measurement of engineering identity was accomplished using an adapted version of Godwinet al.’s (2016) measure of identity. Godwin et al. concludes that an engineering student’sengineering identity is a function of four attitudes relating to interest, performance, recognitionand agency. Interest is the student’s innate attraction to the subject material surroundingengineering, such as math, science and physics. Performance is an academic self-efficacyconstruct measuring how much a student believes in their ability to positively perform inacademically in engineering coursework. Recognition is how a student believes they arerecognized as an engineer, particularly by meaningful others such as parents or professors.Finally, agency or as Godwin et al
University. Special acknowledgment is given to Dr. Amanda Goodson, Founder ofAmanda Goodson Global. She served as the Professional Development Consultant anddeveloped and implemented the curriculum for this PDW.Bibliography 1. Emmer, M. J. and Brunhoeffer, G. C. F. Knowledge and attributes of forecasting index: Self-assessment for graduating Construction Management students. In: Proceedings of the 2015 Associated Schools of Construction Annual International Conference. 2015. http://www.ascpro.ascweb.org/chair/paper/CERT385002015.pdf. Accessed March 15, 2017. 2. Multon, K. D., Brown, S. D., and Lent, R. W. Relation of self-efficacy beliefs to academic outcomes: A meta-analytic investigation. Journal of Counseling
University of Michigan-Dearborn Advancement ofTeaching and Learning Fund and the NSF Award #1245036 Collaborative Education: Building aSkilled V&VF Community. We would like to thank Ms. Raminderdeep Randhawa who workedas Research Assistant on this project and Ms. Navin Tama who worked as a Graduate StudentInstructor for the fall 2016 offering of CIS 375. They gave generously of their time and energy tothis project.Bibliography1. Branch R. (2010): Instructional Design: The ADDIE Approach, Springer, 2010.2. Ardis, M., Chenoweth, S. and Young, F. (2008): “The ‘Soft’ Topics in Software Engineering Education”, Proceedings of 38th Annual Frontiers in Education Conference (Vol. 1, Oct 2008), IEEE Press, Saratoga Springs, NY, 2008, pp. F3H1
appointment of five lead engineers to serve as project mentors for theprogram. These project mentors selected ten community college students from a shortlist of 20candidates provided by two members of the RU team (lead principal investigator and graduatestudent researcher) who conducted 34 interviews from an original pool of 58 applicants. Originalapplicants represented a range of individual differences: 26% female, 55% underrepresentedethnic minorities; 57% first generation; 27% veterans; 62% low-income; 5% students with1This research was supported by, or in part by, the U. S. Office of Naval Research under awardnumber N00014-15-1-2438.disabilities2. The final selection of ten from this diverse pool echoed such diversity: two females,five minorities
applications of positively impacting others areeasily connected in the biomedical engineering field. Nearly 40% of biomedical engineers arewomen. Although males are still the majority in this field, biomedical engineering is one of themore popular engineering fields among women.15 The final major change to our program fornext year is our goal to interview participants about their experiences. We will utilize this as away for students to reflect on their experiences as well as a way for us to receive more rich dataabout the short-term impacts of our program.Resources[1] F. Halpern, D., Aronson, J., Reimer, N., Simpkins, S., R. Star, J., & Wentzel, K. (2007,September 1). Encouraging Girls in Math and Science. Retrieved December 2, 2014, fromhttp
Student Affairs, Washington, DC: Author.2. Schneider, C.J. and Miller, R. (2005). Liberal education outcomes: A preliminary report onstudent achievement in college, Association of American Colleges and Universities, Washington.DC.3. Baxter Magolda, M.B. (2001). Making their own way: Narratives for transforming highereducation to promote self-development. Stylus Publishing.4. Parks Daloz, L.A., Keen, C.H., Keen, J.P. and Daloz Parks, S. (1996). Common fire: lives ofcommitment in a complex world. Beacon.5. Paul, R. and Elder, L. (2010) The miniature guide to critical thinking: Concepts and Tools,Foundation for Critical Thinking Press.6. Paul, R., Niewoehner, R. and Elder, L. (2006). The thinker’s guide to engineering reasoning,Foundation Critical
.[7] Kotche, M., and S. Tharp, Interdisciplinary Medical Product Development Senior Capstone Design, Proceedings of the 122nd ASEE Annual Conference and Exposition, Seattle, WA, June 14-17, 2015.[8] Redekopp, M., Raghavendra, C., Weber, A., Ragusa, G., and T. Wilbur, A Fully Interdisciplinary Approach to Capstone Design Courses, Proceedings of the 116th ASEE Annual Conference and Exposition, Austin, TX, June 14-17, 2009.[9] Seaward, G., Converting Single Disciplinary Capstone Projects to Interdisciplinary Experiences, Proceedings of the 108th ASEE Annual Conference and Exposition, Albuquerque, NM, June 24-27, 2001.[10] Sirinterlicki, A., Interdisciplinary Capstone Projects, Proceedings of the 121st ASEE Annual
