Paper ID #19263Exploring the Post-graduation Benefits of High-Impact Practices in Engi-neering: Implications for Retention and Advancement in IndustryTrevion S. Henderson, University of Michigan Trevion Henderson is a doctoral student in the Center for Higher and Postsecondary Education (CSHPE) at the University of Michigan. He recently earned his master’s degree in Higher Education and Student Affairs at The Ohio State University while serving as a graduate research associate with the Center for Higher Education Enterprise. Trevion also hold’s a Bachelor’s degree in Computer Science and Engineer- ing from The Ohio State
Paper ID #20488The Relationship between Engineering Students’ Self-efficacy Beliefs and TheirExperience Learning Computer Programming: A Sequential ExplanatoryMixed-Methods InvestigationMs. S. Zahra Atiq, Purdue University, West Lafayette S. Zahra Atiq is a PhD student at the School of Engineering Education at Purdue University, West Lafayette. Her research interests include: computer science education specifically on teaching computer programming to undergraduates and how to improve their learning experiences. She is also interested in understanding student behaviors and performance in online learning environments specifically
Paper ID #18442A Systems Approach to Analyzing Design-Based Research in Robotics-FocusedMiddle School STEM Lessons through Cognitive ApprenticeshipDr. S. M. Mizanoor Rahman, New York University Mizanoor Rahman received his Ph.D. degree in Mechanical Engineering from Mie University at Tsu, Japan in 2011. He then worked as a research fellow at the National University of Singapore (NUS), a researcher at Vrije University of Brussels (Belgium) and a postdoctoral associate at Clemson University, USA. He is currently working as a postdoctoral associate at the Mechanical and Aerospace Engineering Department, NYU Tandon School of
Paper ID #18386Developing an Instrument to Understand the Social-Structural Integration ofDiverse StudentsMr. Nelson S. Pearson, University of Nevada, Reno Nelson Pearson is an Ph.D. student at the University of Nevada, Reno. His research interest includes, social networks and the integration of diverse populations, engineering culture as well as engineering pedagogy. His education includes a B.S. and M.S. in Civil Engineering from the University of Nevada, Reno.Dr. Allison Godwin, Purdue University Allison Godwin, Ph.D. is an Assistant Professor of Engineering Education at Purdue University. Her research focuses what
Paper ID #20017Characterizing Indicators of Students’ Productive Disciplinary Engagementin Solving Fluids Mechanics ProblemsMs. Jessica E. S. Swenson, Tufts Center for Engineering Education and Outreach Jessica Swenson is a graduate student at Tufts University. She is currently pursuing a Ph.D. in mechanical engineering with a research focus on engineering education. She received a M.S. from Tufts University in science, technology, engineering and math education and a B.S. from Northwestern University in me- chanical engineering. Her current research involves examining different types of homework problems in mechanical
women in engineering degree programs and effective pedagogy in undergraduate engineering curriculum.Dr. James J. Pembridge, Embry-Riddle Aeronautical Univ., Daytona BeachDr. Yosef S. Allam, Colorado School of Mines Yosef Allam is a Teaching Associate Professor in the EPICS first-year engineering program at the Col- orado School of Mines. Prior to joining Mines, he was an Assistant Professor in the Engineering Funda- mentals Department at Embry-Riddle Aeronautical University and an Affiliate Director for Project Lead The Way in Florida, as well as an Instructor in the First-Year Engineering Program at The Ohio State University. He graduated from The Ohio State University with B.S. and M.S. degrees in Industrial and
Graphical Communication. Her research interests involve the retention of women in engineering degree programs and effective pedagogy in undergraduate engineering curriculum.Dr. Yosef S. Allam, Colorado School of Mines Yosef Allam is a Teaching Associate Professor in the EPICS first-year engineering program at the Col- orado School of Mines. Prior to joining Mines, he was an Assistant Professor in the Engineering Funda- mentals Department at Embry-Riddle Aeronautical University and an Affiliate Director for Project Lead The Way in Florida, as well as an Instructor in the First-Year Engineering Program at The Ohio State University. He graduated from The Ohio State University with B.S. and M.S. degrees in Industrial and
inclusivity in engineering education. In particular, she is interested in engineering e-learning and the dis- covery of traversable engineering pathways for nontraditional, low-income, first generation, and veteran undergraduates.Mr. Joel Raymond HoodMr. Derrick S. Harkness, Utah State University I am currently a graduate student at Utah State University working on a Master’s degree in Mathematics with an emphasis in Education. c American Society for Engineering Education, 2017 WIP: Methodological Considerations for Constructing NontraditionalStudent Personas with Scenarios from Online Forum Usage Data in CalculusIntroductionPersonas and scenarios each gained popularity as design tools within the fields
