Collection

2007 Spring ASEE Middle Atlantic Section Conference

Authors

Kalyan Mondal

specification, the formula fororder calculation will be different.For a relative specification, the order N of a Butterworth lowpass prototype is given by: ⎡ log10 [(10 R p / 10 − 1) /(10 As / 10 − 1)] ⎤N =⎢ ⎥ , where R p denotes the passband ripple in dB, ⎢ 2 log10 (Ω p / Ω s ) ⎥As denotes the stopband attenuation in dB, Ω p is the passband edge angular frequency inradians/s, and Ω s is the corresponding stopband edge angular frequency in radians/s.In the case of absolute specifications in terms of 3-dB cutoff frequency Ω c , the order N is given ⎡ log10 [(1 / δ 22 ) − 1] ⎤by N = ⎢ ⎥ , where δ 2 is the absolute attenuation factor. ⎢ 2

Collection

2007 Fall ASEE Middle Atlantic Section Conference

Authors

Yan H. Huang; Seong W. Lee

students will design the experiment with purpose. The students need to take some courses like statistics, thermodynamics, experimental design etc. so that they can analyze the observed data in a more accurate way. Reference:1. National Research Council. “Engineering Undergraduate Education.” Nation Academy Press. Washington, D.C. pp. 8-15. 1986.2. Albrecht, H., and etc. (2002), Laser Doppler and Phase Doppler Measurement Techniques. Springer-Verlag Publishing.3. S. M. Maasutani,(1997). Laboratory Experiments to Simulate CO 2 Ocean Disposal.4. Albrecht, H., and etc., Laser Doppler and Phase Doppler Measurement Techniques, Springer-Verlag Publishing, December, 2002.5. Chukwulebe, B.Q. and S. Lee, “Laser-Based Investigation of

Collection

2006 Spring ASEE Middle Atlantic Section Conference

Authors

James A. Sinclair; Kamal Shahrabi; Ali Setoodehnia

CD ROM drives.• Minimum 32 MB RAM (the program will still run with less then minimum RAM required, but you may not get the desired results in speed or video reproduction quality).• Any Windows Media Player programs, including the player that is always included in all standard MS Windows installations.• Any commercial speakers.Bibliography:Alessi, S. & Trollip, S. (1991) Computer Based Instruction: Methods & Development,2nd Edition. New Jersey: Prentice Hall Publishers.Arnold, S., Barr, N., & Donnelly, P. (1994). Constructing and ImplementingMultimedia Teaching Packages, Glasgow: University of Glasgow (TLTP).Blackmore, J. (1996) Pedagogy: Learning Styles [Online]. Available:http://granite.cyg.net/~jblackmo/diglib

Conference Session

Electrical and Computer Engineering Division (ECE) Poster Session

Collection

2024 ASEE Annual Conference & Exposition

Authors

Chao Wang, Arizona State University

Tagged Divisions

Electrical and Computer Engineering Division (ECE)

solving sessions to engage students in a highly theoretical Random SignalAnalysis course.Research has shown that when students are in constructive and interactive modes of engagement,they gain deeper understanding of knowledge. To help students learn better, six interactive andactive problem solving sessions are incorporated in the Random Signal Analysis course. In eachproblem solving session, students are presented with one or multiple non-trivial problem(s).They work in teams of two while interacting with a table of eight students. While students areengaging with problem solving, the instructor and teaching assistants walk around the classroomanswering questions and giving feedback.At the end of each problem solving session, students complete a

Collection

2003 ASEE North Midwest Section Conference

Authors

Michael P. Hennessey

curve, experimental – purple triangles).References[1] University of St. Thomas, 2002-2004 Undergraduate Catalog, St. Paul, MN, 2002.[2] Scofield, C., O’Brien, M., and Nelson, R., “Modeling the Kinematics of a GCA Par Systems DKP300V Robot Manipulator,” 15th Annual Winchell Undergraduate Research Competition, sponsored by the Minnesota Academy of Science and hosted by the University of St. Thomas, April 27-28, 2001. [3] McClelland, S. R., “Characterizing Slop in Mechanical Assemblies Using SolidWorks ,” ASME RSC Region VII Old Guard Competition, Wichita, KS, April 5, 2002.[4] Hennessey, M. P., Shakiban, C., and Shvartsman, M

