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2016 ASEE Annual Conference & Exposition

Authors

Chandramouli Viswanathan Chandramouli, Purdue University, Calumet (Engineering); Emily Hixon; Chenn Q. Zhou, Purdue University, Calumet (Engineering); John Moreland, Purdue University Northwest; Jichao Wang, CIVS, Purdue University Calumet; zitao xiong, tappollo; Rameh Teegavarapu, Florida Atlantic University; Pradeep K. Behera P.E., University of the District of Columbia; JAMES FORREST FOX, University of Kentucky

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any othercomments on the unit of instruction. In courses where the 3D modules was implemented,students were asked to complete a questionnaire containing 40 objective items and 1 open-endeditem. All items included on the questionnaire used prior to 3D implementation are included onthis survey, with minor modifications made to reflect the inclusion of the 3D modules. 21additional items specific to the 3D modules were also added. The construction of thequestionnaire was influenced by the work of Lee (2011) [1] who also examined the use of virtualreality to aid learning.ParticipantsA total of 128 students participated in the study. Forty-five students were in a control group thatdid not use the 3D modules, while 83 students were in the treatment

Conference Session

NSF Grantees Poster Session II

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2016 ASEE Annual Conference & Exposition

Authors

Juan C Morales, Universidad del Turabo; Kenneth A Connor, Rensselaer Polytechnic Institute; Yacob Astatke, Morgan State University; Michael J. Prince, Bucknell University; Idalides Vergara-Laurens, Universidad del Turabo; Miguel A. Goenaga-Jimenez, Universidad del Turabo

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learn how to use the oscilloscope, they were able to see the signals, frequencies, and other parameters that are discussed in the classroom, but are best demonstrated with hands-on activities. Students were able to see how changing input parameters from the signal generator included in the software reflected different responses at the circuit output.  The best thing about this experience is for students to perform the different labs in the comfort of their homes with only the Analog Discovery Board which has a very low cost.  Students can have a virtual laboratory anywhere, once they have access to a PC or laptop.  The ease of using the board, the FFT, the potential to develop a number of experiments

Conference Session

NSF Grantees Poster Session I

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2016 ASEE Annual Conference & Exposition

Authors

M. J. Klopfstein, Oklahoma State University; Lisa Cota, Oklahoma State University; Don A. Lucca, Oklahoma State University; Xiaoliang Jin, Oklahoma State University; Prabhakar R Pagilla, Texas A&M University

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nonparametric data. Additionally, there is no estimation of population parametersin OOM; the statistics in OOM reflect solely the data collected. In an OOM analysis, theresearcher provides a hypothesized pattern for the data, and the analysis checks the obtained dataagainst that pattern. The resulting statistic, called a Percent Correctly Classified (PCC) index, isthe percentage of the data which fits the hypothesized pattern. For this paper, the hypothesizedpattern was an increase in students’ scores on the Awareness, Motivation or Exposure subscalesafter the lecture as compared to their scores before the lecture.Table 2 shows the results for this model. The column labeled “Percent Correctly Classified(PCC)” gives the percent of students whose score

Conference Session

NSF Grantees Poster Session II

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2016 ASEE Annual Conference & Exposition

Authors

Sheng-Jen Hsieh, Texas A&M University

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NSF Grantees Poster Session

.  Meeting as a group to discuss specific action items based on the survey results, such as curriculum changes and development of instructional materials and technologies.AcknowledgementsThis material is based upon work supported by the National Science Foundation’s AdvancedTechnology Education Program under Grant No. 1304843. Any opinions, findings, andconclusions or recommendations expressed in this material are those of the author(s) and do notnecessarily reflect the views of the National Science Foundation.References1. Bureau of the Census, Statistical Brief: Advanced Manufacturing Technology SB-13-90, U.S. Department of Commerce, Washington, D.C., 1990.2. Online resource available at: http://www.census.gov/foreign- trade

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NSF Grantees Poster Session I

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2016 ASEE Annual Conference & Exposition