)Mr. Ryan McCullough, Colorado State University Ryan McCullough is a B.S./M.S. student in Electrical Engineering at Colorado State University. He currently has a B.Ed. from the University of Toledo and worked as a teacher for five years before returning to get a degree in electrical engineering in 2014. He is working as a research assistant in both engineering education and MRI RF coil design.Mr. Pranav S. Athalye, Colorado State University Pranav S. Athalye is a PhD student at Colorado State University, Electrical and Computer Engineering Department. He works as a teaching assistant with Dr. Branislav Notaros as the instructor for Elec- tromagnetics courses. His graduate research includes RF coil designing for
, PA. Her research interests include iden- tity development through co and extra-curricular experiences for engineering students.Dr. Courtney June Faber, University of Tennessee Courtney is a Research Assistant Professor and Lecturer in the College of Engineering Honors Program at the University of Tennessee. She completed her Ph.D. in Engineering & Science Education at Clemson University. Prior to her Ph.D. work, she received her B.S. in Bioengineering at Clemson University and her M.S. in Biomedical Engineering at Cornell University. Courtney’s research interests include epistemic cognition in the context of problem solving, researcher identity, and mixed methods.Dr. Marian S. Kennedy, Clemson University
non-technical people learn and apply a design process to their work. He is interested in the intersection of designerly epistemic identities and vocational pathways. Dr. Lande is the PI/co-PI on NSF-funded projects focused on engineering doing and making, citizen science and engineering outreach, and ”revolutionizing” engineering education. He has also been an instructor and participant in the NSF Innovation Corps for Learning program. He re- ceived his B.S in Engineering (Product Design), M.A. in Education (Learning, Design and Technology) and Ph.D. in Mechanical Engineering (Design Education) from Stanford University.Dr. Shawn S. Jordan, Arizona State University, Polytechnic campus SHAWN JORDAN, Ph.D. is an
Paper ID #18098The RED Teams as Institutional Mentors: Advice from the First Year of the”Revolution”Dr. Jeremi S. London, Arizona State University, Polytechnic campus Dr. Jeremi London is an Assistant Professor of Engineering at Arizona State University. She holds B.S. and M.S. degrees in Industrial Engineering and a Ph.D. in Engineering Education, all from Purdue Uni- versity. Prior to her PhD, she worked in quality assurance and logistics roles at Anheuser-Busch and GE Healthcare, where she was responsible for ensuring consistency across processes and compliance with federal regulations. For four consecutive summers
their work. He is interested in the intersection of designerly epistemic identities and vocational pathways. Dr. Lande is the PI/co-PI on NSF-funded projects focused on engineering doing and making, citizen science and engineering outreach, and ”revolutionizing” engineering education. He has also been an instructor and participant in the NSF Innovation Corps for Learning program. He re- ceived his B.S in Engineering (Product Design), M.A. in Education (Learning, Design and Technology) and Ph.D. in Mechanical Engineering (Design Education) from Stanford University.Dr. Shawn S. Jordan, Arizona State University, Polytechnic campus SHAWN JORDAN, Ph.D. is an Assistant Professor of engineering in the Ira A. Fulton Schools of
Science and Engineering at North Carolina State University where she has served as the Director of Undergraduate Programs since 2011. Her research focuses on the intersection of science and engineering identity in post-secondary and graduate level programs.Dr. Monique S. Ross, Florida International University Monique Ross holds a doctoral degree in Engineering Education from Purdue University. She has a Bachelor’s degree in Computer Engineering from Elizabethtown College, a Master’s degree in Computer Science and Software Engineering from Auburn University, eleven years of experience in industry as a software engineer, and three years as a full-time faculty in the departments of computer science and engineering
electrical at higherrates than traditional students (McNeil, Ohland, & Long, 2016). This paper focused on thestickiness measure for NTS students, and other statistical tests of prediction were outside thescope of this paper. Further research is needed to explore why NTS’ stickiness follows adifferent trend than traditional students. 5 ReferencesAlvord, C. J. (2004). First-time freshman graduation rates Fall 1980-Fall 1997 entering classes (Biennial Report). Retrieved from http://ms7.dpbwin2k.cornell.edu/documents/ 1000024.pdfAstin, A. W., & Astin, H. S. (1992). Undergraduate science education
