Conference Session

Liberal Education Revisited: Five Historical Perspectives

Collection

2011 ASEE Annual Conference & Exposition

Authors

John Heywood, Trinity College, Dublin

Tagged Divisions

Liberal Education/Engineering & Society

thisstudy [8]. These studies were examined and contributed to the student‟s overallassessment. Accompanying these developments in the Technical College Sector was therise of an Association for Liberal Education that had its own research officer [9].It will not have escaped the notice of the reader that no mention is made of universitystudents in technological studies receiving such treatment. Why should a person on adegree course be treated differently? The concept of liberal education has a long historythat can be traced back to the Greeks, and Davies provides an all too brief history of thedevelopment of liberal education from those times [8.ch 1]. From the Greeks and theRomans we get the notions of being free to learn, and as Davies notes

Conference Session

Outstanding Contributions: Mechanical Engineering Education

Collection

2011 ASEE Annual Conference & Exposition

Authors

Patrick W. Pace, University of Texas, Austin; Kristin L. Wood, University of Texas, Austin; John J. Wood, U.S. Air Force Academy; Daniel D. Jensen, U.S. Air Force Academy; Brian K Skibba, Air Force Research Laboratory

Tagged Divisions

Mechanical Engineering

Professor in the Department of Engineering Mechanics at the U. S. Air Force Academy. He has published approximately 100 technical publications and generated approximately 2 million dollars of research finding. His current research interests include development of new design methodologies as well as methods for improving engineering education. Page 22.1350.1 c American Society for Engineering Education, 2011Studying Ideation in Engineering Design Education: Application to Highly Mobile RobotsIntroduction Developing innovative ideas as part of engineering design can be

Conference Session

Entrepreneurship Teaming and Collaboration

Collection

2012 ASEE Annual Conference & Exposition

Authors

Andrew L Gerhart, Lawrence Technological University; Donald D. Carpenter, Lawrence Technological University

Tagged Divisions

Entrepreneurship & Engineering Innovation

partnered with The Henry Ford, both of which are located in the Detroitmetro area. As a result, Lawrence Tech‟s camp was focused on exploring creativity, innovation,and ingenuity as it relates to the American experience and manufacturing. In subsequentsummers, Boston University and St. Louis University will host summer enrichment opportunities Page 25.364.3in their respective metro areas. (Themes, details, and objectives for the Boston and St. Louiscamps had not been finalized by the time of publication of this paper.)2. Lawrence Tech Summer Enrichment ProgramThe Detroit metro area is well known as being the world‟s automotive industry capital and

Conference Session

Breaking barriers, building futures: Narratives of equity and inclusion in STEM education

Collection

2024 ASEE Annual Conference & Exposition

Authors

Bailey Bond-Trittipo, Florida International University; Stephen Secules, Florida International University; Jocelyn Garcia; Maria Oralia Tinoco Alegre, Florida International University; Malak Elaouinate, Florida International University; Andrew Green, Florida International University; Andres TREMANTE

Tagged Topics

Diversity

Tagged Divisions

Culture & Social Justice in Education Division (EQUITY), Equity

Conference Session

Architectural Engineering Division (ARCHE) Technical Session 1

Collection

2024 ASEE Annual Conference & Exposition

Authors

Ryan Solnosky P.E., Pennsylvania State University; John J. Phillips, Oklahoma State University

Tagged Divisions

Architectural Engineering Division (ARCHE)

furthest tocompletion, with electrical design being lowest and equal to plumbing. An unexpected result was how manytake their designs to a construction document (CD) level of completeness (Fig. 2b). This could be partiallydue to a team’s ability to go to that level of refinement, or perhaps certain key parts of a discipline’ssystem(s) are developed to that extent while other parts are not. For example, a team may design a singlestructural connection but not all of them in the building. To provide some literature context, most capstoneshave students target a level of completeness of their project somewhere between SD and DD [18-19]. a) covered within the capstone b) completeness of student work