Collection

2009 Pacific Southwest Section Meeting

Authors

Ranjan K. Sen; Pradip Peter Dey

  emory and the distributed me emory models of parallel p programming g.    The shareed memory m model is also  known as the e symmetric  multiprocess sing or SMP wwhere cost off data access  by different  sequential  program  insta y  s ances  of  a  parallel  com mputation  are the  same. This  e  . assumptioon is not nece essarily alway

Collection

2009 Pacific Southwest Section Meeting

Authors

Gordana Jovanovic Dolecek; Fred Harris

. Fig. 9. Rating scheme.AcknowledgementThis work was supported in part by the CONACYT under Grant No. 91013.References1.T. C. Hutchinson, F. Kuester, „ Hardware Architecture for a Visualization Classroom: VizClass, 2004 Wiley Periodicals, Inc. Comput appl Eng Educ 12:232-241.2. Fuller D.A. and Moreno A.F. (2004). Experimenting With a Computer-Mediated Collaborative Interaction Model to Support Engineering Courses, Computer Applications in Engineering Education, 12 (3), 175-187.3. Li, S. G. and Lie, Q.(2004). Interactive Groundwater (IGW): An Innovative Digital Laboratory for Groundwater Education and Research, Computer Applications in Engineering Education, 11 (4), 179-203.4. Fu, T.T. (2003). Applications of Computer Simulation in

Collection

2010 Northeast Section Meeting

Authors

Raymond Addabbo

, = 0, we obtain a second order nonlinear ordinary dtdifferential equation, d 2θ (3) + ω 02 sin θ = 0. dt 2The units of physical parameters are emphasized that is, angular frequency, frequency and periodas summarized below in table 1. Name of Parameter Symbol Units Angular Frequency g rad ω0 = s l

Collection

2014 ASEE Zone 1 Conference

Authors

Hamoud Alshammari; Hassan Bajwa; Jeongkyu Lee

required data. NameNode should be able to direct thethe subsequence of a sequence that has already been jobs to read the specific DataNodes without goingsearched require the same amount of time. through all DataNodes. 3 REFERENCES[1] A. Pavlo, E. Paulson, A. Rasin, D. J. Abadi, D. J. [7] A. McKenna, M. Hanna, E. Banks, A. Sivachenko, K. DeWitt, S. Madden, and M. Stonebraker, "A Cibulskis, A. Kernytsky, K. Garimella, D. Altshuler, comparison of approaches to large-scale data S. Gabriel, and M. Daly, "The Genome Analysis analysis," in Proceedings of the 2009 ACM

Collection

2007 St.Lawrence Section Meeting

Authors

Chirag Variawa

report.This paper focuses on the 2005-2006 academic year, and analyzes the second part of the ESPcourse series, ESP II. In was this particular year ESP was first taught in full-scale, and it wasalso the year in which the author was a student in the class. The course coordinator andinstructors, respectively, for the 2005-2006 year included Prof.’s S. McCahan, P. Anderson, R.Andrews, M. Kortschot, K. Woodhouse, and P.E. Weiss. Enrolment in the 2005-2006 year wasapproximately 950 students at the beginning of the course.Project-Based Learning (PBL) coursesEngineering Strategies and Practice II is a project-based learning course. The student’s grade isbased on their approach to addressing the client’s need, and the level to which they haveincorporated

Conference Session

Student Papers

Collection

2025 ASEE Southeast Conference

Authors

Spencer Matthew Pollard, California State University, Chico; Abbas Attarwala, California State University, Chico; Jaime Raigoza, California State University, Chico

Tagged Topics

Student Papers

-source materials so we may construct the activity ourselves.References[1] J. K. Perron, C. DeLeone, S. Sharif, T. Carter, J. M. Grossman, G. Passante, and J. Sack, “Quantum Undergraduate Education and Scientific Training,” 2021. [Online]. Available: https://arxiv.org/abs/2109.13850[2] A. Asfaw, A. Blais, K. R. Brown, J. Candelaria, C. Cantwell, L. D. Carr, J. Combes, D. M. Debroy, J. M. Donohue, S. E. Economou, E. Edwards, M. F. J. Fox, S. M. Girvin, A. Ho, H. M. Hurst, Z. Jacob, B. R. Johnson, E. Johnston-Halperin, R. Joynt, E. Kapit, J. Klein-Seetharaman, M. Laforest, H. J. Lewandowski, T. W. Lynn, C. R. H. McRae, C. Merzbacher, S. Michalakis, P. Narang, W. D. Oliver, J. Palsberg, D. P. Pappas, M. G. Raymer, D. J. Reilly, M

