Conference Session

Pre-college Engineering Education Division Technical Session 19

Collection

2020 ASEE Virtual Annual Conference Content Access

Authors

Foad Hamidi, University of Maryland, Baltimore County; Adena Moulton, Digital Harbor Foundation; Shawn Grimes; Stephanie Grimes; Andrew Coy, Digital Harbor Foundation

Tagged Divisions

Pre-College Engineering Education

months, we collected data using aseries of survey tools including two Upper Elementary School and Middle/High School StudentAttitudes toward STEM (S-STEM) Surveys (Technology and Engineering and 21st CenturySkills) [8] and the Alternative Uses Test (AUT) [9][10]. Additionally, we conducted interviewswith representative youth about their perceptions and attitudes towards the surveys.While the AUT results showed a positive change in the youth, initial results from pre-postSTEM-S evaluations showed insignificant and sometimes negative shifts in youth's intereststowards Technology and Engineering, and 21st Century Skills. Interviews showed that youthstruggled to accurately assess changes in themselves due to the time lapse between pre-postprogram

Collection

2020 Northeast Section Meeting

Authors

Aditi Deokar

- 0.899 ± 0.784 ± 1.000 ± 0.880 ± 0.734 ± 0.947 ± 0.944 ± 0.987 ±ROC score 0.021 0.025 0.000 0.058 0.038 0.008 0.014 0.005 Ye et al. had also found that gradient boosting was the best machine learning model, as measured by AUC-ROC score (0.709), but their logistic regression model was their best predictor (0.7351). However, we found that our gradient boosting model (0.864) outperformed both our logistic regression model (0.753) and Ye et al.’s logistic regression model in AUC-ROC score. Our gradient boosting model also slightly outperformed Artzi et al.’s gradient boosting model (0.85 AUC-ROC score), created based on electronic health records

Collection

2003 GSW

Authors

Chun-Ling Huang

performance. Students declaring relatively strong self-efficacy, generally achieved higher academic grades, and were much more likelypersisting in engineering majors than those with low self-efficacy [11].Following up on their early research with an investigation comparing self-efficacy theoryto alternative theoretical paradigms. Lent et al., reported evidence suggesting that self-efficacy is helpful in the prediction of the grades and persistence of engineering majors.Brown, Lent, and Larkin documented the interactions between aptitude and self-efficacy.Brown et al.’s results suggest that strong self-efficacy expectations especially importantto the success of moderate ability students as compared to high-ability students, and arealso predictive of

Conference Session

Improving Mechanics & Structural Modeling Courses

Collection

2009 Annual Conference & Exposition

Authors

Arnaldo Mazzei, Kettering University; Richard Scott, University of Michigan

Tagged Divisions

Mechanical Engineering

: W ? bhL τ g (3)Where τ is the mass density and g ? 9.81 m s 2 .The problem is one of multi-objective optimization, namely, the simultaneous minimization ofυm and W , with b and h as design variables.Several interesting and informative points arise at this juncture. The aim here is to raise somequestions, and answer some of them, that should expand student horizons and make them moreaware, in particular, of some design issues. 6 PLLet f1 ( … bhL τ g ) be the weight objective function and f 2 ( … ) be the stress objective

Conference Session

Assessing Design Coursework

Collection

2006 Annual Conference & Exposition

Authors

Michael Trevisan, Washington State University; Denny Davis, Washington State University; Steven Beyerlein, University of Idaho; Phillip Thompson, Seattle University; Olakunle Harrison, Tuskegee University

Tagged Divisions

Design in Engineering Education

., Magleby, S. P, Sorensen, C. D., Swan, B. R., & Anthony, A. R. (1995). A survey of capstone engineering courses in North America. Journal of Engineering Education, 165-174. 2. McKenzie, L., Trevisan, M., Davis, D., & Beyerlein, S. (2004). Capstone design courses and assessment: A national study. Paper presented at the American Society for Engineering Education Annual Conference. 3. National Research Council. (2001). Knowing what students know: The science and design of educational assessment. Washington, DC: The National Academies Press. 4. Campbell, S., & Colbeck, C. L. (1997). Teaching and assessing engineering design: A review of the research. Paper presented at the American Society for

