startup technology venture focusing on Augmented and Virtual Reality for creating immersive learning content. Hurriyet was a software engineer at Alcatel-Rovsing in Copenhagen, Denmark, developing software for American Airlines Data Network. Dr. Ok holds a D.Sc. Degree in Computer Science from the GWU, and M.S. and B.S. Degrees in Computer Science from Hacettepe University, Ankara, Turkey.Dr. Natalie B. Milman, The George Washington University Natalie B. Milman, Ph.D. is Chair of the Department of Educational Leadership and Professor of Edu- cational Technology at The George Washington University’s Graduate School of Education and Human Development. She is also a member of the interdisciplinary Human-Technology
course. Research into creating 20,21 and evaluating 22 concept maps canprovide guidance on creating one for other courses. Exam Question: A program in the (non-existent) programming language Eek, whose syntax looks a lot like C. This is a good program and it runs correctly. int a(int z, int y) { void main() { print(’a’) int w, x, y, z, t, u, v return y - z + 2 w = b(3) } x = a(w, 3) int b(int x) { y = b(x) print(’b
, vol. 65, no. 4, pp. 544-552, 2022, doi: 10.1109/TE.2022.3147099.[2] A. Godwin and A. Kirn, "Identity-based motivation: Connections between first-year students' engineering role identities and future-time perspectives," Journal of Engineering Education, vol. 109, no. 3, pp. 362-383, 2020, doi: https://doi.org/10.1002/jee.20324.[3] W. J. S. B. E. Hughes, E. Annand, R. Beigel, M. B. Kwapisz, and B. Tallman, "Do I think I’m an engineer? Understanding the impact of engineering identity on retention," presented at the 2019 ASEE Annual Conference & Exposition, Tampa, Florida, June 15, 2019, 2019.[4] M. S. Somia Alfatih, M. S. Leong, and L. M. Hee, "Definition of Engineering Asset
relates to field-effect transistors (FETs). The right response is “C” whichemphasizes how a transistor’s threshold voltage is affected by several variables, includingtemperature, manufacturing process, and the transistor’s physical dimensions (length and width). Figure 1: Three items related to semiconductor materialsOne kind of digital logic gate, the NAND gate, is the subject of Question 10. There are two inputs(A and B) and one output (Q) on a NAND gate. A NAND gate behaves as follows: it onlyproduces a 0 (LOW) output when both of its inputs are 1 (HIGH). Because the output of a NANDgate is only 0 when both inputs are 1, “A” is correct.3 ManufacturingTwo questions on the survey, as seen in Figure 3, focus on the
logging between 11-15 days: 19% Figure 2. Learning activities from Student A (above) and Student B (below) show the differences in the amount of time spent studying over 10 days and also the different levels of cognitive engagement based on Bloom’s taxonomy.Figure 3. Distribution of different Bloom’s taxonomy levels across different courses. MAE 8, CENG 15,CSE 8 and SE 9 are introduction courses to programming across four different engineering departments.ECE 5 is an introduction to electrical and computer engineering with hands-on projects and labs. Nano 11 isa lecture based introduction course to Nano Engineering.Preliminary Feedback from StudentsThe preliminary student feedback has centered around the productivity and effectiveness of the
://www.analog.com/en/education/education- library/software-defined-radio-for-engineers.html [4] J. -K. Hwang, "Innovative communication design lab based on PC sound card and Matlab: a software-defined-radio OFDM modem example," In Proceedings of the 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, pp. III-761.[5] K. VonEhr, W. Neuson, and B. E. Dunne, “Software defined radio: choosing the right system for your communications course,” In Proceedings of the 2016 ASEE Annual Conference & Exposition, New Orleans, Louisiana.[6] C. J. Prust, "An introductory communication systems course with MATLAB/Simulink- based software-defined radio laboratory," In Proceedings of the 2019 ASEE Annual
Footprint of Technology and Commerce 3 2. Design Informed by Rare and Dangerous Materials used in Technology a. In Terms of the Environment i. Planned Obsolescence and Inaccessible Design ii. Recycling: Pros and Cons iii. Technology and Runaway Consumerism iv. The Environmental Advantages of Technology b. In Terms of Colonialism, Extractivism, Mining, and Human Rights c. In Terms of the Geopolitics of Materials iii. (Dis)ability, Access, and Human-Centered & Universal Design iv. Iterative Design v. UX Design vi. Interdisciplinary Design
Paper ID #42951Investigating the Impact of Team Composition, Self-Efficacy, and Test Anxietyon Student Performance and Perception of Collaborative Learning: A HierarchicalLinear Modeling ApproachTridib Kumar Saha, Purdue University Tridib K. Saha is a final-year PhD candidate in Electrical and Computer Engineering at Purdue University, specializing in hybrid electric vehicle modeling and simulation, power and energy, and engineering education. He serves as a lecturer in the ECE department, teaching fundamental circuits courses for approximately four years. His academic focus has evolved toward ECE educational research, course
