Capstone Project (Optional) Certifications Figure 1. Cyber Security Degree ArchitectureMajor Areas of Study Beyond General EducationThe new holistic multi-disciplinary B.S. Degree is built on a solid foundation of the following fourareas: 1. Mathematics Skills—Precalculus and Statistics a. MATH 2412: Precalculus b. MATH 2334: App Stats Health c. Discrete Math and CS related topics recommended by the ABET are covered in a new course called Foundation of Systems (CSCI-2322) 2. Technical Skills—Computer Science a. 50 Adv. Hrs. 3. Investigation Procedures and Policies
75 11.95 5.549 .641 .05). Although significant differences did not exist acrosssection type, there were fewer failing grades (C, D, and F), and a larger percentage of B grades inthe SLA-aBLe sections than the non-SLA-aBLe sections as shown in Figure 3. The data from thepublic institution shows same trends [12]. Final Grade Comparison 40% 36% 35% 35% 29% 30% 27% 25% 25% 25% 20% 15% 10
collaboration boundaries to understand how they can supportengineering students’ development of leadership competencies. This is work-in-progress, andpart of a larger project that aims at exploring students’ development of global competencies. Thecurrent paper advances our understanding of boundary crossing that occur within an engineeringdesign team, and it asks: a) what boundaries were encountered in globally situated engineeringdesign projects in a Canadian University and, b) how can these boundaries enable students tomake productive progress in their global leadership skills?Theoretical PerspectivesThe study was guided by three theoretical perspectives namely: 1) Vygotsky’s socialconstructivist perspective allowed for the study of students
Paper ID #34587The Disconnect Between Engineering Students’ Desire to Discuss RacialInjustice in the Classroom and Faculty AnxietiesDr. Tracy Anne Hammond, Texas A&M University Dr. Hammond is Director of the Texas A&M University Institute for Engineering Education & Innovation and also the chair of the Engineering Education Faculty. She is also Director of the Sketch Recognition Lab and Professor in the Department of Computer Science & Engineering. She is a member of the Center for Population and Aging, the Center for Remote Health Technologies & Systems as well as the Institute for Data Science
students to computational tools used in solving Page 11.1046.3civil engineering problems, (3) evaluate critical thinking and communication skills. The projectsare designed to solved by student teams, who are told they are acting as consultants on theproject posed. These projects are open ended problems with multiple possible solutions and aredesigned to emphasize interpretation of numerical results rather than pure numericalcomputations.Both the scope and nature of the projects can be seen in the sample projects that are given in theappendices (Appendix B is a project from the structural analysis course, and Appendix C is aproject from the
as shown in Table 1. The Table considers three mid term tests of worth45%, five home works of worth 10%, one project of worth 5%, five pop quizzes of worth10% and a final test of worth 30%. Each of these items can individually be graded on ascale of 100. However, the total score for the semester can be translated into a final scaleof 100. Letter grades can be assigned based on standard procedure of ‘A’ for 90 or more,‘B’ for 80 or more but less than 90, etc. Letter grades can be assigned by scaling thestandard to any level as well. Table 1. Example grade distribution Grading Category Weight, % 3 Mid Terms 45 5 Home
digital logic. Two questions were asked: Question 1: "Considering my level of preparation, the non-digital experiments 1-4 were (a) Too difficult, (b) About right, (c) Too easy. Question 2: " Considering my level of preparation, the digital experiments (5-8) were (a) Too difficult, (b) About right, (c) Too easy."The results, shown in Table 2, clearly indicate that most of the students found the required workto be at a reasonable level of difficulty regardless of the type of experiment.Table 2. Lab I Student assessment of the difficulty of the required laboratory work. Non-Digital Experiments Digital ExperimentsToo difficult 18
Texas A&M A Univerrsity. A smaall group of ffaculty wasassigned to assess thee curriculumm to see if thee courses offffered were aall relevant aand to assess thecurrent prerequisite p structure. s Giv ven this duaal mandate, a request wass made of alll teachingfaculty to o prepare a brief b PowerP Point slide lissting the dessired incominng skills, exxpected outgooingskills and d any laborattory or projeect componeent of their coourse. An eexample slidde for one off thecourses is shown in Figure F 1. Thee expecting outgoing skiills for the ccourses in thee program w werethen takeen and combined into a master