Conference Session

Problem Solving, Adaptive Expertise, and Social Engagement

Collection

2018 ASEE Annual Conference & Exposition

Authors

Oenardi Lawanto, Utah State University; Angela Minichiello P.E., Utah State University; Jacek Uziak, University of Botswana; Andreas Febrian, Utah State University

Tagged Divisions

Educational Research and Methods

students’ knowledge about the task-related discipline(s) [24], [25]. In thisstudy, we only focus on the implicit and explicit aspect of task interpretation. This study views task interpretation as an integral part of self-regulation. Self-regulatedlearning (SRL) is a complex, iterative, and situated goal-directed learning process [5], [8], [26].SRL is comprised by the student, learning environment, and learner’s engagement with theenvironment and is affected by student’s emotion and motivation [7], [9], [26]. Student’sengagement starts with task interpretation. Task interpretation is followed by (a) developing aplan based on the task understanding, (b) enacting the plan, (c) monitoring the progress andapproach, and (d) making any

Conference Session

Active Learning Methods in Action

Collection

2018 ASEE Annual Conference & Exposition

Authors

John Ray Morelock, Virginia Tech; Holly M. Matusovich, Virginia Tech

Tagged Divisions

Educational Research and Methods

about performance, and then code, gave students visual and textual practice more. The goal is to feedback about the code’s results, and improve performance in particular allowed students to retry or move to a concepts/skills over time. harder level (Chaffin et al., 2009). Gamified academic Students perform common A board game where students answered activity classroom learning task(s) with multiple-choice questions about the task-irrelevant game mechanics learning content to correctly to move (e.g., points, rewards, moving around the

Conference Session

NSF Grantees Poster Session

Collection

2018 ASEE Annual Conference & Exposition

Authors

Matthew W. Ohland, Purdue University, West Lafayette (College of Engineering); Susan M. Lord, University of San Diego; Marisa K. Orr, Clemson University; Russell Andrew Long; Richard A. Layton, Rose-Hulman Institute of Technology; Catherine E. Brawner, Research Triangle Educational Consultants; Nichole Ramirez, Purdue University

Tagged Topics

NSF Grantees Poster Session

teamwork models, statewide pre-college math initiatives, teacher and faculty professional development programs, and S-STEM pro- grams.Nichole Ramirez, Purdue University Nichole Ramirez is a postdoctoral researcher in the School of Engineering Education at Purdue Univer- sity. She received her Ph.D. in Engineering Education and M.S. in Aviation and Aerospace Management from Purdue University and her B.S. in Aerospace Engineering from The University of Alabama. She is currently the Associate Director of Policy Analysis for the Multi-Institution Database for Investigating Engineering Longitudinal Development (MIDFIELD). c American Society for Engineering Education, 2018 Expanding

Conference Session

Poster Session

Collection

2019 ASEE Annual Conference & Exposition

Authors

Kenie R. Moses

Tagged Divisions

Computers in Education

, number of engineering courses taken and studentclassification (freshman, sophomore, etc.) in addition to student demographics and engineeringmajor. Analyzing these connections, if any, may be of great interest to researchers and practitionersattempting to affect positive change in engineering students’ affective domains.References[1] Y. Tang, R. University, S. Shetty, T. S. University, X. Chen, and R. University, “Interactive VirtualReality Games to Teaching Circuit Analysis with Metacognitive and Problem-Solving Strategies,”presented at the ASEE Annual Conference & Exposition, Vancouver, BC, June,, 2011.[2] H. Khalil and M. Ebner, “MOOCs Completion Rates and Possible Methods to Improve Retention - ALiterature Review,” In Proceedings of