Conference Session

MECH - Technical Session 9: Advanced Mechanical Engineering Topics

Collection

2024 ASEE Annual Conference & Exposition

Authors

Rachel Mok, Massachusetts Institute of Technology; Cong Li, Massachusetts Institute of Technology; Benita Comeau, Massachusetts Institute of Technology; Emily Welsh, Massachusetts Institute of Technology; Nicholas Xuanlai Fang, University of Hong Kong; John Liu, Massachusetts Institute of Technology

Tagged Divisions

Mechanical Engineering Division (MECH)

their ability to learn the ma-terial, apply the material they have learned, and how well they believe they will perform in the Figure 5: User testing flow chart.learning activity. The full list of questions in the affective assessment is provided in Appendix B.The cognitive assessment consists of five multiple-choice questions focusing on technical aspectsof AFM imaging and identifying sources of common image artifacts.In the lab session, once it was confirmed that each student had completed the pre-lab, they wererandomly assigned to either the simulation cohort or the traditional paper (control) cohort. Stu-dents in the paper cohort did not have access to the simulation and were instead provided withimage(s

Conference Session

Student Division Technical Session 2: Career Development and Employability

Collection

2024 ASEE Annual Conference & Exposition

Authors

Mandana Ashouripashaki, The Ohio State University; Krista M Kecskemety, The Ohio State University

Tagged Divisions

Student Division (STDT)

behaviors.The foundation of the MBTI lies in four fundamental dimensions, each represented by a pair ofopposing traits: • Extraversion (E) – Introversion (I): This dimension focuses on where individuals direct their attention and energy. Extraverts gain their energy from external sources and thrive on social interaction, while introverts find solace in their inner world and prefer reflection. • Sensing (S) – Intuition (N): This aspect relates to how individuals process information. Sensing types rely on concrete details and present realities, while intuitive types prioritize abstract concepts and future possibilities. • Thinking (T) – Feeling (F): This dimension highlights decision-making styles. Thinkers

Conference Session

Diverse Pathways: Exploring Inclusive Practices and Outreach in Engineering Education

Collection

2024 ASEE Annual Conference & Exposition

Authors

Maimuna Begum Kali, Florida International University; Gabriel Van Dyke, Utah State University; Stephen Secules, Florida International University; Cassandra J McCall, Utah State University; Bruk T Berhane, Florida International University; Vanessa Tran, Utah State University; Agustina Dotta Ceriani, Florida International University

Tagged Topics

Diversity

Tagged Divisions

Minorities in Engineering Division(MIND)

Services at Utah State University. Her research centers the intersection identity formation, engineering culture, and disability studies. Her work has received several awards including best paper awards from the Journal of Engineering Education and the Australasian Journal of Engineering Education. She holds a Ph.D. in Engineering Education from Virginia Tech as well as M.S. and B.S. degrees in civil engineering from the South Dakota School of Mines and Technology.Dr. Bruk T Berhane, Florida International University Dr. Bruk T. Berhane received his bachelorˆa C™s degree in electrical engineering from the University of Maryland in 2003. He then completed a masterˆa C™s degree in engineering management at George

Conference Session

DSA Technical Session 7

Collection

2024 ASEE Annual Conference & Exposition

Authors

Harpreet Auby, Tufts University; Namrata Shivagunde, University of Massachusetts, Lowell; Anna Rumshisky, University of Massachusetts, Lowell; Milo Koretsky, Tufts University

Tagged Topics

Data Science & Analytics Constituent Committee (DSA)

with the question, four in-context examples of answers, and the corresponding codes and instructed it to generate thecode(s) for the new answer instance. The in-context examples for GPT-4 prompt are drawn fromthe training split of the manually-coded dataset. We finetuned the Mixtral of Experts (MoE) [30]model using input and target pairs derived from the manually-coded training datasets. Thistrained model was then prompted with new test inputs, and the model-generated coded sequencewas evaluated against the manually coded target sequence. We evaluated both models on a testset of around 140 samples for each thermodynamics question. Using manual and languagemodel-based coding, we aim to answer two research questions: 1. What aspects of student

Conference Session

Open-Ended Problems and Student Learning

Collection

2011 ASEE Annual Conference & Exposition

Authors

Nora Siewiorek, University of Pittsburgh; Larry J. Shuman, University of Pittsburgh; Mary E. Besterfield-Sacre, University of Pittsburgh; Rosa Goldstein, University of Pittsburgh