formative assessments to favordifferent learning styles (Wang, Wang et al. 2006). Both learning style and formativeassessment strategy significantly affected student achievement, though, consistent with Pashler etal.’s conclusion, the interaction between these factors was not significant. Additionally, as thisstudy was performed with a web-based middle-school biology course, a gap remains with regardto undergraduate engineering education.As the primary motivation for this study is increasing the diversity of the engineering graduatesthat colleges and universities prepare for the workforce, some evidence demonstrates thatvarying teaching approaches to favor a multitude of learning styles may aid in achieving thatparticular end. A validation study of
realobject. Based on free responses it can be said that some students appreciated the link betweentheory and practice. The activity has gained interest at the author’s institution where two additional instructorshave adopted it. It is anticipated that it will evolve as a result of broader deployment.Acknowledgements The author acknowledges the James Madison University Quality Collaborative project,funded by Lumina Foundation.References[1] S. D. Sheppard and B. H. Tongue, Statics Analysis and Design of Systems in Equilibrium (revisd edition), Danvers, MA: John Wiley & Sons, Inc., 2007.[2] F. P. Beer, E. R. Johnston, Jr., D. F. Mazurek, P. J. Cornwell and B. P. Self, Vector Mechanics for Engineers (11th edition), New York, NY: McGraw
Engineering Programs, 2016-2017 (p. 25). Baltimore, MD.Barron, B. J. S., Schwartz, D. L., Vye, N. J., Moore, A., Petrosino, A., Zech, L., & Bransford, J. D. (1998). Doing with Understanding: Lessons from Research on Problem- and Project- Based Learning. The Journal of the Learning Sciences, 7(3/4), 271–311.Blumenfeld, P. C., Soloway, E., Marx, R. W., Krajcik, J. S., Guzdial, M., & Palincsar, A. (1991). Motivating Project-Based Learning: Sustaining the Doing, Supporting the Learning. Educational Psychologist, 26(3/4), 369.Boaler, J., & Greeno, J. G. (2000). Identity, Agency, and Knowing in Mathematics Worlds. In J. Boaler (Ed.), Multiple Perspectives on Mathematics Teaching and Learning (pp. 171– 200
gained.References1. Bandura, A. (1982). Self-Efficacy Mechanism in Human Agency. American Pyschologist, 37(2), 122-147.2. Basawapatna, A., Repenning, A., & Koh, K. H. (2015). Closing The Cyberlearning Loop. Proceedings of the 46th ACM Technical Symposium on Computer Science Education - SIGCSE '15, (pp. 12-17).3. Bean, N., Weese, J. L., Feldhausen, R., & Bell, R. (2015). Starting From Scratch: Developing a Pre- Service Teacher Program in Computational Thinking. Frontiers in Education.4. Bell, R. S. (2014). Low Overhead Methods for Improving Capacity and Outcomes in Computer Science. Manhattan, KS: Kansas State University.5. Brennan, K., & Resnick, M. (2012). Using artifact-based interviews to study the
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, sustainable materials, and polymeric materials. Dr. Harding is PI on several educational research projects including the psychology of ethical decision making and promoting the use of reflection in engineering education. He serves as Associate Editor of the journals Advances in Engineering Education and International Journal of Service Learning in Engineering. Dr. Harding has served numerous leadership positions in ASEE including division chair for the Materials Division and the Community Engagement Division. Dr. Harding received
division grades, collectively andindividually, do not predict upper-division design grades, we still require a minimum level ofexposure to the math, science, and, engineering concepts without which students are doingdesign outside of an engineering context. These results may also be indicative of the relationshipfor traditional capstone design experiences. Additional research is necessary to see if theseeffects hold true in that context. The implications for the study are that additional information inprogram applications must be included to effectively predict a student’s performance.References 1. S. Singer and K. A. Smith, “Discipline-Based Education Research: Understanding and Improving Learning in Undergraduate Science and