Authors

Susan Staffin Metz, Stevens Institute of Technology (School of Engineering and Science); Sheryl A. Sorby, Ohio State University; Tania Jarosewich, Censeo Group LLC

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5) Orthographic Projection with feedback. Inclined and Curved Surfaces• Video mini-lectures. The team has professionally 6) Pattern Folding developed 2-5 minute video introductions to 7) Rotation of Objects about One Axis module topics, which are available in common 8) Rotation of Objects about Two or formats for use with a variety of computer More Axes platforms. 9) Reflection and Symmetry• Video how-to instructions. Additional videos 10) Cross-Sections of Solids

Conference Session

NSF Grantees Poster Session I

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2016 ASEE Annual Conference & Exposition

Authors

Yanna Lambrinidou, Virginia Tech; Nathan E Canney, Seattle University

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NSF Grantees Poster Session

. After analysis of these interviews isunderway, interviews with members of “mobilized publics” will be conducted to examine thisrelationship from both sides.AcknowledgementsThis material is based on work supported by the National Science Foundation under Grant#1551152. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation.References1 Riley, D. 2008. Engineering and Social Justice. San Rafael, CA: Morgan and Claypool.2 National Academy of Engineering (NAE). 2005. Educating the Engineer of 2020: Adapting EngineeringEducation to the New Century. Washington, DC: The National Academies Press, 47.3 National Academy of

Conference Session

NSF Grantees Poster Session I

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2016 ASEE Annual Conference & Exposition

Authors

Spencer Seung Kim, Rochester Institute of Technology (CAST); Elizabeth Dell, Rochester Institute of Technology (COE)

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Diversity, NSF Grantees Poster Session

plastics production line with prototyping,extrusion, and injection molding machines. Thus, the low-division students were able toexperiment with green materials for the lab activities, and the upper division students couldconduct applied research projects in green plastics manufacturing through co-op.17-20Assessment, Evaluation, and System ApproachThe traditional-transmission learning format, in which the degree of a student’s success dependsonly on the performance of quizzes, tests and projects in class, does not truly reflect theeffectiveness on learning and skills application.1-5, 11-15 We proposed a system approach to drawon the analysis and evaluation of student’s learning outcomes and thus, were able to design acurriculum model to improve an

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NSF Grantees Poster Session II

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2016 ASEE Annual Conference & Exposition

Authors

Katherine Christine Tetrick, Washington State Univeristy; Eve A. Riskin, University of Washington; John B. Schneider, Washington State University; Sonya Cunningham, University of Washington

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these categories is far above the university averages reflecting the factthat minorities and first-generation students are more prevalent among those from economicallyand educationally disadvantaged backgrounds.Table 1: 2013-2016 STARS student demographics Cohort I (2013-2014) Cohort II (2014-2015) Cohort III (2015-2016) UW WSU UW WSU UW WSUFirst Generation 80% 58% 80% 79% 45% 70%Underrepresented 47% 45% 44% 48% 31% 48%MinorityFemale 40% 18% 40% 14% 41% 19%Program DescriptionsThe STARS

Conference Session

NSF Grantees Poster Session II

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2016 ASEE Annual Conference & Exposition

Authors

Karl A Smith, University of Minnesota, Twin Cities; Ann F. McKenna, Arizona State University, Polytechnic Campus; Rocio C. Chavela Guerra, American Society for Engineering Education; Russell Korte, Colorado State University; Christopher Swan, Tufts University

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Veterans in Assistive Technology andEngineering) team who conducted 102 interviews. Their development is reflected in the changes to theirBusiness Model Canvas – Initial (Fig. 2) and Final (Fig. 3). See FIE 2014 paper for further details (32).Fig. 2 ELeVATE’s Initial Business Model Canvas (focus on value propositions and customer segments)Fig. 3 ELeVATE’s Final Business Model Canvas (focus on value propositions and customer segments)Assessing and Changing the I-Corps™ L ProgramQuality Evaluation Designs (QED) conducted a comprehensive evaluation focused on three facets of theI-Corps™ L program: 1. Program delivery, including the 3-day initial workshop, 5 webinars, and 2-day final workshop 2. Impact of I-Corps™ L program delivery on I-Corps