assignment was due for MAE 434W,which could have influenced questions 8 and 11. Based on the instructors’ feedback, Expertizawas updated between semesters and the scores from the spring semester suggest the studentsfound the newly adjusted system easier to use.Table 2. Average Survey Results per Class from the Fall and Spring Semesters. Survey Question Fluid Mechanics Capstone Design 1. The reviews I received addressed F 3.41 F 3.63 the questions/concerns I had about S 3.79 S 3.43 my work. 2. The reviews I received gave me F 3.50 F 3.63 new insight into my work. S 3.80
currently working at a start-up andperceives the climate to be much more positive than P0’s previous employer (a largecompany). P0 attributes this difference to the fact that it is a smaller company, and thuspeople are more apt to rely on and get to know each other.The interviewees used a variety of approaches to deal with their situations. P0 “never feltconnected with the Black [company employees]” and eventually left that company for asmall start-up. P1 did not expect to feel connected when first hired. Instead, P1’s approachwas to focus on the technical aspects of the job and “when I want to see Black folks I justdrive home.” P5 has decided,that I’m not pushing the envelope, I’m just sitting there collecting my paycheck…The less I dothe more
systems, conducting research inengineering education domains focused on interaction-dominant phenomena, and meeting critical datacollection and analysis needs, complex systems research can provide important insights for theengineering education community. ReferencesAnylogic (2016) Retrieved from: http://www.anylogic.com/Benson, L., Kirn, A., & Faber, C. (2013, June). CAREER: Student motivation and learning in engineering. In ASEE Annual Conference Proceedings.Berggren, K. F., Brodeur, D., Crawley, E. F., Ingemarsson, I., Litant, W. T., Malmqvist, J., & Östlund, S. (2003). CDIO: An international initiative for reforming engineering education. World Transactions on Engineering and
., Ciarallo, F.W., Klingbeil, N.W. (2014). Developing the Academic Performance- Commitment Matrix: How measures of objective academic performance can do more than predict college success. Proceedings 121st ASEE Annual Conference and Exposition, Indianapolis, IN, June 2014.Brown, S. D., Tramayne, S., Hoxha, D., Telander, K., Fan, X., & Lent, R. W. (2008). Social cognitive predictors of college students’ academic performance and persistence: A meta- analytic path analysis. Journal of Vocational Behavior, 72(3), 298-308.Burnham, J.R. (2011). A case study of mathematics self-efficacy in a freshman engineering mathematics course. (unpublished master’s thesis). Washington State University, Pullman, WA.Connor, M. C., & Paunonen, S. V
Education, Washington, DC: ASEE, 2012.6 See https://www.nsf.gov/pubs/2014/nsf14602/nsf14602.htm7 Douglas, E., private communication, January 31, 2017.8 Jordan, S. and M. Lande, “Additive innovation in design thinking and making,” International Journal of Engineering Education, 32(3B), pp. 1438-1444, 2016.9 McKenna, A., N. Kellam, M. Lande, S. Brunhaver, S. Jordan, J. Bekki, A. Carberry, and J. London, “Instigating a Revolution of Additive Innovation: An Educational Ecosystem of Making and Risk Taking,” 2016 ASEE Annual Conference & Exposition, New Orleans, LA, June 2016.10 Kellam, N., B. Coley, and A. Boklage, “Story of change—Using experience-based critical event narrative analysis to understand an engineering program’s
. doi: 10.1002/sce.210075. Baker, D., Krause, S., Yaşar, ş., Roberts, C., & Robinson-Kurpius, S. (2007). An intervention to address gender issues in a course on design, engineering, and technology for science educators. Journal of Engineering Education, 96(3), 213-226. doi: 10.1002/j.2168-9830.2007.tb00931.x6. Adelman, C. (1998). Women and men of the engineering path: A model for analyses of undergraduate careers. (Report No. PLLI-98-8055). Washington, DC: Office of Educational Research and Improvement, U.S. Department of Education Retrieved from ERIC database. (ED419696).7. Bucciarelli, L. L. (2003). Engineering philosophy. Delft, The Netherlands: DUP Satellite.8. Su, R., Rounds, J., &
– .47 .63 .45 .42 .41 .00 3. Perceived Usefulness .33 .42 – .66 .75 .70 .72 .12 4. Perceived Ease of Use .44 .58 .65 – .69 .70 .69 .09 5. ILTs Compatibility .23 .38 .73 .66 – .73 .79 .10 6. Attitudes toward ILT s .30 .38 .67 .71 .70 – .78 .11 7. ILTs Behavioral Intentions .22 .33 .69 .66 .77 .78 – .07 8. GPA -.04 .04 .13 .13 .11 .12 .09 – Note. Parametric (i.e., Pearson) correlations are below the primary diagonal and non
for Work Avoid in either comparison.It is interesting to observe significant decreases in Expectancy between both 2013 and 2016 andbetween 2014 and 2016, with a medium effect size for the decrease between 2014 and 2016.Student perceptions about their abilities to complete tasks in their engineering courses appear todecrease after their first year, possibly due to the challenges of upper level courses with whichthey are confronted.Table 2: Summary of mean (standard deviation) values for all factors for each year and thematched pairs t-test or Signed-Rank test results for comparisons, including the test statistic t(n-1)or S, respectively, the sample size n, the p-value, and the effect size d for significant results.Factor scores are on a scale