, 2023].[3] J. Fuller & W. Kerr, “The great resignation didn’t start with the pandemic,” Harvard Business Review, March 23, 2022. [Online]. Available: https://hbr.org/2022/03/the-great- resignation-didnt-start-with-the-pandemic. [Accessed February 7, 2023].[4] W. Lu & B. Zoghi, “Designing a professional master’s program to build life-long successful skills for engineering managers,” In 13th Annual International Conference of Education, Research and Innovation, November 9-10, 2020. [Online]. Available: https://library.iated.org/view/LU2020DES. [Accessed February 7, 2023].[5] “A guide to the Engineering Management Body of Knowledge, 5th edition,” ASEM.org. [Online]. Available: https://www.asem.org/EMBoK. [Accessed
next section.Results and DiscussionThis section summarizes the experimental results obtained from this study. A comparison wasalso accomplished to verify the effectiveness of the methodologies using the base line data. © American Society for Engineering Education, 2024 2024 ASEE Southeastern Section ConferenceCS405 – “Linux with Application Programming” is a core course in the computer sciencecurriculum at Alabama A&M University. Table 1 includes the student assessment results inCS405 regarding the learning outcomes and the ABC rates (only grades A,B, and C areconsidered as “Pass” according to the computer science curriculum in the universityundergraduate bulletin). The base line
: (20 minutes) a. Live Script 1 - Introduction to MATLAB Drive (Figure 1) Figure 1: Live Script 1 b. Live Script 2 - Plotting Data – MATLAB (self-paced Live Script) (Figure 2) Figure 2: Live Script 2 c. Participants are encouraged to bring and use their laptop to access MATLAB online for the Live Scripts.5. Lecture 5: LLSFT (20 minutes) a. Return to Excel to input the equations for the slope, y-intercept, and correlation coefficient. b. Live Script 3 - Linear Least Squares Fitting Technique in MATLAB (Figure 3) Figure 3: Live Script 3MathWorks® - MATLABParticipants will actively engage in the
. Lessons Learned and ConclusionsThere were quite a few lessons learned by the instructors from this PBL experiment:1) The hardest part about the experiment was, in the first place, picking a good PBL problem thatwas relevant to the class material at hand. Some of the criteria that the author used in selecting aproblem were: a) the design has to emphasize, or at least force the use of, concepts and equationslearned in the classroom, b) the possible solution designs should be relatively simple to make orbuild, not costly in dollar amount, and not very time consuming.2) The second thing learned was that the implementation of PBL takes a significant portion ofthe instructor’s time.3) The instructor needs to alert students to verify assumptions made in
Midwest Sectional Conference 2STANDARDS FOR TENURETenure means different things to different institutions and faculty depending on their mission andhistory. If we model tenure in three institutional dimensions--type, location, and age wewitness a wide range of perspectives. Fundamentally, tenure can be viewed as a license to teachat a particular i i i . Wi h e e, he i c ime a he i i i i limi ed.Tenure is rooted in the belief in academic freedom. The instructor worthy of tenure will beprotected from prejudice h gh a g a a ee f j b ec i . The fe academic a dprofessional standing including professional integrity
RubricThe original version of the oral presentation rubric for our laboratory course is shown inAppendix A. This is an example of a scoring guide rubric. There is narrative of expectations ofan excellent presentation, but there is no clear rationale for what separates “excellent” from“very good,” for example. This presents a clear drawback when it comes to inter-rater reliability,as each evaluator has their own opinion for the different standards.The original video presentation rubric is shown in Appendix B. Arguably this is not an effectiverubric. It could generously be categorized as a scoring guide rubric as well.One proposal was to move toward more of a check-box style rubric, as described in Stevens andLevi [2]. However, the team quickly found
during the experimental work. The CISC specificationswere as follows:CISC System OneCPU: Intel Pentium-II (Stock 350Mhz, 3.5x 100Mhz FSB)Front Side Bus Speed for Test Series A: 100Mhz (CPU @ 350 - Stock)Front Side Bus Speed for Test Series B: 133Mhz (CPU @ 466 -Over clocked)RAM: 256mbHard Disk Drive: Western Digital WDC WD205BA (20gb ATA33)IDE Chipset: Intel PIIX-4 BXSCSI Chipset: NoneVideo Card: nVidia RivaTNT-1 v3400, 16mb Video Ram, Memory Clock: 120Mhz,3d Engine Clock: 105MhzSound Card: Creative Labs PCI64CISC System TwoCPU: Intel 80486DX (Stock 40Mhz)Bus Speed for Test Series A: (CPU @ 40Mhz - Stock)Bus Speed for Test Series B: (CPU @ 50Mhz - Over clocked)RAM: 24mbHard Disk Drive: SCSI Seagate Hawk ST32151N (2.1gb SCSI-2 Fast @10mbit/sec
. a) Each robot starts at an arbitrary unknown location and incrementally builds a local map of the environmentThe object avoidance capability on the mobile robots is basedon the algorithm using heading range information provided while using its abilities to localize itself. It then sends the information of the local maps to the host.by front mounted measuring sonar device. A transmission ofdata between mobile robots to a host computer, we used b) The host matches the pose of the robot and the boundary of the robots. It can
