandardized Standard Standardized t P F Degrees R2 Coefficient, Error Coefficient, of B β FreedomConfidence
alongside CS students, as well as inadditional courses in a chosen domain. However, we opted to take a different approach anddevelop a minor degree specific to social science students given that (a) prior programmingexperience and mathematical background have been shown to predict success in introductoryprogramming courses, e.g., [11] - [13], and (b) social science students typically have noprogramming and very little math background relative to CS majors. As such, we developed anentirely new series of four courses with content crafted specifically for these students, such thatclasses are taken only with fellow social science students (similar to the computational socialscience minor at UC San Diego). Courses are designed to be taken serially
, we mean a set of nodes thatshare all possible pairwise connections; with the term (induced) star, we imply a set of nodes each with aconnection to a common center and no other edges between other pairs of nodes. To find the largestinduced clique that includes a certain node and the largest induced star that includes that node as a center,we solve the integer programs presented in (1) and (2), respectively. We also present pictorial examplesof cliques and stars in Figure 1 in (a), (b), (c) and (d), (e), (f), respectively.In both mathematical formulations, 𝑥𝑖 is a binary variable that is equal to 1 if and only if node 𝑖 is in theclique/star. Additionally, in the clique formulation, two nodes are not allowed to both be in the clique,unless
: a. What they find desirable or valuable in the job setting (in terms of their long range career path). b. How they transitioned from a first-year student to a co-op/intern student in terms of school performance and motivation. c. Challenges they may have had from a persistence standpoint (e.g. bouncing back from a poor grade on an assignment, quiz or test). d. How their co-op/internship experience is part of their strategy to reach their ultimate goal (whether full-time employment, graduate school, etc.) Additionally, it was important in all the items above that the shadowed employee asks the first-year student about their thoughts and opinions as
is at the lowfrequencies). Convert the 2-D DCT to its log magnitude so that this concept can berealized using the log magnitude of the DCT. You should get a plot similar to Figure 1(b) Page 25.1081.6in [6]. The equation that converts a DCT C(u,v) to its log magnitude L(u,v) is given by[6] log(1 + 0.01| C (u , v) |)L(u , v) = 255 (1) log(1 + 0.01[max | C (u , v) |]) u ,vProject Assignment Part 4: Feature ExtractionWrite a MATLAB program that computes the 2-D DCT of an image and scans it in a‘zigzag’ fashion (see
-0552737 (for 2006-2009). She also acknowledges the additional support ofOakland University’s Office of the Provost and Vice President for Academic Affairs, as well asthe office of the Vice Provost for Research and by the School of Engineering and ComputerScience at Oakland University. Special thanks go to former REU student Caymen Novak for herassistance with the outreach activity.References: 1. http://me-reu.secs.oakland.edu 2. L. Guessous, Q. Zou, B. Sangeorzan, J.D. Schall, G. Barber, L. Yang, M. Latcha, A. Alkidas and X. Wang, "Engaging Underrepresented Undergraduates in Engineering through a Hands-on Automotive-themed REU Program," Paper # IMECE2013-62111, ASME 2013 International Mechanical Engineering Congress and
. b. Community members and I value the same things. 3.12 3.33 3.35 c. This community has been successful in getting the needs of its 3.29 3.50 3.30 members met. d. Being a member of this community makes me feel good. 3.47 3.61 3.50 e. When I have a problem, I can talk about it with members of this 3.59 3.39 3.75 community. f. People in this community have similar needs, priorities, and 3.47 3.39 3.55 goals. g. I can trust people in this community
same lines, it can be seen from Table 1 that afew students have not taken advantage of Professor and/or Teaching Assistant Office Hours. Ifstudents are understanding the course material, they will have less need to ask additional questionsin office hours thereby reducing the number of students visiting office hours.Table 1: Key to On-Going Program Activities, and the Number of Respondents who Did NotParticipate in Each Activity Identifier Program Activity Number of Non-Participants A Faculty Mentoring 0 B Tutoring Center 7 C S-STEM Program