Conference Session

NSF Grantees Poster Session II

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2016 ASEE Annual Conference & Exposition

Authors

Kelsey Joy Rodgers, Purdue University, West Lafayette; Bryan W. Boudouris, Purdue University, West Lafayette; Heidi A. Diefes-Dux, Purdue University, West Lafayette; Michael T. Harris, Purdue University, West Lafayette

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model development requires students tocommunicate their ideas and continue to evolve their solutions to reflect their evolving ideasconcerning the mathematical situation. The model refinement process involves moving from aninitially chaotic model to a more developed model through an iterative process. Importantly,while these activities are to an extent open-ended, they are not the type of open-ended problemwhere any solution is acceptable; there are criteria built into the problem that make somesolutions better than others, aligning with the self-assessment principle (see below).12 In thiscourse, the iterative process involves three major submissions with feedback from both peers andinstructors.16

Conference Session

NSF Grantees Poster Session I

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2016 ASEE Annual Conference & Exposition

Authors

Micah Lande, Arizona State University, Polytechnic campus; Shawn S. Jordan, Arizona State University, Polytechnic campus

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NSF Grantees Poster Session

Making activities and maker spaces in childrens’ museums.There is a trend for museums and science/technology centers to establish Maker spaces. ThePittsburgh Children's Museum has created Makeshop, a maker space reflecting 7 specificlearning practices, for example. Research has shown Maker spaces as sources ofmultidisciplinary learning, a blending of communities of practice with formal learning, andfinally that the depth of learning is in the making. While the research points to the values ofMaking in general, and specifically making in museum maker spaces, there seems to be littleresearch on family making, and how museums can encourage family making. This researchhopes to bridge both these gaps by studying the importance of family making and

Conference Session

NSF Grantees Poster Session II

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2016 ASEE Annual Conference & Exposition

Authors

Yi Pan, Georgia State University; Michael Weeks, Georgia State University; Yanqing Zhang, Georgia State University

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NSF Grantees Poster Session

that we can measure the learningexperiences and outcomes in these 4 courses. Below are the evaluation results.Pre-EvaluationAll the participants are students from the computer science department at Georgia State University. Theassessment is divided into three parts:  Work experience with computer and programming language used (written response)  Knowledge of operating system (choice question)  Study experience of PC and different ways to learn (choice question)The diversity in the nature of question reflects both the understanding of students about the operating system andthe best way for the students to learn it effectively.Written response – Operating System:Work Experience YES (%) NO (%)Have

Conference Session

NSF Grantees Poster Session I

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2016 ASEE Annual Conference & Exposition

Authors

Brian J Skromme, Arizona State University; Xiang Gao, Arizona State University; Bhargav Korrapati, Arizona State University; Vignesh Seetharam, Arizona State University; Yih-Fang Huang, University of Notre Dame; Daniel H Robinson, The University of Texas at Austin

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Tutor showed a statistically significantadvantage for the post-test scores on node analysis [t(64) = 3.09, p < 0.05] with an effect size(Cohen d-value) of 0.72σ. For mesh analysis, the difference was not statistically significant [t(64)= 0.88, p = 0.38], which may reflect the fundamentally easier nature of that topic (both groupshad relatively high averages). The survey results showed a very strong preference for CircuitTutor and a strong belief that it taught them more effectively than System X. A typical studentcomment was “I liked Circuit Tutor more because I could do a ton of problems. I liked that evenif I couldn't figure it out, I could ‘give up’; and it would thoroughly explain how to do everythingso I could understand what I did

Conference Session

NSF Grantees Poster Session I

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2016 ASEE Annual Conference & Exposition