Paper ID #49662Python-based Microcontroller Architecture and Microcontroller ApplicationEducation in Engineering TechnologyDr. Byul Hur, Texas A&M University Dr. B. Hur received his B.S. degree in Electronics Engineering from Yonsei University, in Seoul, Korea, in 2000, and his M.S. and Ph.D. degrees in Electrical and Computer Engineering from the University of Florida, Gainesville, FL, USA, in 2007 and 2011, respectively. In 2016, he joined the faculty of Texas A&M University, College Station, TX. USA, where he is currently an Associate Professor. His research interests include Mixed-signal/RF circuit design and
mold was washed and cured as done previously inRef. [16]. The mold was washed in 99% IPA for a total of 50 minutes. During washing, the moldwas shaken on a digital shaker at 160 rpm. Additionally, it was removed from the IPA and blownoff with compressed air every 10 minutes. This helped to remove the excess resin. Once washed,the mold was placed into the UV oven to finalize the resin solidification. It was exposed to UVlight for four cycles, totaling 40 minutes. Finally, the mold was placed into a conventional ovenovernight at 130°C. This finalized any chemical reactions occurring within the resin, allowing forPDMS to cure on the interface of the mold and PDMS.Figure 7: (A) 3D-printed plastic master mold for the channel modules. (B) Fabricated
design competition revealed increasedsatisfaction amongst students, faculty, and industry partners. Following this, the TRUE modelwas adopted as part of the capstone design.In the summer of 2020, only two types of capstone projects were encouraged: (a) TRUEprojects and (b) Student-initiated projects that were reviewed and approved by a facultycommittee through a proposal system. By Spring 2023 (as of the writing of this work-in-progress paper), all capstone design projects in the department of EE have been converted tofit the TRUE project model, which means all capstone projects are real-world projects withindustry/community sponsors/partnerships. While this significant shift has been driven byanecdotal experiences shared by various stakeholders
AC 2011-1138: KRISYS: A LOW-COST, HIGH-IMPACT RECRUITINGANDJoseph A. Morgan, Texas A&M UniversityJay R Porter, Texas A&M University Jay R. Porter joined the Department of Engineering Technology and Industrial Distribution at Texas A&M University in 1998 and is currently Professor and Program Director for the Electronics and Telecommu- nications Programs. He received the BS degree in electrical engineering (1987), the MS degree in physics (1989), and the Ph.D. in electrical engineering (1993) from Texas A&M University. His areas of inter- est in research and education include product development, analog/RF electronics, instrumentation, and entrepreneurship.Dr. Wei Zhan, Texas A&M University Dr
AC 2012-3596: PROFESSIONALISM SKILLS: A FRAMEWORK FOR THEACADEMIC ENVIRONMENTKaren J. Horton P.E., University of Maine Karen J. Horton, P.E., is an Associate Professor of mechanical engineering technology at the University of Maine, and a licensed Professional Engineer in the state of Maine. She is a Co-principal Investigator on a National Science Foundation ADVANCE Institutional Transformation Grant to increase recruitment, retention, and advancement of tenure-track women faculty members in STEM fields. Prior to her 1997 appointment to the university, she was employed as a Mechanical Engineer at Bath Iron Works in Maine, as a high school mathematics and electronics teacher for the Department of Defense Dependent
examination of indicators of engineering students' success and persistence. Journal of Engineering Education, 2005. 94(4): p. 419-425.13. McLoughlin, L.A., Spotlighting: Emergent gender bias in undergraduate engineering education. Journal of Engineering Education, 2005. 94(4): p. 373-381.14. Potts, G., B. Schultz, and J. Foust, The effect of freshmen cohort groups on academic performance and retention. Journal of College Student Retention: Research Theory, & Practice, 2004. 5(4): p. 385-395.15. Kimball, J., A study of engineering student attributes and time to completion of first-year required courses at Texas A&M University, in Educational Administration and Human Resource Development. 2006, Texas A&M
, J. E. Froyd, M. Hoit, J. Morgan, D.L. Wells, "First-Year Integrated Curricula Across the Engineering Education Coalitions," Journal of EngineeringEducation, v 88, no. 4, October 1999.6. Morgan, J., and Bolton, B. "An Intergrated Freshman Engineering Curricula," Frontiers in Education '98,Tempe Mission Palms Hotel, Tempe, Arizona, November 4-7, 1998.7. Kenimer, A. and J. Morgan, “Building Community Through Clustered Courses,” ASEE, Montreal, Canada,June 2002.8. Malave, C., J. Rinehart, J. Morgan, R. Caso Esposito, and J. T. P. Yao, "Inclusive Learning Communities atTexas A&M University - A Unique Model for Engineering," Creating and Sustaining Learning Communities:Connections, Collaboration, and Crossing Borders, Tampa, FL, March 10-13