Conference Session

Professional Papers

Collection

2025 ASEE Southeast Conference

Authors

Simon Thomas Ghanat P.E., The Citadel; Mostafa Batouli, The Citadel; William J. Davis P.E., The Citadel; Tess Doeffinger, The Citadel; Anthony Songer, Boise State University

Tagged Topics

Professional Papers

strategies toboost preparation and participation, thereby enhancing learning outcomes across engineeringsubjects.Due to the small sample size, it is challenging to make conclusive recommendations based on theobservations. The results of this study, limited to the data from 2022-2023, should not begeneralized to broader conclusions. Further data collection and analysis over several more courseofferings are necessary to draw informative conclusions. Future studies should encompassdifferent courses with larger sample sizes. Engineering faculty can create a more engaging andeffective learning environment in their courses by incorporating the strategy used in this study.References[1] Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N

Conference Session

Professional Papers

Collection

2025 ASEE Southeast Conference

Authors

Andrea Arce-Trigatti, Tennessee Tech University; Pedro E. Arce, Tennessee Technological University; Robby Sanders, Tennessee Technological University

Tagged Topics

Professional Papers

. “The renaissance foundry: A powerful learning and thinking system to develop the 21st century engineer,” Critical Conversations in Higher Education, 1(2), 2015, 176-202. 6. V. Matthew, S. Lipkin-Moore, P. E. Arce, A. Arce-Trigatti, N. Lavoine, L. Lucia, E. Selvi, M. Eggermont, M. Tiryakioglu, J. Hall, R. Edelen, and J. Plumblee. “A Roadmap for the Design and Implementation of Communities of Practice for Faculty Development,” Paper presented at 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. 2022, https://peer.asee.org/40564 7. K. Pabody, C. Wilson, A. Arce-Trigatti, P. E. Arce, S. H. Buer, A. Haynes, R. Chitiyo, J. R. Sanders, and T. Smith. “The Renaissance Foundry Model and culturally

Conference Session

Professional Papers

Collection

2025 ASEE Southeast Conference

Authors

Robby Sanders, Tennessee Technological University; Andrea Arce-Trigatti, Tennessee Tech University; Pedro E. Arce, Tennessee Technological University

Tagged Topics

Professional Papers

Engineering Education,” 2022. Retrieved from https://engineeringforoneplanet.org/wp- content/uploads/2022_EOP_Framework_110922.pdf 4. P. E. Arce, J. R. Sanders, A. Arce-Trigatti, L. Loggins, J. Biernacki, M. Geist, J. Pascal, and K. Wiant. “The renaissance foundry: A powerful learning and thinking system to develop the 21st century engineer,” Critical Conversations in Higher Education, 1(2), 2015, 176-202. 5. V. Matthew, S. Lipkin-Moore, P. E. Arce, A. Arce-Trigatti, N. Lavoine, L. Lucia, E. Selvi, M. Eggermont, M. Tiryakioglu, J. Hall, R. Edelen, and J. Plumblee. “A Roadmap for the Design and Implementation of Communities of Practice for Faculty Development,” Paper presented at 2022 ASEE Annual Conference

Conference Session

Professional Papers

Collection

2025 ASEE Southeast Conference

Authors

Sean Walker, University of South Alabama; Kari J Lippert, University of South Alabama

Tagged Topics

Professional Papers

+( ) 𝐸2 𝑁A confidence interval (𝑧) of 95% is chosen, yielding Z-values of 1.96, with a margin of error (𝐸)of 4%-8%, which corresponds to the 95% confidence interval [13]. The standard deviation (𝜎) isestimated to be 1, given the small population size. After n surveys have been completed, thesample standard deviation (s) will be calculated and a confidence interval for σ will bedetermined to ensure that the correct number of samples are take. N is the total population size ofall the students exposed to the flipped classroom with alternate instructors. Three statisticalmethods of means, materiality, statistical relations, and Cronbach’s Alpha, illustrated in Equation(2), will be used to analyze and understand the results of the survey

Conference Session

Professional Papers

Collection

2025 ASEE Southeast Conference

Authors

Adam Piper, Mississippi State University; Jenna Johnson, Mississippi State University; Daniel Dunaway, Mississippi State University