Conference Session

International Division Technical Session 5

Collection

2015 ASEE Annual Conference & Exposition

Authors

Cheryl Matherly, The University of Tulsa; Sarah R. Phillips, Rice University ; Cody A. Chapman, University of Tulsa

Tagged Topics

Diversity

Tagged Divisions

International

. student in Industrial/Organizational Psychology at the University of Tulsa. Page 26.1544.1 c American Society for Engineering Education, 2015 The Impact of International Research Experiences on Undergraduate Learning1.0 IntroductionThis paper compares the learning outcomes for students participating in domestic andinternational research experiences. This question is important given that science andengineering (S&E) research is increasingly collaborative and international in scope withresearch teams comprised of faculty and student researchers in multiple

Conference Session

Engineering Technology Division Poster Session

Collection

2016 ASEE Annual Conference & Exposition

Authors

Xiumin Diao, Purdue University

Tagged Divisions

Engineering Technology

controller, the stabilizing controller, and themode controller will be discussed in the next three sections.A. Design of the position controller The pendulum in the system has a length of 2 L  0.335 (m) and its center of mass is located atits geometric center. Thus the natural frequency for small oscillation of the pendulum is given by mgL 3g p    6.628 (rad/s)  IA 4Lwhere I A is the mass moment of inertia of the pendulum about point A . To have the rotating armto react to the pendulum’s movements quickly, the closed-loop response of the rotating armshould be considerably

Conference Session

College Industry Partnerships Division Technical Session 2

Collection

2017 ASEE Annual Conference & Exposition

Authors

Hossein EbrahimNejad, Purdue University

Tagged Divisions

College Industry Partnerships

and undergraduate programs. Further, todate there does not appear to be a single accepted approach or best practice for incorporatingtargeted competencies into engineering curricula. More research into how to address andincorporate targeted engineering competencies into undergraduate curricula is called for.AcknowledgementI acknowledge the contributions of Dr.Mary Pilotte. References1 Parry, S. B. Just What Is a Competency?(And Why Should You Care?). Training 35, 58 (1996).2 Turley, R. T. & Bieman, J. M. in ACM Conference on Computer Science. 271-278.3 Nair, C. S., Patil, A. & Mertova, P. p. m. a. m. e. a. Re-engineering graduate skills - a case study. European

Conference Session

SE Curriculum and Course Management

Collection

2008 Annual Conference & Exposition

Authors

Joseph Clifton, University of Wisconsin-Platteville; Rob Hasker, University of Wisconsin-Platteville; Mike Rowe, University of Wisconsin-Platteville

Tagged Divisions

Software Engineering Constituent Committee

all students will attend class on the day the course surveysare administered; however, we are considering web-based alternatives to attempt to get 100%.All measurements are normalized to the range 1 - 5, with five meaning “good” and one meaning“poor”. These are then aggregated and are entered into the Assessment Results spreadsheet. Aportion of the spreadsheet for fall 2006 is shown below. Ave % 5's % 4's % 3's % 2's % 1's 5's 4's 3's 2's 1's Comments Page 13.1411.6 B.1.a 3.5 23.5 17.6 47.1 11.8 0.0 4 3 8 2 0 Req - SE 4330 Assess B.1.b 4.6 56.3 43.8

Conference Session

Undergraduate Spacecraft Design II

Collection

2007 Annual Conference & Exposition

Authors

Lawrence Boyer, St. Louis University; Krishnaswamy Ravindra, St. Louis University; John George, St. Louis University; Kyle Mitchell, St. Louis University

Tagged Divisions

Aerospace

during burnsc = total distance covered during coasting∆s = distance covered during one iteration of coasting portionΣ∆s = total distance covered during coastingt/c = thickness ratio of finsV = velocityρ = air density, sea levelIntroduction:Most aerospace engineering curriculums contain an introductory course that introduces a Page 12.897.2sophomore student to the world of aerospace. Generally this course tends to be a broadintroduction to terminology, basic aerodynamics, performance, propulsion and structures. Insome programs, a hands-on project is assigned to the students to make the course moreinteresting and provide