strong data that could indicate best practices, and which do not? Format of Final Product: The team would spend one (or if desired, two) semester(s) developing a set of critical areas for further investigation, culminating in an article suitable for a peer-reviewed journal.additional references, each, to clarify their portion of the outline. To share his or herfindings, each student used a 5-slide PowerPoint presentation to explain what he or shehad learned. The DoS participated via teleconference in the instructor-facilitateddiscussion. Then, for four weeks, each student worked independently to write a five-page, singled-spaced, draft document with a minimum of fifteen references, each, thatclarified his or her
organizations often tend to amplify the moral and political values that are lacking and need to be further enhanced in developing contexts. They view technologies as instruments for well-being rather than profits.As engineering educators who are interested in preparing future engineers for the increasinglyglobalized future, we need to be careful about what kind(s) of “global engineers” we are training.Emphasizing one or two approaches to engineering ethics over others represents an incompleteapproach that fails to project an appropriately comprehensive view of global engineering practice.Obviously, we are not training every student to become a professional engineer working in amultinational business company, nor do we expect that
the given image. For example, one student (S03) wrote the following in hispre-VTS essay: “This mural shows us a landscape ... As for the content of this mural, ...[y]ou see a man in the middle who looks to be working next to some kind of fence in the pond that take[s] water closer to the house in the background.”InterpretationLike the quote above, most essays also contained writing that functioned to interpret the contentin the image. For example, another student (S02) wrote in his pre-VTS essay: Table 5. Preliminary Results of Inductive Coding of Short Essay Responses Before and After VTS Workshop (n=6) Total # of
focused on ambitious goals:“To take full advantage of the benefits and to recognize, address, and even avoid some of thepitfalls of technology. . . [to help citizens] become better stewards of technological change” (p.2). Then, as now, “technological literacy” is the most widely recognized way of describing theproject(s) in which this division is engaged. In my 2006 paper, I argued that we needed torename the enterprise, mainly because “literacy” implied remediation rather than the aspirationto create something that had never existed before: a well-informed citizenry with the knowledge,motivation, and confidence to engage in purposeful deliberation about technology. Looking back from a distance of over 10 years, I am pleased to say that
Paper ID #19852Improving the Requirements Inspection Abilities of Computer Science Stu-dents through Analysis of their Reading and Learning StylesMr. Anurag Goswami, North Dakota State University Anurag Goswami is a Ph. D. Candidate in the department of Computer Science at North Dakota State University. His main research interests include empirical software engineering, human factors in software engineering, and software quality. He is a member of the IEEE Computer Society.Dr. Gursimran Singh Walia, North Dakota State University Gursimran S. Walia is an associate professor of Computer Science at North Dakota State University
and the Eccles et al. Model of Achievement-Related Choices. In Handbook of competence and motivation, eds. A.J. Elliot and C.S. Dweck. New York: The Guilford Press.Echo Ridge (2017). Dyse – Dynamic Spectrum Environment Emulator, http://www.echoridgenet.com/products/dyse.Evans, J. S. B. T. (2003). In two minds: Dual-process accounts of reasoning. Trends in Cognitive Sciences, 7(10), 454-459. doi:10.1016/j.tics.2003.08.012Evans, Jonathan St. B. T. (2009). How many dual-process theories do we need? one, two, or many? (). Oxford: Oxford University Press. doi:10.1093/acprof:oso/9780199230167.003.0002Gee, J. P. (2003). What video games have to teach us about learning and literacy (1st ed.). New York
conducted, we have uncovered, timeand time again, that our students come into our classes with issues that have a direct or indirectbearing on their ability to learn physics. One central question this paper aims to address is: Arethe factors that impede or enhance student learning in physics any different in the millennial age?IntroductionToday’s classrooms are largely populated by millennials. For the past two decades we have seenincreased use of variety of terms used to describe them. The millennial is often considered to bean individual born sometime between approximately 1980 and 2000. We often refer to thissubset of the population as Generation Y or Gen Y. Other names given to this group ofindividuals include Echo Boomers and 24/7’s