Tagged Divisions

Educational Research and Methods

to the Reflection Tool QuestionsAn excerpt of the responses Instructor 1 gave during the interview is summarized below in Table2. The comparisons to student responses are also listed, which includes only the top responses(or top two if the difference in number of responses was 2 or less). A discussion of thecomparison of the two responses follows Table 2.Table 2: Instructor 1’s perception of student responses to reflection questions in the Engineering Page 22.351.6Economic Analysis CourseReflection Tool Questions Instructor 1 perception MEA specifics Comparison to

Collection

2023 ASEE GSW

Authors

Piyush Tandon; Larry Powell; Seth Polsley; Tracy Hammond

participant is not actually swimming any particular stroke. Prior methods of conductingstudies would record some level of inactive data (e.g. participant walking to the pool), whichwould then have to be parsed and removed manually. We can also record flip turns with this app,which also allows us to avoid manually removing flip turns in order to preserve data integrity.This application was developed through prior work done with Powell [55].Data Processing And Feature ExtractionIn order to extract features and train a classifier using our accelerometer data, we first need toclean the data, extract features, and present it to our classifier(s) in a .csv file format, which is afile format that WEKA, a machine learning library, accepts as input for

Conference Session

Educational Research and Methods Division (ERM) Technical Session 2

Collection

2024 ASEE Annual Conference & Exposition

Authors

Asif Mohaisin Sadri, International Islamic University, Malaysia; Arif Mohaimin Sadri, University of Oklahoma; Khondhaker Al Momin, University of Oklahoma; Javeed Kittur, University of Oklahoma; Tahrima Rouf, University of Oklahoma

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods Division (ERM)

Conference Session

Educational Research and Methods Division (ERM) Technical Session 29

Collection

2024 ASEE Annual Conference & Exposition

Authors

Justin Charles Major, Rowan University; Richard Tyler Cimino, New Jersey Institute of Technology

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods Division (ERM)

caring that includes both comfortwith faculty and empathetic faculty understanding from the same author.Discrimination (25 items)Discrimination is an active process that influences belonging in engineering (McGee, 2020). Toaccount for this potential, we adapted and included five items across five different identity-axes(race/ethnicity, gender, sexual orientation, (dis)ability, and socioeconomic status) from Bahnsonet al.’s (2022) work on discrimination in engineering graduate student experiences.Comfort and Team Inclusion (19 items)We believe feelings of discrimination and differences in belonging are also seen through students’comfort and inclusion on their team. As such, we included items based on these topics. Like othersabove, these scales

Collection

2024 ASEE Midwest Section Conference

Authors

Hamzah Mousa; Margarita O. Genes; Adam C. Lynch

P O TENCIAL P O TENCIAL CURRENT P RO CES S P O TENCIAL FAILURE RP N ( S EV x O CC x RECO MMENDE EFFECTS O F S EV CAUS ES O F O CC P RO CES S DET ACTIO NS TAKENS TEP / FUNCTIO N MO DE DET) D ACTIO NS FAILURE FAILURE CO NTRO L

Conference Session

PCEE Technical Session 5: STEM Teacher Instructional Moves

Collection

2022 ASEE Annual Conference & Exposition

Authors

Pamela Lottero-Perdue, Towson University; Jamie Mikeska

Paper ID #37136Simulated Engineering Teaching Experiences: PreserviceTeachers Learning to Facilitate Discussions to Help StudentsBecome Informed Designers (RTP)Pamela S. Lottero-Perdue (Professor of Science & Engineering Education) Pamela S. Lottero-Perdue, Ph.D., is Professor of Science and Engineering Education in the Department of Physics, Astronomy & Geosciences at Towson University. She has integrated engineering into courses for PreK-8 teacher candidates, developed and directed a graduate STEM program for PreK-6 teachers, and partnered with teachers to implement PreK-8 science-integrated engineering