Conference Session

Improving ME instructional laboratories

Collection

2006 Annual Conference & Exposition

Authors

Jed Lyons, University of South Carolina

Tagged Divisions

Mechanical Engineering

determined how piston displacement depends on crankangle in a single-cylinder internal combustion engine and compared their results to a theoreticalequation. A schematic of a piston, connecting rod and crank is shown in Figure 2. Assumingthat the crank and connecting rod have perfect pin connections, it can be shown by trigonometrythat the distance between the crank axis and the piston pin axis (s) is given by s = a cos + (L2 – a2 sin2 )1/2 (1)when the connecting rod length (L) and the crank radius (a) are known. These values, and thedistance from the piston pin axis to the top of the piston (x), are measured by the laboratoryinstructor and given to the students before lab. Figure 2

Conference Session

Collaborative & New Efforts in Engineering Education

Collection

2006 Annual Conference & Exposition

Authors

Joao Vinhas, Politecnico de Viseu; Joao Paiva, Politecnico de Viseu

Tagged Divisions

International

shown in the following table as afunction of time. Page 11.667.7Table 1. Particle experimental values of position versus time for Example 1. Time t (s) Position s (m) 0 2 1 5 2 9 3 5 4 -1Students are supposed to calculate the scalar displacement between the instants t = 1 s and t= 4 s. Students who try to solve this very

Conference Session

ASEE Multimedia Session

Collection

2003 Annual Conference

Authors

Carol Mullenax

very small number of upperclass transfer students are accepted eachyear, either individually or through formal 3-2 programs established with liberal arts schools.The size of the graduating class at Caltech has averaged 193 over the past 30 years. Admissionsnumbers are generally quite similar. Consequently, we are dealing with small numbers.The Caltech Admissions staff is small, but potent. There is a segment called UndergraduateAdmissions Support (UAS) which coordinates alumni volunteer efforts to help with undergraduateadmission. UAS was started in the mid-70’s. None of the current staff date back to the program’sinception, but they feel that the timing (coinciding with the initial admittance of women to theInstitute) is not mere coincidence

Conference Session

Inservice Teacher Engineering Education

Collection

2005 Annual Conference

Authors

Kathleen Crowe; Kris Wood; Richard Crawford; Daniel Jensen

provide insight into how people learn 13, 14.The goal is to create a learning environment that facilitates effective learning for all MBTI types.Figure 2 below gives an overview of the MBTI designations. Manner in Which a Person Interacts With Others E Focuses outwardly. Gains energy from others. Focuses inwardly. Gains energy from cognition I EXTROVERSION INTROVERSION Manner in Which a Person Processes Information S Focus is on the five senses and experience. Focus is on possibilities, use, big picture. N SENSING

Conference Session

Design and Manufacturing Experiences II

Collection

2004 Annual Conference

Authors

W. Bowman

. Power Available 1.600 1.400 1.200 1.000 Power Available [W] 0.800 Power Available 0.600 0.400 0.200 0.000 0.000 2.000 4.000 6.000 8.000 10.000 12.000 14.000 16.000 Wind Speed [m/s] Figure 2: Power Available Curve for the DC

Conference Session

Measuring Perceptions of Engineering

Collection

2005 Annual Conference

Authors

Christine Cunningham; Cathy P. Lachapelle; Anna Lindgren-Streicher

guide the field [4-6].One of stumbling blocks that has been identified is that scholars have not yet come to consensuson the specific concepts and process understandings that comprise technological literacy [7].More clarification at the national, state, district, or project level could provide some guidelines.However, we have chosen to begin to investigate conceptions at a much more basic level;specifically, what do students think engineering and technology are? One could argue that forany person to be technologically literate, s/he must first have some idea of what engineering andtechnology are. Though they are surrounded by the products of engineering in our everydaylives, students and the general public generally don’t understand what