Higher Education, TIAA Institute, April 2016. https://www.tiaainstitute.org/public/pdf/taking_the_measure_of_faculty_diversity.pdf. Accessed Feb. 11, 2017.[5] M. J. Finkelstein, V. M. Conley, J. H. Schuster. (2016). The Faculty Factor: Reassessing the American Academy in a Turbulent Era, Johns Hopkins University Press.[6] M. A. Mason, N. H. Wolfinger and M. Goulden. (2013). Do Babies Matter?: Gender and Family in the Ivory Tower. Rutgers University Press.[7] E. A. Cech and M. Blair-Loy. (2014) Consequences of flexibility stigma among academic scientists and engineers. Work Occupations 41(1):86–110.[8] S. Damaske, E. H. Ecklund, A. E. Lincoln & V. J. White. (2014). Male scientists’ competing devotions to work and family
2003.Colbeck, C.L., Campbell, S.E. and Bjorklund, S.A. 2000. Grouping in the dark: What collegestudents learn from group projects. The Journal of Higher Education, 71 (1): 60-83.Felder, R. M., G. N. Felder and E. J. Dietz. 1998. A Longitudinal Study of Engineering StudentPerformance and Retention. V. Comparisons with Traditionally-Taught Students. Journal ofEngineering Education, 87 (4): 469-480.Felder, R. M., and L. K. Silverman. 1988. Learning and teaching styles in engineeringeducation. Engineering education, 78 (7): 674-681.Froyd, J.E. and M.W. Ohland. 2005. Integrated Engineering Curricula. Journal of EngineeringEducation, 94 (1): 147-164.Graham, T., S. Rowlands, S. Jennings, and J. English. 1999. Towards whole-class inter- activeteaching
Press.2. Pryor, J. H. and Reedy, E. J., 2009, “Trends in Business Interest Among U.S. College Students: An Early Exploration of Data Available from the Cooperative Institutional Research Program,” Ewing Marion Kauffman Foundation.3. Yang, A., 2014, Smart People Should Build Things. New York, NY: HarperCollins Publishers.4. Boyd, N. G. and Vozikis, G. S., 1994, “The Influence of Self-Efficacy on the Development of Entrepreneurial Intentions and Actions,” Entrepreneurship Theory and Practice, pp. 63-77.5. McGrath, R. G., 2000, The Entrepreneurial Mindset: Strategies for Continuously Creating Opportunity in an Age of Uncertainty. Boston, MA: Harvard Business School Press.6. Condoor, S. and McQuilling, M., 2009, “Incorporating an
of all of the projects, students were remindedagain and again to think back to these goals, and encouraged to revise the goals as they learned more. Instep 3 (Decide what should be modeled and why), students imagined the model(s) they would create tomatch their physical system. This process didn’t simply ask students to rely upon knowledge they alreadytheoretically had. Rather, it forced them to research in order to learn how they might model the systemthey were analyzing. This research might take them back to foundational knowledge they had alreadybeen exposed to or to new knowledge; although at the beginning the modeling efforts tended to mainlyemphasize the former. The point is that there had to be early imagining of the ultimate model(s
, which consists ofthe types of information that would customarily be found on a job application. The informationprovided by students is used to compile and understand their capabilities and interests, whichincludes major(s), grade point average or GPA, past or current internship and/or coopexperiences, undergraduate research projects, technical skills, leadership experiences, careerinterests, project preferences, etc. As a result of using this process, over a period of many years,we have acquired a significant amount of data and insights into the factors that may contribute tocapstone team success.In parallel with the process of collecting and compiling information on student interests andcapabilities, project descriptions are developed that are
depth across the range ofengineering topics implied by the title of the program.The curriculum must include probability and statistics, including applications appropriate to theprogram name; mathematics through differential and integral calculus; sciences (defined asbiological, chemical, or physical science); and engineering topics (including computing science)necessary to analyze and design complex electrical and electronic devices, software, and systemscontaining hardware and software components.The curriculum for programs containing the modifier “electrical,” “electronic(s),”“communication(s),” or “telecommunication(s)” in the title must include advanced mathematics,such as differential equations, linear algebra, complex variables, and
question and aided inproducing a thick and rich dataset. The first question asked about the project(s) the student wasworking on and the second asked why he or she chose to participate in the extracurricularproject(s). The next four questions asked the students to discuss how their learning, engagement,confidence, and career prospects are affected by the project(s). The seventh question asked themto describe, in detail, the project building process, while the last two questions had them reflecton the value of the experience and the support they received. After each interview, codingcommenced using a constant comparative technique. Heuristic, discrete units of data was codedand categorized, initially through the note-taking process within the