)References 1. Connor K, Kelly J, Scott C, Chouikha M, Newman D, Gullie K, Ndoye M, Dabipi I, Graves C, Zhang L, Osareh A, Albin S, Geddis D, Andrei P, Lacy F, Majlesein H, Eldek A, Attia J, Astatke Y, Yang S, Jiang L, Oni B, Zein-Sabatto S “Experiment Centric Pedagogy – Improving the HBCU Engineering Student Learning Experience,” ASEE Annual Conference, Salt Lake City, June 2018, USA. 2. Connor K, Scott C, Korte R, Sullivan B, Velez-Reyes M “Mini-Workshop Series for Minority Serving Institutions with ECE Programs,” ASEE Virtual Conference 2021 3. Connor K, Scott C, Chouikha M, Leigh-Mack P, Sullivan B, Kelly J, Goodnick S, Smith M, Klein M, Abraham S, Oni B, Ososanya E, Eldek A, Yang S, Erives H, Joslyn C
Paper ID #41346Comparison of Engineering and Computer Science Student Performance andOpinions of Instruction of a Microcomputers Course Across Delivery FormatsDr. Todd Jeffrey Freeborn, The University of Alabama Todd Freeborn, PhD, is an associate professor with the Department of Electrical and Computer Engineering at The University of Alabama. Through NSF funding, he has coordinated REU Sites for engineering students to explore renewable resources and speech pathology. He is also the coordinator for an NSF S-STEM program to prepare students for gateway courses across different disciplines of engineering to support and
the assistance of ChatGPT. We include this information when we share therubric as an incentive for potential collaborators to improve it.) Asset Driven Equitable Partnerships – ADEP in Practice (WIP)References [1] Connor, K. A., & Goodnick, S. M., & Klein, M., & Sullivan, B. J., & Kelly, J. C., & Leigh-Mack, P., & Abraham, S., & Janowiak, J., & Alvarado, S., & Andrei, P., & Scales, W. A., & Wilson, T., & Lagunas, Y. (2023, June), Board 78: ADEP: Asset-Driven Equitable Partnerships (WIP) Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland. 10.18260/1- 2—42939 [2] National Academies of Sciences, Engineering
Paper ID #39917Board 84: The 2TO4 Project - Facilitated Transition from 2-Year to4-Year Engineering Studies (WIP)Dr. Kenneth A Connor, Rensselaer Polytechnic Institute Kenneth Connor is an emeritus professor in the Department of Electrical, Computer, and Systems Engi- neering (ECSE) at Rensselaer Polytechnic Institute (RPI) where he taught courses on electromagnetics, electronics and instrumentation, plasma physics, electric power, and general engineering. His research in- volves plasma physics, electromagnetics, photonics, biomedical sensors, engineering education, diversity in the engineering workforce, and technology
opportunities that impact the successful transition of studentsfrom 2-year to 4-year institutions. Data collection for this study is now in its initial phase, withIRB approval having recently been secured. Details on all aspects of this project are described inthe following sections. Additional background on this project can be found at Connor, K. A., &Berhane, B. T., & Chouikha, M. F., & Velez-Reyes, M., & Sullivan, B. J., & Klein, M., &Lagunas, Y., & Muskett, M., & Nastiuk, A., & Alvarado, S., & Hibbler, E. (2023, June), Board84: The 2TO4 Project - Facilitated Transition from 2-Year to 4-Year Engineering Studies(WIP) Paper presented at 2023 ASEE Annual Conference & Exposition, Baltimore , Maryland.10.18260
their families is correlated with increases inacademic success, as measured by retention, progression (GPA and courses completed), and 4- to6-year graduation rates, for both computer engineering and computer science students. We havedemonstrated these effects in a dually designated Hispanic-Serving Institution (HSI) and AsianAmerican and Native American Pacific Islander-Serving Institution (AANAPISI) and have doneso as a pilot study for other, including similar, institutions as well as other STEM fields.AcknowledgmentsThis work was funded in part by NSF Grant #1742607.References[1] Fernández, E., Rincón, B. E., & Hinojosa, J. K. (2021). (Re)creating family and reinforcing pedagogies of the home: How familial capital manifests for
of Idaho Professor John Crepeau received his BS degree in mechanical engineering from the University of California, Berkeley, and his MS and PhD degrees from the University of Utah. After serving as an NSF-NATO Postdoctoral Research Fellow at Humboldt University in Berlin, Germany, he began teaching at the University of Idaho. He was a Fulbright Scholar at the Escuela Superior Politecnica del Litoral in Guayaquil, Ecuador. He has served as Department Chair, Associate Dean and Interim Dean at the University of Idaho. ©American Society for Engineering Education, 2024Enhancing Pathways from Community Colleges to Four-Year Schools with an Online Lecture/Laboratory Course in