Authors

Matthew W. Ohland, Purdue University, West Lafayette; Russell Andrew Long, Purdue University, West Lafayette; Susan M Lord, University of San Diego; Marisa K. Orr, Louisiana Tech University; Catherine E. Brawner, Research Triangle Educational Consultants

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related to those. In spite of these constraints, there are plans to expandboth the number of participating institutions and research access to the dataset.Expansion strategy. New institutional partners will receive funding to provide and update data.As the database becomes larger in size, joining the MIDFIELD partnership becomes even moreattractive. Twenty institutions have signed letters of commitment to join MIDFIELD. Newinstitutions will be targeted to reflect variability in geographic region, institution size asdetermined by the number of engineering graduates per year, and institutional control (public orprivate). Institutions will also be targeted that have a high or low graduation rate for under-represented minorities – plans include

Conference Session

NSF Grantees Poster Session II

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2016 ASEE Annual Conference & Exposition

Authors

Yen-Lin Han, Seattle University; Kathleen E. Cook, Seattle University; Teodora Rutar Shuman, Seattle University; Gregory Mason, Seattle University

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and surface N. 4. Angle factors are available in equation or graphic form in both publications cited in the Reference section. They must be determined from the area and local geometry of all the enclosing “panels” that are “seen” by the person whose comfort is being assessed. Angle Factor Charts and equations are shown in Figure 9. The equations apply to a small horizontal plane, whereas the charts (not shown) reflect the view of a rotated person represented by plane projections. 5. A site visit will be required to measure the window areas and a, b, and c view factor dimensions.bNecessary Assumptions: 1. The indoor glass surface temperature must be calculated or measured

Conference Session

NSF Grantees Poster Session II

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2016 ASEE Annual Conference & Exposition

Authors

Nasser Alaraje, Michigan Technological University; Aleksandr Sergeyev, Michigan Technological University; John Reutter III, J.F. Drake State Community and Technical College; Craig J. Kief, COSMIAC at UNM; Bassam H Matar, Chandler Gilbert Community College; David M. Hata, TEMPlaTe Educational Consulting

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12 38 African-American 7 5 12 Native-American 0 0 0 Other Ethnicity 10 3 13 Table 2. “Applied Value” survey results for fall semester 2014 and spring semester 2015 at four-year colleges.A total of 23,000 student-hours of microcontroller instruction was delivered at the college levelduring the 2014-15 academic year. The number of student-hours of instruction delivered at thefour-year level was double that delivered by community colleges and may reflect a greater abilityto apply the technology

Conference Session

NSF Grantees Poster Session II

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2016 ASEE Annual Conference & Exposition

Authors

Greg Kepner, Midwest Photonics Education Center; Anca L. Sala, Baker College, Flint

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DUE# 1400561 “Midwest PhotonicsEducation Center.”Any opinions, findings, and conclusions or recommendations expressed in this material are thoseof the authors and do not necessarily reflect the views of the National Science Foundation.Bibliography1. http://www.light2015.org/Home/Event-Programme.html?tab=1. Accessed Jan. 11, 2016.2. http://www.aimphotonics.com/. Accessed Jan. 11, 2016.3. http://www.op-tec.org/index.php. Accessed Jan. 11, 2016.4. http://www.op-tec.org/resources/industry-demand-report. Accessed Jan. 30, 2016.5. http://www.mi-light.org. Accessed Jan. 11, 2016.

Conference Session

NSF Grantees Poster Session II

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2016 ASEE Annual Conference & Exposition

Authors

James Huff, Harding University; Brent K Jesiek, Purdue University, West Lafayette; Carla B. Zoltowski, Purdue University, West Lafayette; Kavitha Durga Ramane; William C. Oakes, Purdue University, West Lafayette