Conference Session

Design Cognition III

Collection

2012 ASEE Annual Conference & Exposition

Authors

David R. Wright, North Carolina State University

Tagged Divisions

Design in Engineering Education

Collection

2022 ASEE Gulf Southwest Annual Conference

Authors

Xishuang Dong, Prairie View A&M University; Xavier Alexander Dukes; Joshua Littleton, Prairie View A&M University; Tri'Heem Neville; Christopher Rollerson; Arthur L Quinney

Tagged Topics

Diversity

ConclusionThis paper presents preliminary work of the implementation of object detection on Raspberry Pi for asenior design project. We run a mobile deep learning model, SSD-MobileNet, on Raspberry Pi todetect various objects. Preliminary valudation results demonstrate the effectiveness of thisimplementation. Moreover, the on-going work is to improve weapon detection. Future work will focuson completing comprehensive and systematical validation on weapon detection in different testingscenarios. References1. Dave, E. (2011). How the next evolution of the internet is changing everything. The Internet of Things.2. Islam, S. R., Kwak, D., Kabir, M. H., Hossain, M., and Kwak, K. S. (2015). The internet

Collection

2022 ASEE Gulf Southwest Annual Conference

Authors

Olubunmi Gregory Adekanmbi, Prairie View A&M University

discussed.Below are the basics of the Gravitational N-Body Problem for the sake of this experiment. Findingpositions and movements of bodies in space subject to gravitational forces from other bodies usingNewton’s laws of motion.Gravitational force F between two bodies of masses ma and mb as seen in Figure 1 is: (1) Figure 1: Gravitational N-Body ProblemG is the gravitational constant (6.673 × 10-11 m3 kg-1 s-2) and r the distance between the bodies. (2)For a system of N particles, the sum of the forces is

Collection

2022 ASEE Gulf Southwest Annual Conference

Authors

Carol E Akpan, Prairie View A&M University ; Lealon L Martin; Kendall Lemons

Tagged Topics

Diversity

particular, researchers performanalyses of the environments associated with a microgreens market using a PESTLE framework –which identifies the political (P), economic (E), sociocultural (S), technological (T), legal (L), andenvironmental (E) forces influencing a market. The political environment (P) is favorable towardsincreased microgreen production. For example, the Farm Bill of 2018 provided the USDA’s NationalInstitute of Food and Agriculture with up to $10 million of annual funding toward a competitive grantprogram supporting the development of urban, indoor, and emerging agriculture practices (USDA)2.The economic environment (E) is perceived to be favorable for a microgreens market. Microgreenstrade at a premium when compared to other

Collection

2022 ASEE Gulf Southwest Annual Conference

Authors

Kazi Meharajul Kabir, Prairie View A&M University; shuza Binzaid; John Okyere Attia P.E., Prairie View A&M University

, fabricated, and tested successfully at the PVAMU's SMART Center for bike laneapplications. The EGP is composed of seven layers of compound materials. A 3-feet-long integratedPZT strip of 18 thin-film PZT cells was placed in the middle of the EGP. The prototype of the EGPwas tested using an output load of 7.5 kΩ. A bicycle with a rider weighing a total of about 142pounds served as the mechanical pressure source for the test. The tested PZT cells produced anaverage of 68 VDC, and the energy of the DCPR was 616.53 mW/s for the rider riding the bike onthe EGP. IntroductionGlobal energy demand is increasing due to technological advances and consumer patterns that haveled to increased energy demand [1-2

Collection

2022 ASEE Gulf Southwest Annual Conference

Authors

Ruaa Al Mezrakchi, Tarleton State University; Ahmed Al-Ramthan, Tarleton State University

Tagged Topics

Diversity

of the 2022 ASEE Gulf-Southwest Annual Conference Prairie View A&M University, Prairie View, TX Copyright © 2022, American Society for Engineering Education 7 References1. Sumarni, S., 2016, "Think Pair Share effect of understanding the concept and achievement," in Proceeding of the International Conference on teacher Training and Education, Vol. 2, No. 1, pp. 783-787.2. Deshpande, A. and Salman, B., 2016, "Think-pair-share: application of an active learning technique in engineering and construction management classes," in Associate Schools of Construction, 52nd