Page 4.308.10survey taken in the Fall 1998 semester and the course assignment database results for the 1997-1998 academic year illustrates the potential use of these two outcome indicators in conjunctionwith each other. Figures 3 and 4 illustrate the survey and database results respectively regardingthe quantity and quality of opportunities to engage in activities related to the intendedEducational Outcomes (1-16) in graphs (A) and (B) for all Electrical Engineering courses. Graph(C) in each of the figures illustrates a measure of performance regarding the achievement of the16 intended Educational Outcomes of the program. For all Electrical Engineering courses,student performance perceptions, regarding their achievement in attaining the
contrast, the UHF condition (Figure 3B) demonstrates a nearly linear temperatureincrease past the initial 5-10 meters for most of the fluid, as the gap between the lines stays nearlyconsistent. In both graphs, the constant temperature lines will always align parallel at the center ofthe pipe; this is in order to account for the necessary symmetry condition in which the radialtemperature gradient must disappear. © American Society for Engineering Education, 2024 2024 ASEE Midwest Section Conference Figure 3. (A) Uniform wall temperature contour (50°C), (B) Uniform heat flux plot (1 kW/m2).The axial temperature gradients can be more clearly visualized when averaging the
purpose of our next interview to elicit responses to questions that we have and navigate through the interview. For this next interview 1. Please find 4 pictures (although you may use as many as 6): a. One that represents something about you as a person b. One that represents something about you as a professional c. One that represents your (primary) discipline d. One that represents your cross-disciplinary work 2. Make sure the pictures are in JPEG format. 3. Email your pictures to – [project email] no later than [date]. In the subject line include your name (Last name, First name) and date (mm/dd/yy). (Note: the photos will be on a password protected system) Figure 1. Instructions provided to
. Shortfall, the self-contained computer simulation game developed byNortheastern University, serves as one of these modules. The specific outcomes that weoriginally aimed to achieve with this computer simulation game are that students can describe, atan introductory level, the following: a) environmental and economic sustainability issues, b) how individual firm decisions collectively affect supply-chain decisions (referred to as market interaction), Page 15.208.5 c) how computational methods can be used to assist policy decisions, and d) the effect of complexity on decision-making.The courses in which we have
Paper ID #39941Student-centered design: A capstone design project of a batch vacuumevaporator for food science students by a multidisciplinary team ofengineering seniorsDr. Philip Jackson, University of Florida Dr. Philip B. Jackson earned B.S. degrees in Aerospace Engineering and Mechanical Engineering as well as an M.S. and Ph.D. in Mechanical Engineering, all from the University of Florida. He is currently faculty in the Department of Engineering Education at the University of Florida where he leads the Game-Based Learning and Digital Experiences Laboratory (GLaDE)Emily Hope FordAllison Kathleen PorrasAndrew John MacIntosh
. Amazon [cited 2016 September 25]; Available from: https://www.amazon.com/b?node=8037720011.4. Zuckerberg, M. The technology behind Aquila. Facebook 2016 [cited 2016 September 24]; Available from: https://www.facebook.com/notes/mark-zuckerberg/the-technology- behind-aquila/10153916136506634/.5. Soergel, A., New Application for Drones: Disaster Relief, in U.S. News. 2016.6. Greene, S., Mesa County, Colo. A National Leader In Domestic Drone Use, in The Huffington Post. 2013: Colorado.7. Workforce Data. Oklahoma Department of Commerce 2016 [cited 2016 September 24]; Available from: http://okcommerce.gov/data/workforce-data/.8. Reese, J., W. Hundl, and T. Coon, Oklahoma Agriculture Statistics 2015
learning. Proc. - Front. Educ. Conf. FIE 1, T3A20-T3A25 (2003).3. Carberry, A., Siniawski, M., Atwood, S. & Diefes-Dux, H. Best Practices for Using Standards-based Grading in Engineering Courses Best Practices for Using Standards-based Grading in Engineering. ASEE Conf. Proc. (2016).4. Ankeny, C. & D. O’Neill. Work in Progress: Aligning and Assessing Learning Objectives for a Biomedical Engineering Course Sequence Using Standards-based Grading within a Learning Management System. ASEE Conf. Proc. (2019).5. Beck, C. & Lawrence, B. Inquiry-based ecology laboratory courses improve student confidence and scientific reasoning skills. 3, (2012).6. Carberry, A., Krause, S., Ankeny, C. & Waters, C