developed acomplete open-source toolchain from Verilog synthesis through bitstream flashing. The combinedresult has been a proliferation of open-source development boards and and substantial usercommunity around the iCE40.In the introductory digital lab setting, these low-cost FPGAs achieve the trifecta of tangibility,accessibility, and professional practice. In our offering of ES 4, we have used a sequence ofUPduino boards, starting with the UPduino 2.0 from Gnarly Grey (now discontinued) andcontinuing with the UPduino 2.1, 3.0, and 3.1 from TinyVision.ai.(a) UPduino 3.1 (b) WebFPGA ShastaPlus($30, TinyVision.ai) ($38, WebFPGA.io) (c) TinyFPGA BX
/25979.[2] A. Huynh and N. T. Buswell, “How was your internship: Stories about the engineering internship experience from five female engineering students,” in 2019 Pacific Southwest Section Meeting. California State University, Los Angeles , California: ASEE Conferences, April 2019, https://peer.asee.org/31829.[3] D. Weagle, D. B. Ortendahl, and M. A. P.E., “Universities and industries: A proactive partnership shaping the future of work,” in 2019 ASEE Annual Conference & Exposition, no. 10.18260/1-2–33486. Tampa, Florida: ASEE Conferences, June 2019, https://peer.asee.org/33486.[4] J. P. Martin, S. D. Garrett, S. G. Adams, and J. Hamilton, “A qualitative look at african american students: Perceptions of developing engineer of
. Cognition and Instruction, 30(4):404–434, 2012. [7] Mary Hegarty, Mike Stieff, and Bonnie L. Dixon. Cognitive change in mental models with experience in the domain of organic chemistry. Journal of Cognitive Psychology, 25(2):220–228, 2013. [8] M. Stieff, B. L. Dixon, M. Ryu, B. C. Kumi, and M. Hegarty. Strategy training eliminates sex differences in spatial problem solving in a stem domain. Journal of Educational Psychology, 106(2):390–402, 2014. [9] Jonathan H Tomkin, Matthew West, and Geoffrey L Herman. An improved grade point average, with applications to cs undergraduate education analytics. ACM Transactions on Computing Education (TOCE), 18(4):1–16, 2018.[10] Suleman Mahmood and Geoffrey L Herman. A modular assessment for cache
than80 percent correctness for post-lab surveys. The results of the self-identified assessment wereverified by analyzing results from multiple-choice questions.The first question was Figure 15 A, which evaluated students' knowledge of identifying drawnlogic gates. Surprisingly, 67 percent (Table 3) of students could identify the correct logic gate thefirst time without using the BEADLE curriculum. This stemmed from the fact that students hadbriefly covered this material in the lecture before completing the assignment. Nearly the entiretest population selected the answer correctly the second time, as 99 percent chose the correctsolution.The question from Figure 15 B tests students' knowledge of Boolean operator symbols, which issimilar to the
students were given kits containing 1 microfarad, a 2.2 kW resistor, and an ADALM1000 device. The connection layout shown in Figures 4a and 4b was used as a setup guide withthe software. The steps followed by the students to set up these circuits includes: Set the minimumand maximum values of channel A of the arbitrary waveform generator (AWG) to 0.5 V and 4.5V, respectively, to apply a peak-peak square waveform centered on 2.5 V as the circuit's inputvoltage. The source voltage measure current (SVMI) mode was chosen from the AWG A drop-down menu as a square waveform menu. Channel A's frequency was set to 15 Hz, and Hi-Z modewas chosen from the AWG B mode drop-down menu. CA-V and CB-V were chosen for displayfrom the ALICE curves drop-down menu
%, Pell enrollment ~50% of the total enrollment. Based on a total enrollment of about 1500 students per class. * African American average GPA gap is significantly higher than URM, typically 0.3-0.85, and enrollment is about 5% of the total. A 0.4 gap in GPA separates ‘B+’ and ‘A-’ grades, for example. Data provided by the California State University Student Success Dashboard [30]To overcome the GPA gap and the DFW disparities, we plan to redesign six critical-path, largeenrollment courses ENGR1 Introduction to Engineering, ENGR17 Introductory Circuit Analysis,EEE117 Network Analysis, EEE108 Electronics I, EEE161 Applied Electromagnetics, andEEE180 Signals & Systems, based on active
furthercategorized the student experiences into “cognitive, affective, metacognitive, and pedagogicalcategories”, as influenced by Bloom’s taxonomy, Fink’s taxonomy, and the work explained in[53], [60], [61]. The categorization structure for codes representing challenging experiences isshown below in Figure 3.Figure 3. Categorization structure of codes representing challenging experiences into cognitive,metacognitive, and affective experiences, in addition to pedagogical factors. Categories labeledwith (B) are extracted from Bloom’s taxonomy, and categories labeled with (F) are extractedfrom Fink’s significant learning outcomes.With this structure, we were able to assess Kulkarni’s experiences as a BLV student in ENGR40M more comprehensively, and we also