Collection

2022 ASEE Gulf Southwest Annual Conference

Authors

Aniket Patel, Texas A&M University; Seth Polsley, Texas A&M University; Tracy Anne Hammond, Texas A&M University

slightly betterresults. Our next steps include building on existing sketch recognition research andincorporating more features such as tilt and pressure measurements in hopes of building areliably accurate application to access children’s fine motor skills. References 1. Grissmer, D., Grimm, K.J., Aiyer, S.M., Murrah, W.M., Steele, J.S.: Fine motor skills and early comprehension of the world: two new school readiness indicators. Develop-mental psychology 46(5), 1008 (2010). 2. Anthony, L., Brown, Q., Nias, J., Tate, B., Mohan, S.: Interaction and recognition challenges in interpreting children’s touch and gesture input on mobile devices. In:Proceedings of the 2012 ACM

Conference Session

Faculty Development Division (FDD) Technical Session 4

Collection

2023 ASEE Annual Conference & Exposition

Authors

Gabriella Coloyan Fleming, University of Texas, Austin

Tagged Topics

Diversity

Tagged Divisions

Faculty Development Division (FDD)

) further narrowing the list down to a “short list” for an on-site, in-personinterview, 5) deciding which candidate(s) will receive an offer, and 6) negotiation. In somecases, steps three and four are skipped, and only one round of interviews is completed. The faculty hiring process is fraught with bias, including racial bias [1], gender bias inletters of recommendation [2], and search committee members seeking to hire people whoseresearch areas are most similar to their own [3]. Hiring people similar to oneself extends beyondresearch areas. Many search committees look for candidates who would be a good “fit”(generally, scientifically, programmatically) [4, 5]. However, “fit” is highly subjective and opento the evaluator’s personal biases

Conference Session

Entrepreneurship & Engineering Innovation Division (ENT) Poster Session

Collection

2023 ASEE Annual Conference & Exposition

Authors

Chithra Adams, VentureWell; Sarah E. Zappe, Pennsylvania State University; Stephanie Cutler, Pennsylvania State University; Phil Weilerstein, Broadening Impacts; Hope Liu

Tagged Divisions

Entrepreneurship & Engineering Innovation Division (ENT)

necessarily reflect the views of the NSF.References 1. SE. Zappe, SL. Cutler, & L. Gase. 2023. A Systematic Review of the Impacts of Entrepreneurial Support Programs in Science, Technology, Engineering, and Math Fields. Entrepreneurship Education and Pedagogy, 6(1), 3–31. https://doi.org/10.1177/25151274211040422 2. F. Hasson, S. Keeney, and H. McKenna. 2000. Research guidelines for the Delphi survey. Journal of Advance Nursing, vol. 32, pp. 1008-1015. 3. F. Hasson, and S. Keeney, “Enhancing rigour in the Delphi technique research,” 2011, Technological Forecasting & Social Change, vol. 78, pp. 1695-1704. 4. P. Wainwright, A. Gallagher, H. Tompsett, & C. Atkins. 2010. The use of vignettes within a

Conference Session

Will This Be on the Mechanics Test? Concept Inventories and Understanding Exams

Collection

2023 ASEE Annual Conference & Exposition

Authors

Anna K. T. Howard, North Carolina State University, Raleigh; Azadeh Dashti Cole, North Carolina State University, Raleigh

Tagged Divisions

Mechanics Division (MECHS)

engineering computer applications. Proceedings of the 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. https://peer.asee.org/413492 Moore, J. P., & Ranalli, J. (2015, June), A Mastery Learning Approach to Engineering Homework Assignments. Proceedings of the 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.234053 R. Averill, S. Roccabianca, and G. Recktenwald, A Multi-Instructor Study of Assessment Techniques in Engineering Mechanics Courses. Proceedings of the 2019 ASEE Annual Conference & Exposition, Jun. 2019. https://peer.asee.org/a-multi-instructor-study-of-assessment-techniques-in-engineering-mechanics- courses4 Sangelkar, S., & Ashour, O. M., &

Conference Session

Equity, Culture & Social Justice in Education Division (EQUITY) Technical Session 4