Collection

2000 Annual Conference

Authors

George A. Perdikaris

monitored by an incremental encoder(MPG), which returns change of position (i.e., velocity) per sampling time T; also, the Page 5.449.2controller output is communicated to the analog plant via a DAC.A motor drive plant is often modeled by a double-integrator transfer function Θ( s ) Km Gp(s) = = 2 (1) M ( s) swhere the analog position plant gain Km depends on motor drive parameters. If the DAC andMPG gains Kda and Kdt are taken into consideration, the digital position plant

Conference Session

ASEE Multimedia Session

Collection

2002 Annual Conference

Authors

Abhijit Nagchaudhuri

, 1999, CD ROM. 11. Kadel, S., and Keehner, J.A. (eds.), Collaborative Learning : A Sourcebook for Higher Education. National Center of Postsecondary Teaching, Learning, and Assessment, Pennsylvania State University, University Park, PA , 1994. 12. Brown, G., and Pendleberry, M., Assessing Active Learning, Parts 1 and 2, CVCP Universities; Staff Development and Training Unit, University House, Sheffield, UK, 1992.ABHIJIT NAGCHAUHDURIAbhijit Nagchaudhuri is currently an Associate Professor in the Department of Engineering and AviationSciences at University of Maryland Eastern Shore. Prior to joining UMES he worked in Turabo Universityin San Juan , PR as well as Duke University in Durham North Carolina as Assis

Collection

2001 Annual Conference

Authors

Leo Smith; Hisham Alnajjar; Donald Leone; Mohammad Saleh Keshawarz; Ladimer Nagurney; Devdas Shetty

of skills namely, ‘Engineering skills’,‘Communication Skills’, ‘Computer Skills’, ‘Resource Utilization skills’, ‘Management Skills’,and ‘Connection and linkage to other courses’. A S S ES S M EN T R ES U L T S 5 4 .0 8 4 .1 2 4 .3 2 4 .1 2 4 .0 3 3 .7 4 4 3 2 1 EN G G . S K IL L S CO M M. S K IL L S CO M P. S K IL L S RES O U RCE MG MT. S K IL L S CO NNECTIO N UTIL S N. S K IL L S TO O THER

Collection

2000 Annual Conference

Authors

Patricia Davies; Leah H Jamieson; Laura A Guedelhoefer; Edward J. Coyle; James D. Jones

displayed on the chart below. Page 5.265.5 5 M a le F e m a le 4 .5 C a u c a s ia n M in o ritie s 4

Collection

1998 Annual Conference

Authors

S.A. McClellan; J.W. Goode

explosive growth of theInternet and World-Wide-Web, the effects of these technologies are increasingly presentin routine settings. Consequently, the exposure to “quantized” and “compressed”information is very high whereas exposure to the theoretical underpinnings and a firmunderstanding of the associated tradeoffs is very low. We begin here with a briefintroduction to the theory surrounding both the mechanics of speech production and themathematical modelling of vocalization, including basic quantization and prediction.The dryness of the mathematical development is then nicely contrasted with thereal-time demonstrations of speech coding which rely on a participant’s vocalizations. II. H U M A N S PEECH AND L INEAR P R E D I C

Conference Session

Computing and Information Technology Division (CIT) Technical Session 1

Collection

2024 ASEE Annual Conference & Exposition

Authors

Kwansun Cho, University of Florida; Umer Farooq, Texas A&M University; Saira Anwar, Texas A&M University

Tagged Divisions

Computing and Information Technology Division (CIT)

is for novice programmersAbstractIn this work-in-progress paper, the emphasis is to understand the perceptions about whichlanguage should be the first programming language. Computer programming is a fundamentalskill for novice engineers. However, over time, multiple programming languages have emergedand are being used as the first language for students. While in modern times, many schoolsaround the globe, particularly in the USA, consider Python’s syntax simplicity and versatility asa way to go, other places and traditional computer scientists consider C++’s efficiency as theirchoice. Similarly, many engineering schools introduce MATLAB as the first programminglanguage. While these decisions are made at the