Paper ID #41730Microelectronics Research and Global Competencies: Unpacking ResearchAbroad Experiences of Engineering StudentsChibuzor Joseph Okocha, University of Florida Okocha Chibuzor Joseph is an ambitious Ph.D. student at the University of Florida, specializing in the integration of Artificial Intelligence (AI) in engineering Education and computer science education with a significant focus on global competence. His pioneering research, guided by Professor Gloria Kim, is at the forefront of educational innovation and aims to transform the landscape of learning in these technologically advanced fields. Chibuzor
intelligence in healthcare: past, present and future," Stroke and vascular neurology, vol. 2, no. 4, 2017.[21] T. M. Mitchell, Machine learning. McGraw-hill New York, 2007.[22] A. Pathak. "Top 14 In-Demand Skills Required for AI Professionals." Geekflare. https://geekflare.com/skills-required-for-ai-professionals/ (accessed Feb 28, 2023).[23] B. Marr. "9 Soft Skills Every Employee Will Need In The Age Of Artificial Intelligence (AI)." Forbes. https://www.forbes.com/sites/bernardmarr/2020/09/28/9-soft-skills-every- employee-will-need-in-the-age-of-artificial-intelligence-ai/?sh=66e4a4b354b8 (accessed February 28, 2023).[24] F. Ertam and G. Aydın, "Data classification with deep learning using Tensorflow," in
examining differenceswithin each department, to identify differences in course characteristics or topics that haveunbalanced student enrollment.References[1] T. Ross, G. Kena, A. Rathbun, A. KewalRamani, J. Zhang, P. Kristapovich, and E. Manning.“Higher Education: Gaps in Access and Persistence Study (NCES 2012-046)”. U.S. Departmentof Education, National Center for Education Statistics. Washington, DC: Government PrintingOffice, 2012.[2] R. Fry, Kennedy, B. and C. Funk, “STEM jobs see uneven progress in increasing gender,racial and ethnic diversity”. Pew Research Center, 2021, pp.1-28.[3] S. James, S. Singer. “From the NSF: The National Science Foundation's Investments inBroadening Participation in Science, Technology, Engineering, and Mathematics
the overall efficiency of the educational management process. Figure 2 depicts the outline of the interfaces for IntelliGroups. a. Model of Landing Page b. Model of Group Pagec. Model of Group Parameter Page d. M odel for Custom Questions Input Page e. Model for Creating Initial Survey Figure 2. The outline of the interfaces for IntelliGroups he initial version of IntelliGroup incorporated three grouping criteria: gender of Tstudents, students’ grades in the class, and project preference. The application
Towards Seeing Themselves as Scholars," The Review of Higher Education, vol. 42, pp. 1527-1547, 01/01 2019, doi: 10.1353/rhe.2019.0074.[13] J. P. Azevedo, M. Gutierrez, R. de Hoyos, and J. Saavedra, "The unequal impacts of COVID-19 on student learning," Primary and secondary education during Covid-19: Disruptions to educational opportunity during a pandemic, pp. 421-459, 2022.[14] E. CAMP. "Students lost one-third of a school year of learning during the pandemic." https://reason.com/2023/02/03/children-lost-one-third-of-a-year-of-learning-during-the- pandemic-analysis-finds/ (accessed Feb 3, 2023.[15] K. A. Bird, B. L. Castleman, and G. Lohner, "Negative impacts from the shift to online learning
Paper ID #38206Board 83: Sensor Fusion Algorithms and Tracking for Autonomous SystemsDr. Zekeriya Aliyazicioglu, Cal Poly Pomona Dr. Zekeriya Aliyazicioglu received his M.S. degree in 1991 and Ph.D. degree in 1995, both in Electri- cal Engineering from Southern Methodist University (Dallas, Texas). He is currently a Professor of the Department of Electrical and Computer Engineering a . He is currently a Professor of the Department of Electrical and Computer Engineering at Cal Poly Pomona. His research interests include Digital Sig- nal Processing and Digital Image Processing applications, Communication Systems, and Robotics
Paper ID #44333Bridging the Gap: Exploring Semiconductors Exposure and Motivation amongMultidisciplinary Engineering Students ¨ University of FloridaDr. Lilianny Virguez, Lilianny Virg¨uez is an Instructional Associate Professor within the Engineering Education Department at the University of Florida. With a background in the telecommunications industry, Dr. Virg¨uez brings valuable practical experience to her academic role. She earned her Ph.D. in Engineering Education and a Master’s degree in Management Systems Engineering from Virginia Tech, complementing her Bachelor’s degree in Telecommunications