Collection

2023 ASEE Annual Conference & Exposition

Authors

Stephanie Masta, Purdue University, West Lafayette ; Janelle Grant, University of Illinois, Urbana-Champaign; Cara Margherio, University of Washington; Darryl Dickerson, Florida International University; Matthew W. Ohland, Purdue University, West Lafayette ; Alice L. Pawley, Purdue University, West Lafayette

Tagged Topics

Diversity

Tagged Divisions

Culture & Social Justice in Education Division (EQUITY), Equity

Conference Session

Engineering Technology Division (ETD) Technical Session 1

Collection

2023 ASEE Annual Conference & Exposition

Authors

Carmen Cioc, The University of Toledo; Sorin Cioc; Noela A. Haughton, The University of Toledo

Tagged Divisions

Engineering Technology Division (ETD)

develop a better understanding of the technical content, societal andeconomic impact of the proposed solution, while supporting the students’ preparedness andreadiness for the workforce.IntroductionThere are numerous recent scholarly works examined the way in which the Kern EntrepreneurialEngineering Network (KEEN)’s mindset is enhancing the students’ engagement and skills invarious engineering courses, like Material Science [1], or Mechanical Design or StructuralAnalysis [2, 3, 4], or Fluid Mechanics [5, 6, 7, 8] or across engineering curriculum [9, 10, 11, 12,13].In all instances, the authors found that the inclusion of an entrepreneurship education, aspromoted by KEEN, and further support the engineering students’ readiness for the

Collection

2022 ASEE - North Central Section Conference

Authors

Scott Duplicate Streiner, University of Pittsburgh; Qin Zhu, Colorado School of Mines

Tagged Topics

Diversity

. Review of General Psychology, 19(4), 408–424. https://doi.org/10.1037/gpr00000536. Graham, J., Nosek, B. A., Haidt, J., Iyer, R., Koleva, S., & Ditto, P. H. (2011). Mapping the Moral Domain. Journal of Personality and Social Psychology. https://doi.org/10.1037/a00218477. Clancy, R. F. (2021). The Relations between Ethical Reasoning and Moral Intuitions among Engineering Students in China. 2021 ASEE Virtual Annual Conference Content, July 2021.8. Graham, J., Haidt, J., & Nosek, B. A. (2009). Liberals and Conservatives Rely on Different Sets of Moral Foundations. Journal of Personality and Social Psychology, 96(5), 1029–1046. https://doi.org/10.1037/a00151419. Graham, J., Meindl, P., Beall, E., Johnson, K. M., & Zhang, L

Conference Session

Educational Research and Methods (ERM) Division Poster Session

Collection

2022 ASEE Annual Conference & Exposition

Authors

Saharnaz Baghdadchi, University of California, San Diego; Alex Phan, University of California, San Diego; Carolyn Sandoval, University of California, San Diego; Huihui Qi, University of California, San Diego; Marko Lubarda, University of California, San Diego; Nathan Delson, University of California, San Diego

five potential answers ranging from “to a great extent” to “not at all”and two free response questions were utilized in this study. The Likert scale questions used inthis study were: ● Did the oral exam(s) contribute positively to your learning in the course? ● Do you feel that the oral exam(s) helped improve your technical speaking skills? ● Did the oral exam(s) increase your motivation to learn? ● Do you feel the oral exam(s) contributed positively to academic integrity in the course? ● Did the oral exams cause you undue stress?The two free response questions asked about the best aspects of the oral exams and their areas ofimprovement. To run ANOVA on ranks tests and find the correlation between different factors,scores of 5

Conference Session

Case Studies

Collection

2022 ASEE Zone IV Conference

Authors

Yuri R. Rodrigues, Seattle Pacific University

Tagged Topics

Conference Submission, Diversity

-thematic in the design and decision-making process [14]. Moreover, the proposed holisticengineering design education prevailing over the restricted use of key technical macro-thematicfactors, allow for the design of equitable and inclusive solutions through the consideration of thediverse influences associated with the project. This is an especially critical feature given that keytechnical macro-thematic factors used for traditional engineering design may be developed basedon specific group(s) of our society. Therefore, not accounting for the uniqueness and diversity thatlocal-thematic may impose, and even demand, from the respective solution, e.g., Smart Gridprojects for a high- and low- income regions significantly differ on its design features