Tagged Topics

Professional Papers

evaluations ofteaching, course surveys, or simply teaching evaluations) have been used for assessing teachers’effectiveness in one form or another since the 1920’s. In many cases, though, modernassessment has relied far too heavily on student opinions as though it were a comprehensiveassessment of teaching effectiveness and student learning [2], when in fact, there are numerousapproaches to evaluate teaching more holistically. Other common strategies for teachingevaluation include peer observation (by fellow faculty members), external review (often byexperienced teaching and learning professionals), and self-evaluation. In each case, modernapproaches center on evidence-based evaluation practices [3], and several examples arediscussed herein.The

Collection

2014 ASEE Zone 1 Conference

Authors

Sundas Zafar; Aparicio Carranza

saved this python script will run. The scriptextracted. The actual configuration file is camera.py is designed to use SSMTP and sendtitled motion­mmalcam.conf. an email notification every time a picture is saved. Since it uses SSMTP it is necessary towget  enter the email address and password of thehttps://www.dropbox.com/s/xdfcxm5hu71s97d/ account the notifications are to be sent to [3].motion­mmal.tar.gz The content text can also be adjusted withintar zxvf motion­mmal.tar.gz the program. In this

Collection

2014 ASEE Zone 1 Conference

Authors

Walter Engels; Farshid Zabihian

the cold deep water toefficiency was 6.99%. In the second analysis of the system, there the surface [2]. In 1993 a small open cycle OTEC plant waswas a mass flow rate of 1000 kg/s. The working fluid and designed and constructed by L. A. Vega in Hawaii [3]. Thistemperature difference were accounted for in the heat exchangeof the warmer surface water to the cold water used in the was a small plant that was more of a testing plant. The plantcondenser. In this analysis the Rankine cycle efficiency was closed in 1998. It was a model of an actual working plant andfound to be 3.97% and the

Collection

2025 Northeast Section Conference

Authors

Julianne Torreno; Nealesh Guha; Mashtura Rahman; Michael Ventouratos; David Lee; Shivansh Sharma; Sunil Dehipawala; Guozhen An; Tak Cheung

Proteins and DNA are Poorly Correlated”, Mol Biol Evol. 2023 Apr 4;40 (4).with the student population. There are about 5 physics majors, [2] L. Teekas, S. Sharma, and N. Vijay, “Terminal regions of a protein are a50 engineering majors, and 500 ET majors in which 20 of them hotspot for low complexity regions and selection”, Open Biol. 2024are considering transition to engineering. None of the Jun;14(6):230439.participants in this report is majoring in physics. In fact, all the [3] B. Leung, unpublished data, Year of 2025 Great Neck

Collection

2015 ASEE Zone 3 Conference

Authors

Luis Rodriguez; Gail Coover; Dalelia Davis; George Johnson; Oumar Kaba; Angela Frey; Andrew Pham; Amihan Huesmann

outcomes (retention/graduation rates and exit surveys) of the pilot run of the program measured so far bode well for the potential impact of the WiscAMP Excel Program on URM student success in STEM.Bibliography1. Dweck, C. S. (2006) Mindset: The new psychology of success. New York: Ballantine Books.2. Dweck, C. S., Legget, E. L. (1988) “A social-cognitive approach to motivation and personality”, Psychological Review 953. Hurtado, S., Eagan K., HERI Research Brief (2010) Degrees of Success: Bachelor’s Degree Completion Rates among Initial STEM majors. Higher Education Research Institute at UCLA4. Figueroa, T., Hughes B., Hurtado, S. (2013) “Supporting Future Scientists: Predicting Minority Student Participation in

Collection

2014 ASEE Zone 4 Conference

Authors

Matthew Adle; Justin Bostwick; Kyle Graves; Synjin Hipolito; Yong Gan

, C.G.; Antonietti, M., Mesoporous materials by templating of liquid crystalline phases, Adv. Mater. 1997, 9, 431–436.10. Goltner, C.G.; Henke, S.; Weibenberger, M.C.; Antonietti, M., Mesoporous silica from lyotropic liquid crystal polymer templates, Angew. Chem. 1998, 110, 633–636.11. Kramer, E.; Forster, S.; Goltner, C.; Antonietti, M., Synthesis of nanoporous silica with new pore morphologies by templating the assemblies of ionic block copolymers, Langmuir, 1998, 14, 2027–2031.12. Goltner, C.G.; Berton, B.; Kramer, E.; Antonietti, M., Nanoporous silicas by casting the aggregates of amphiphilic block copolymers: The transition from cylinders to lamellae and vesicles, Adv. Mater. 1999, 11, 395–398.13. Han, B.H