Professor of Electrical and Computer Engineering at Temple University specializing in electrical machines and power systems, multimedia tutoring, and control and optimization of dynamic systems. He has been the principle investigator of a project for the development of an intelligent tutoring shell that allows instructors create their own web-based tutoring system. His current research focuses on security of cyber-physical systems based on multiagent framework with applications to the power grid, and the integration of an intelligent virtual laboratory environment in curriculum. He is an associate editor of Dynamics of Continuous, Discrete and Impulsive Systems: Series B, and is a member of IEEE, ASEE, and Sigma Xi
, H. M. Matusovich, C. J. Atman, R. Streveler, and R. Miller, “Work in progress: Engineering Pathways Study: The college-career transition,” Proc. Ann. Frontiers Educ. Conf., Rapid City, SD, 2011.[10] S. K. Gilmartin, A. L. Antonio, S. R. Brunhaver, H. L. Chen, and S. D. Sheppard, “Career plans of undergraduate engineering students: Characteristics and contexts,” Alfred P. Sloan Foundation Conf. on U.S. Engineering in the Global Economy, National Bureau of Economic Research, Cambridge, MA, 2011.[11] S. D. Sheppard, A. L. Antonio, S. R. Brunhaver, and S. K. Gilmartin, “The early career pathways of engineering students,” in Cambridge Handbook of Engineering Education Research, A. Johri and B. Olds, Eds. New York, NY
bag lecture by Institute for Broadening Participation (IBP)]Altogether, the intended major program activities were accomplished on schedule, in addition tothe students gaining professional development skills via the supplementary USRG program. Toenhance the knowledge and skill-level of these students in metrology/NDI, the five (5) majorintellectual themes, and the specific research projects under these included the following: 1. Theme: Comprehensive Forensic Metrology/NDI of Surface & Sub-surface Deterioration a. Project: Bio-Inspired Compositional Gradients via LENS Processing for Tailorable Mechanical Responses [12, 13] b. Project: Texturing of SLM Additive Manufactured Surfaces for Bio-Inspired
using in our design? 9. What is the print of this code? a=5 b=4 if a < b print ("a is less than b" else print ("a is greater than b") 10. Where would a cube of ice melt faster: on a plastic or metal plate?The post survey included some of the above questions along with engineering self-efficacy rating questionsbelow. Participants rated each question by picking the following responses: strongly agree, agree, neutral,disagree, or strongly disagree. Given the post survey was administered through an email and after the end ofthe Academy, only N=29 responses were received. 1. I am confident with what Engineering is (72.4% Agree, 24.1% Neutral) 2. The remote
determine the level ofknowledge and interest regarding CNTs and their nanocomposites. In the fall 2014 semester, atotal of 39 students participated in this exercise. After reading the excerpts from the journalarticle, preliminary results indicate that (a) 60% of the students reported an increase in their knowledge level regarding nanoparticles and their composites. (b) 22% of the students reported an increase in interest regarding nanotechnology.Outreach ActivitiesFrom support of the NUE grant, new nanotechnology-related activities are being developed andintegrated into the previously formed NanoClub outreach program as part of an NSF BRIGEGrant (NSF-CMMI 1032637). In 2011 the NanoClub was developed as a weekly afterschooloutreach
the correlation between each factor. Avisual display of the number of times a student played (surrogate for engagement), student’s finalscore in the class (surrogate for their learning capacity), and game level (surrogate forinformation intensity) is shown in Figure 6. It can be observed in the figure that the engagementof students with a final score of less than 80 (C students) had a different pattern from studentswho have a final score that surpassed 80 (A and B students). This is one preliminary finding ofthis research and could be interpreted as that less prepared students (e.g., C students) foundequivalent stimulation in all levels of the game, whereas better prepared students could only bestimulated by levels of the game that provided
and solution taken by the group (the video that you are watching). a. Comment on the steps and modifications that you think align with your team’s process–were these steps justified in a similar way? b. Comment on the steps and modifications that you do not think align with your team’s process – do you agree with their justifications?2. Suggest changes for the solution that students are watching.Phase III: Revisiting Solution and Sheet Metal Forming Design ProcessStudents were instructed to turn in an individual report with the following:1. Student’s proposed final design - with sketches (students can use the provided drawing and mark the changes on it or provide hand sketches.)2. The step