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sociotechnical mindsets that our students can instill inengineering practice.References 1. Huff, J. L. (2014). Psychological journeys of engineering identity from school to the workplace: How students become engineers among other forms of self. Retrieved from ProQuest, UMI Dissertations Publishing (3669254). 2. Huff, J. L., Smith, J. A., Jesiek, B. K., Zoltowski, C. B., Graziano, W. G., & Oakes, W. C. (2014). From methods to methodology: Reflection on keeping the philosophical commitments of interpretative phenomenological analysis. Proceedings of the 2014 ASEE/IEEE Frontiers in Education Conference. October 2014, Madrid. 3. Huff, J. L., Jesiek, B. K., Zoltowski, C. B., Ramane, K. D., Graziano, W. G

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NSF Grantees Poster Session I

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2016 ASEE Annual Conference & Exposition

Authors

Ravi P. Ramachandran, Rowan University; Steven H Chin, Rowan University; Kevin D. Dahm, Rowan University; Liang Hong, Tennessee State University; Sachin Shetty, Tennessee State University; Robert M Nickel, Bucknell University; Richard J. Kozick, Bucknell University; Ying Tang, Rowan University; Robi Polikar, Rowan University

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from Worces- ter Polytechnic Institute (92) and his PhD from Massachusetts Institute of Technology (98). He has pub- lished two books, ”Fundamentals of Chemical Engineering Thermodynamics” and ”Interpreting Diffuse Reflectance and Transmittance.” He has also published papers on effective use of simulation in engineer- ing, teaching design and engineering economics, and assessment of student learning.Dr. Liang Hong, Tennessee State University Dr. Liang Hong received the B.S. and the M.S. degrees in Electrical Engineering from Southeast Univer- sity, Nanjing, China in 1994 and 1997, respectively, and the Ph.D. degree in Electrical Engineering from University of Missouri, Columbia, Missouri in 2002. Since August 2003

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NSF Grantees Poster Session I

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2016 ASEE Annual Conference & Exposition

Authors

Farshid Marbouti, Purdue University, West Lafayette; Heidi A. Diefes-Dux, Purdue University, West Lafayette; Monica E Cardella, Purdue University, West Lafayette

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. Adams, R. S.; Turns, J.; Atman, C. J., Educating effective engineering designers: The role of reflective practice. Design Studies 2003, 24 (3), 275-294.21. Bursic, K. M.; Atman, C. J., Information gathering: A critical step for quality in the design process. Quality Management Journal 1997, 4 (4), 60-75.22. Christiaans, H.; Dorst, K. H., Cognitive models in industrial design engineering: A protocol study. Design Theory and Methodology 1992, 42, 131-140.23. Crismond, D. P.; Adams, R. S., The informed design teaching and learning matrix. Journal of Engineering Education 2012, 101 (4), 738-797.24. Atman, C. J.; Bursic, K. M., Teaching engineering design: Can reading a textbook make a difference? Research in Engineering Design 1996

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NSF Grantees Poster Session I

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2016 ASEE Annual Conference & Exposition

Authors

Andrea M. Ogilvie P.E., Virginia Tech; David B Knight, Virginia Tech Department of Engineering Education; Maura J. Borrego, University of Texas, Austin; Arturo A Fuentes, University of Texas, Rio Grande Valley; Patricia A. Nava, University of Texas, El Paso; Valarie E. Taylor, Texas A&M University

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this study: Dean Tonie Badillo, El Paso CommunityCollege; Dr. Monica Cortez, Texas A&M University; Dr. Eli Esmaeili, South Texas College; Dr.Ben Flores, UTEP; Assistant Dean Patricia A. Gore, UT Austin; Dr. Julie Martin, ClemsonUniversity; Dr. Sylvia McMullen, Blinn College; Dr. MaryJane McReynolds, Austin CommunityCollege; Ms. Jackie Perez; Texas A&M University; Dr. Soko S. Starobin, Iowa State University;Dr. Cristina Villalobos, UT Rio Grande Valley.This material is based upon work supported by the National Science Foundation under Grant No.1428502. Any opinions, findings, and conclusions or recommendations expressed in this materialare those of the author(s) and do not necessarily reflect the views of the National

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NSF Grantees Poster Session II