Collection

2015 Pacific Southwest Section Meeting

Authors

Bridget Benson; John Oliver

describes our implementation of Mastery learning and how it played out inour courses. It is our hope that this paper will give others ideas of how to learn from our mistakesso that other implementations of mastery learning schemes may be more successful.IntroductionThe concept of mastery learning has been around in public schools since the 1920s, but did notgain popularity until the 1960s, with Benjamin S. Bloom’s paper on ‘learning for mastery’ in19681 and another paper on ‘mastery learning’ in 19712. The idea behind Mastery learning is tomake sure all students achieve ‘mastery’ of the course learning objectives by the end of thecourse rather than being solely concerned about assigning an A-F grade on all assignments. Thedriving force behind a

Collection

2025 ASEE -GSW Annual Conference

Authors

Kendra Zagozda, Fort Worth ISD; Roberto Wheelock; Raziye Aghapour, The University of Texas at Arlington; Soulmaz Rahman Mohammadpour, The University of Texas at Arlington; Jaivardhan Sood, The University of Texas at Arlington; Erick C. Jones, The University of Texas at Arlington; Victoria C. P. Chen, The University of Texas at Arlington

Tagged Topics

Diversity

potential, respectively,from ATHENA. The current paper describes the implementation of the DACE process for the Summer2024 project, some findings, and the lesson plans developed by Zagozda to share more broadly to theASEE Community. MethodsAs described in Thomason et al.2, the DACE process provides an approach that middle/high schoolteachers can follow and translate to their classrooms. As a brief summary, DACE consists of thefollowing steps: 1. Calibration of the computer model(s) for the application of interest. 2. Design experiments to organize a set of computer model input parameter settings. 3. Execution of the computer model(s) to generate performance metric outputs. 4

Collection

2021 Northeast Section Meeting

Authors

Michael G. Schrlau

- or team-based learning activities.Acknowledgements I would like to thank the RIT Mechanical Engineering Heat Transfer course instructors, Drs.Rob Stevens, Michael Schertzer, and Ke Du, for their innovations and inspiring contributions toour Heat Transfer course offering and sharing their course experiences during the pandemic inthe Spring 2020 semester. I would also like to thank my RIT Mechanical Engineering colleagueand collaborator, Dr. Kathleen Lamkin-Kennard, for her insights and feedback during the writingof this conference paper.References[1] M. G. Schrlau, R. J. Stevens, and S. Schley, "Flipping Core Courses in the Undergraduate Mechanical Engineering Curriculum: Heat Transfer," Advances in Engineering Education

Collection

2020 ASEE North Midwest Section Annual Conference

Authors

Douglas W. Jacobson, Iowa State University of Science and Technology; Diane T. Rover, Iowa State University; Joseph Zambreno, Iowa State University of Science and Technology; Allegra Frickel, Iowa State University

)AbstractBackground: This virtual initiative, called Summer Engagement in Cyber UndergraduateResearch Experiences (SECURE), was established as a response to support students who mayhave lost summer internships and/or have financial hardships due to COVID-19. Several studentsin the program were NSF S-STEM scholars, a mix of computer engineering, cyber securityengineering, electrical engineering and software engineering students.Purpose/Hypothesis: The main question addressed by this initiative was whether we couldbuild a virtual undergraduate research experience that enabled students to apply their studies andknowledge similarly as they would in a traditional summer internship. Goals for the experienceincluded providing small-group mentoring as well as

Conference Session

Women in Engineering Division (WIED) Technical Session 7

Collection

2023 ASEE Annual Conference & Exposition

Authors

Macarena Becerra-Cid; Monica Quezada-Espinoza, Universidad Andres Bello, Santiago, Chile; Maria Elena Truyol, Universidad Andres Bello, Santiago, Chile

Tagged Topics

Diversity

Tagged Divisions

Women in Engineering Division (WIED)

, while a factorial analysis yielded an adjustment of factors to 4 dimensions with acumulative explanation percentage of 65 % (with a KMO equal to 0.812 and a Barlett's test ofsphericity equal to 0.000). The Exploratory Factor Analysis performed in this study wasPrincipal Component Analysis with Varimax rotation. Table 2 shows the items of eachdimension and the correspondent Cronbach´s Alpha.Table 2. Items by survey dimensions on sense of belonging, self-efficacy and perceived support from the institution. Dimensions Items Sense of belonging- 1. I feel comfortable asking a teacher for help when I don't understand the subject interactions