Conference Session

Engineering Inclusivity: Challenging Disparities and Cultivating Resilience in Education

Collection

2024 ASEE Annual Conference & Exposition

Authors

Austin Morgan Kainoa Peters, Purdue University; Alice L. Pawley, Purdue University; Stephanie Masta, Purdue University; Darryl Dickerson, Florida International University; Matthew W. Ohland, Purdue University

Tagged Divisions

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

assistant professor in the Department of Mechanical and Materials Engineering at Florida International University. Dr. Dickersonˆa C™s research agenda contains two interconnected strands: 1) systematic investigatiDr. Matthew W. Ohland, Purdue University Matthew W. Ohland is the Dale and Suzi Gallagher Professor and Associate Head of Engineering Education at Purdue University. He has degrees from Swarthmore College, Rensselaer Polytechnic Institute, and the University of Florida. His research on the longitudinal study of engineering students and forming and managing teams has been supported by the National Science Foundation and the Sloan Foundation and his team received for the best paper published in the Journal of

Conference Session

Educational Research and Methods Division (ERM) Technical Session 11

Collection

2024 ASEE Annual Conference & Exposition

Authors

Jeffrey Stransky, Rowan University; Prateek Shekhar, New Jersey Institute of Technology

Tagged Topics

Diversity

Tagged Divisions

Educational Research and Methods Division (ERM)

improveretention, researchers have applied asset-based perspectives to studying retention of marginalizedstudents. This approach often emphasizes the role of social capital [1], [11] and socializers [12]–[14] as primary drivers of motivation to pursue STEM education and careers. This present paperbegins to unpack the unique relationship between socializers and the decision students atminority serving institutions (MSIs) make to pursue STEM. We report on the experiences ofstudents gathered using qualitative methods and examined through the lens of expectancy valuetheoretical framework.Theoretical Framework: Expectancy-ValueMotivation to pursue a career in STEM can be modeled through Eccles et al.'s Expectancy-Valuetheory (EV) [15]. EV establishes a direct

Collection

1997 Annual Conference

Authors

Glynn P. Adams; Ing-Chang Jong

of the coupler during the animation. The linkage presentedhere is a crank-rocker mechanism, which can be assembled in a colinear configuration. Thislinkage was selected because of the interesting nature of the coupler link space centrodeand the motion of the output, link. The position solution for the linkage is obtained with a.Newton-Ra.phson method and the use of kinematic coefficients. The details of this approachare presented as is the specific MATLAB code required to produce the position solutionand the animation. IntroductionOne of the main impediments to learning dynamics of mechanisms is the visualization ofthe mechanism motion. Several commercially available software p a c k a g e s such as

Conference Session

Signal Processing Education

Collection

2010 Annual Conference & Exposition

Authors

Cameron Wright; Thad Welch; Michael Morrow

Tagged Divisions

Computers in Education

Figure 3: A plot showing the z-plane annotated for discussing bandpass sampling.dents that allows them to evaluate Equation (1) in a way that promotes exploration and “what if” thinking.A simple m-file that provides this capability is shown in Listing 1, with an example output given in Figure 4for the bandpass signal parameters from Figure 2(a). Listing 1: M ATLAB program to evaluate valid sampling frequencies for bandpass sampling.f u n c t i o n vFs = bp samp ( fu , B )% vFs=bp samp ( f u , B )%% C r e a t e a s e t o f min and max v a l i d s a m p l e f r e q u e n c i e s% f o r bandpass sampling .% For Q= f u / B ,% 2B (Q / n ) <= Fs <= 2B ( ( Q− 1 ) / n −1))% where n i s an i n t e g e r s u c h t h a t 0> bp_samp