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2016 ASEE Annual Conference & Exposition

Authors

Samantha Ruth Brunhaver, Arizona State University, Polytechnic campus; Holly M Matusovich, Virginia Tech; Ruth A. Streveler, Purdue University, West Lafayette; Sheri Sheppard, Stanford University; Cheryl Carrico P.E., Virginia Tech; Angela Harris, Stanford University

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. This research is funded by the NSF as acollaborative research grant (EEC-1360665, 1360956, and 1360958). Any opinions, findings,and conclusions or recommendations expressed in this material are those of the authors and donot necessarily reflect the views of the NSF.Bibliography[1] National Science Foundation, National Center for Science and Engineering Statistics, 2010 SESTAT Integrated Data System, 2013, Retrieved from http://www.nsf.gov/statistics/sestat.[2] G. Lichtenstein, H. G. Loshbaugh, B. Claar, H. L. Chen, K. Jackson, and S. D. Sheppard, “An engineering major does not (necessarily) an engineer make: Career decision making among undergraduate engineering majors,” J. Eng. Ed., vol. 98, no. 3, pp. 227-234.[3] National Center

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2016 ASEE Annual Conference & Exposition

Authors

Aditya Johri, George Mason University; Lori C. Bland, George Mason University; Stephanie Marie Kusano, University of Michigan

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morecomparative analysis of what experiences are the most beneficial.AcknowledgementsThis work was supported in part by NSF Grant#EEC-1424444. We would like to thank ourinformants for participating in the field studies reported here. Any opinions, findings, andconclusions or recommendations expressed in this material are those of the author(s) and do notnecessarily reflect the views of the National Science Foundation.References1. ABET. (2011). Criteria for Accrediting Engineering Programs – Program Outcomes and Assessment. Baltimore, MD: Accreditation Board for Engineering and Technology.2. ASEE (2012). Innovation with Impact: Creating a Culture for Scholarly and Systematic Innovation in Engineering Education. Leah H. Jamieson and Jack R

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NSF Grantees Poster Session II

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2016 ASEE Annual Conference & Exposition

Authors

Noah Salzman, Boise State University; Matthew W. Ohland, Purdue University, West Lafayette; Monica E Cardella, Purdue University, West Lafayette

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, Indianapolis, IN.• Salzman, N., & Ohland, M. W. (2013). Precollege Engineering Participation among First-Year Engineering Students. Presented at the 5th First Year Engineering Experience (FYEE) Conference. Pittsburg, PA. Acknowledgements The authors would also like to acknowledge the support of the National Science Foundation (EEC Grant # 1550961). Any opinions, findings, conclusions, or recommendations do not necessarily reflect the views of the National Science Foundation. The authors would also like to thank Dr. Cathleen Barczys Simons and Dr. Stephen Hoffman for assistance with data collection and analysis for this project. References 1. Carr, R. L., Bennett, L. D. & Strobel, J. Engineering in

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NSF Grantees Poster Session II

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2016 ASEE Annual Conference & Exposition

Authors

Peter R Turner, Clarkson University; Jeffrey Humpherys, Brigham Young University

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and further developed in MaC II. One possibleavenue is the development of undergraduate STEM degree programs as alternatives to traditionaldiscipline majors. These might mirror the growth of Computational Science and Engineering programsover the past 10 – 15 years, and are likely to be reflected in the growth of Data-Enabled Science andEngineering in the next several years. A key question is the extent to which mathematical modeling istreated as a stand-alone “course” or whether it should be integrated as the Modeling across theCurriculum title suggests. Coordinating the fundamental mathematics, computation, statistics and sciencecontent to support application in a wide range of STEM fields may have strong appeal to potentialstudents.The 2.5

Conference Session

NSF Grantees Poster Session I

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2016 ASEE Annual Conference & Exposition

Authors

Bimal P. Nepal, Texas A&M University; Michael Johnson, Texas A&M University; Maria Antoun Henri, Texas A&M University ; Norma Perez, Houston Community College; Madeline Burillo, Houston Community College; Roberto Sanchez, Houston Community College