Conference Session

Graduate Studies Division (GSD) Technical Session 8: Professional Development for Graduate Students

Collection

2023 ASEE Annual Conference & Exposition

Authors

Sanjeev M Kavale, Arizona State University; Adam R. Carberry, Arizona State University

Tagged Divisions

Graduate Studies Division (GSD)

, New York: Guilford Pr., 1999, pp. 403–422.[3] R. Brooks, S. Brooks, and S. Goldstein, “The Power of Mindsets: Nurturing Engagement, Motivation, and Resilience in Students,” in Handbook of Research on Student Engagement, S. L. Christenson, A. L. Reschly, and C. Wylie, Eds., Boston, MA: Springer US, 2012, pp. 541–562. doi: 10.1007/978-1-4614-2018-7_26.[4] C. Dweck, “Implicit Theories,” in Handbook of Theories of Social Psychology, Sage, 2011, pp. 43–61. Accessed: Sep. 14, 2022. [Online]. Available: https://www.torrossa.com/en/resources/an/4912667[5] A. K. Gupta and V. Govindarajan, “Cultivating a global mindset,” Acad. Manag. Perspect., vol. 16, no. 1, pp. 116–126, Feb. 2002, doi: 10.5465/ame.2002.6640211.[6] C. S. Dweck

Conference Session

COED: Online and Remote Learning

Collection

2023 ASEE Annual Conference & Exposition

Authors

Rishi Sunny Gulati; Matthew West, University of Illinois, Urbana-Champaign; Craig Zilles, University of Illinois, Urbana-Champaign; Mariana Silva, University of Illinois, Urbana-Champaign

Tagged Topics

Diversity

Tagged Divisions

Computers in Education Division (COED)

offering online sections of courses to students that want the flexibilitythat they facilitate, if their primary concern is student performance. We found no statistically sig-nificant difference in the overall performance of students that elect to take a course online relativeto those that elect to take it in person. Taking courses online may, however, have a substantialnegative impact on a student’s sense of belonging. This effect is particularly pronounced for un-derrepresented minority students and first generation students, but not present in women.References [1] B. Bizot and S. Zweben, “Generation cs, three years later,” On the Internet at https://cra. org/generation-cs- three-years-later/(visited August 2019), 2019. [2] T. Camp, W. R

Conference Session

Equity, Culture & Social Justice Technical Session

Collection

2023 ASEE Annual Conference & Exposition

Authors

Sara Al Humidi; Alena Sloan; Andrea Atkins, University of Waterloo; Rania Al-Hammoud, University of Waterloo

Tagged Topics

Diversity

Tagged Divisions

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

, interest, and capability of faculty to teach a course.That said, even when a more diverse instructional team is assigned to teach a course, there arechallenges to be overcome which may prohibit instructors from trying new teaching methods orcourse structures.The first challenge to changing teaching methods and course structures is a two-pronged issue:there is an expectation and momentum towards keeping things the same as years past, as well asthe large amount of work to overturn the traditional teaching methods. In each of the examplesthat were given in this paper, the instructor(s) invested no small amount of effort in revising thecourse(s) to suit their designs. The time and energy required to do these revisions is not alwaysavailable to faculty

Conference Session

Committee on Educational Policy Presents: Pillars of Professional Development

Collection

2023 ASEE Annual Conference & Exposition

Authors

Kyle P. Kelly, Michigan State University; Secil Akinci-Ceylan, Iowa State University ; Xiangxiu Zhang; Kristen Sara Cetin, P.E., Michigan State University; Benjamin Ahn, Iowa State University of Science and Technology

Tagged Divisions

Civil Engineering Division (CIVIL)

Paper ID #37759Learning Styles Impact on Ill-Structured Problem Solving Processes ofEngineering Students, Faculty and ProfessionalsKyle P. Kelly, Michigan State UniversitySecil Akinci-Ceylan, Iowa State University Secil Akinci-Ceylan is a PhD student in Educational Technology in the School of Education at Iowa State University.Xiangxiu ZhangDr. Kristen Sara Cetin, P.E., Michigan State University Dr. Kristen S Cetin is an Associate Professor at Michigan State University in the Department of Civil and Environmental Engineering.Dr. Benjamin Ahn, The Ohio State University Dr. Benjamin Ahn is an Associate Professor at The Ohio