intendedmeaning of each dimension would be measured. Based on the difficulties measuring costreported in prior work,20-23 cost items were generated along two different types of cost, task effortcost (i.e., time spent) and emotional/psychological cost,21 to increase the likelihood of producinga factor measuring some aspect of cost. All STV items were displayed as a single scale whichasked respondents, “Please indicate the extent to which you agree or disagree to the followingstatements about your first position after graduating with your bachelor’s degree(s),” on a five-point Likert (bipolar) scale, from 0=“strongly disagree” to 4=“strongly agree”. Nunnally andBernstein26 recommend the use of Likert scales because they are easy to create, produce
participation the faculty at ASU who are members of the affinity groups.Finally, we thank the The Polytechnic School at ASU and the evaluation team for supportingdata collection and participation in this research. This work is supported by the National ScienceFoundation Grant 1519339. Any opinions, findings, and conclusions or recommendationsexpressed in this material are those of the author(s) and do not necessarily reflect the views ofthe National Science Foundation.ReferencesBolman, L. G., & Deal, T. E. (1991). Leadership and management effectiveness: A multi-frame, multi-sector analysis. Human Resource Management1, 30(4), 509–34.Borrego, M. & Henderson, C. (2014). Increasing the use of evidence-based teaching in STEM education: A
underrepresented minorities in engineering. Nonetheless, a story is not completeuntil it integrates not only some of the characters, but also their environment, history, beliefs,values, ways of knowing, doing and being. Similarly, as part of the engineering educationcommunity, we must add more factors to this story – the stories of struggle, subjugation, andoppression.Bibliography 1. Blaisdell, S. (2006). Factors in the Underrepresentation of Women in Science and Engineering: A Review of the Literature. Women in Engineering ProActive Network. 2. Cohen, C. C. D., & Deterding, N. (2009). Widening the net: National estimates of gender disparities in engineering. Journal of Engineering Education, 98(3), 211-226. 3. Beddoes, K
in college, but notin your major? 5. Tell me about how doing PBSL in your major has affected you personally, especially inthe way you describe yourself to others. We summarized four domains based on the interviews and transcription as follows. Due tothe page limit, we only excerpt what they said corresponding to domain 4 which gives uspreliminary data related with question 1. Domain 1: What it’s like to be in the program—relationships amongst students Domain 2: What type/s of people are like to be in the program—people types Domain 3: What type/s of people are like to be in the program—type/s of yourself Domain 4: What impacts of PBSL on you are—changes of your personality or identity Student A participated in PBSL 4
recommendations expressed in this material are those of the author(s) and do notnecessarily reflect the views of the National Science Foundation.References1. Borkowski, J. G., Carr, M., & Pressley, M. (1987). “Spontaneous” strategy use: Perspectives from metacognitive theory. Intelligence, 11(1), 61-75.2. Bransford, J. D., Brown, A., & Cocking, R. (1999). How people learn: Mind, brain, experience, and school. Washington, DC: National Research Council.3. Chopra, S. K., Shankar, P. R., & Kummamuru, S. (2013, August). MAKE: A framework to enhance metacognitive skills of engineering students. In Teaching, Assessment and Learning for Engineering (TALE), 2013 IEEE International Conference on (pp. 612-617). IEEE.4. Cross, D. R., &
79 16 M Private R2 INTRO 140 17 F Private M1 INTRO 123* Carnegie classifications: R1 = Doctoral Universities: Highest Research Activity; R2 = Doctoral Universities: Higher Research Activity; M1 = Master's Colleges and Universities: Larger Programs; M3 = Master's Colleges and Universities: Smaller Programs; B-A/S = Baccalaureate Colleges: Arts & Sciences Focus; and B-DIV = Baccalaureate Colleges: Diverse Fields** Course disciplines: CBME = Chemical/Biomedical Engineering; CIVIL = Civil and Environmental Engineering; DESIGN = Design; EECS = Electrical Engineering/Computer
Materials Science Engineering from Alfred University, and received his M.S. and Ph.D., both from Tufts University, in Chemistry and Engineering Education respectively. Dr. Carberry was previously an employee of the Tufts’ Center for Engineering Education & Outreach and manager of the Student Teacher Outreach Mentorship Program (STOMP).Dr. Trevor Scott Harding, California Polytechnic State University, San Luis Obispo Dr. Trevor S. Harding is Professor of Materials Engineering at California Polytechnic State University where he teaches courses in materials design, biopolymers, and nanocomposites. Dr. Harding has served as PI of a multiinstitutional effort to develop psychological models of the ethical decision making of