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demand STEM careers.AcknowledgementThis material is supported by the National Science Foundation under DUE Grant Numbers 1501952and 1501938. Any opinions, findings, conclusions, or recommendations presented are those of theauthors and do not necessarily reflect the views of the National Science Foundation.References1. Coleman, N., and Ford, M., 2014, "North Dakota and Texas now provide half of U.S. crude oil production," Today in Energy, July 1, http://www.eia.gov/todayinenergy/detail.cfm?id=16931 (Retrieved on July 25, 2014)2. Texas Wide Open for Business, 2013, "Manufacturing in Texas," TexasWideOpenforBusiness.Com, http://www.governor.state.tx.us/files/ecodev/Manufacturing_in_Texas.pdf (Retrieved on July 25, 2014)3. Modine, J

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NSF Grantees Poster Session II

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2016 ASEE Annual Conference & Exposition

Authors

Keke Chen, Wright State University; Bin Wang, Wright State University; Prabhaker Mateti, Wright State University

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NSF Grantees Poster Session

or recommendations expressed in this material are those of theauthors and do not necessarily reflect the views of the National Science Foundation.References [1] Rakesh Agrawal, Anastasia Ailamaki, Philip A. Bernstein, Eric A. Brewer, Michael J. Carey, Sura- jit Chaudhuri, AnHai Doan, Daniela Florescu, Michael J. Franklin, Hector Garcia-Molina, Johannes Gehrke, Le Gruenwald, Laura M. Haas, Alon Y. Halevy, Joseph M. Hellerstein, Yannis E. Ioan- nidis, Hank F. Korth, Donald Kossmann, Samuel Madden, Roger Magoulas, Beng Chin Ooi, Tim O’Reilly, Raghu Ramakrishnan, Sunita Sarawagi, Michael Stonebraker, Alexander S. Szalay, and Ger- hard Weikum. The claremont report on database research. SIGMOD Record, 37(3):9–19, 2008. [2

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NSF Grantees Poster Session I

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2016 ASEE Annual Conference & Exposition

Authors

Robert L. Nagel, James Madison University; Matt Robert Bohm, University of Louisville; Julie S Linsey, Georgia Institute of Technology

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metropolitan public university, designatedas High Doctoral Research by the Carnegie Foundation are also be participating. Studies at thissecond location are focusing on impact of teaching function on capstone design quality. Resultsof these studies are forthcoming.AcknowledgementsThis work is supported by the National Science Foundation through grants 1525449, 1525170,and 1525284. Any  opinions,  findings,  and  conclusions  or  recommendations  expressed  in  this  material  are  those  of  the  authors  and  do  not  necessarily  reflect  the  views  of  National  Science  Foundation.References1.   Pahl  G,  Beitz  W,  Feldhusen  J,  Grote  KH.  Engineering  Design:  A  Systematic  Approach.  3rd  ed:  Springer   Verlag;  2007.  2

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2016 ASEE Annual Conference & Exposition

Authors

Steve Warren, Kansas State University

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Conference Session

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2016 ASEE Annual Conference & Exposition

Authors

Geoffrey L Herman, University of Illinois, Urbana-Champaign; Nicole Johnson-Glauch, University of Illinois at Urbana-Champaign

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ofIllinois or to the topic of state machines in digital logic. Interviews with instructors of digitallogic courses are ongoing. Comparisons between the reasoning and problem solving approachesof students and instructors will be compared in future studies to enable comparisons betweenexperts and novices.6. AcknowledgmentsThanks to Lance Pittman for his help with collecting data and supporting analysis. This projectwas supported by the National Science Foundation under grant EEC 1429348. The opinions,findings, and conclusions presented in this paper do not necessarily reflect the views of theNational Science Foundation or the authors’ institution.References1  Juhl, J. & Lindegaard, H. Representations and visual synthesis in engineering design