Exposition, 2004.[2] Hertzberg, J., “Seeing Fluid Physics: Outcomes From a Course on Flow Visualization,” Bulletin of the American Physical Society, Paper # QE3, 55 (16), 2010.[3] Poon, M., Todd, J., Neilson, R., Grace, D., Hertzberg, J., “Saffman-Taylor Instability in a Hele-Shaw Cell,” Physics of Fluids, 16 (9), p. S9, 2004.[4] Settles, G. S., “On the Fluid Dynamicist as Artist,” Proceedings of the 12th International Symposium on Flow Visualization, Gottingen, Germany, 2006.[5] Kleine, H., Settles, G. S., “The Art of Shock Waves and Their Flow Fields,” Shock Waves, 17, pp. 291-307, 2008.[6] Samuel, M., Henley, J., and Shakerin, S., “Development of a Wet Wall: An Undergraduate Research Project,” Paper #37677
affiliates.References[1] J. M. Bekki, M. Huerta, J. S. London, D. Melton, M. Vigeant, and J. M. Williams, “Opinion: Why EM? The potential benefits of instilling an entrepreneurial mindset,” Advances in Engineering Education, vol. 7(1), 2, 2018.[2] C. J. Creed, E. M. Suuberg, and G. P. Crawford, “Engineering entrepreneurship: An example of a paradigm shift in engineering education,” Journal of Engineering Education, vol. 91(2), pp. 185-195, 2002. https://doi.org/10.1002/j.2168-9830.2002.tb00691.x[3] National Science Foundation, NSF Innovation Corps (I-Corps™), 2019. Available: https://www.nsf.gov/news/special_reports/i-corps/index.jsp[4] A. Huang-Saad, J. Fay, and L. Sheridan, “Closing the divide: Accelerating technology
when it successfully fulfills a human request and the individual has confidence thechatbot can perform well. Figure 1. Conceptual Framework for the User Interface Perceived Trust Efficacy of Chatbots for Future Faculty Mentoring. Adapted from “Enhancing User Experience with Conversational Agent for User Satisfaction Movie Recommendation: Effects of Self- Disclosure and Reciprocity,” by S. Y. Lee
learning approaches with ever-changing research-based and technologically instrumented means, transferring control over education from teachers to mangers of the bureaucracy.Therefore, engineering education is considered as a system that can be studied, controlled,optimized, and assessed. A classic example in this regard is the “pipeline” metaphor [10] that hasbeen widely used in the United States to understand and tackle the systematic challenges withretaining engineering students and recruiting underrepresented populations. Nearly allengineering education graduate programs in the United States are in engineering colleges,schools, or departments. Arizona State University (ASU)’s Engineering Education PhD Programis another good example
upon work supported by the National Science Foundation under Grant No.1741611 Encouraging Civil Engineering Retention through Community and Self-EfficacyBuilding. Any opinions, findings, and conclusions or recommendations expressed in this materialare those of the authors and do not necessarily reflect the views of the National ScienceFoundation.References[1] "Infrastructure Report Card." American Society of Civil Engineers. (accessed 2 Feb., 2019): https://www.infrastructurereportcard.org/.[2] S. Hatch, Diversity by Design: Guide to Fostering Diversity in the Civil Engineering Workplace. Reston, VA: American Society of Civil Engineers, 2008.[3] "Criteria for accrediting engineering programs 2019-2020." ABET. (accessed 2
increased when students have easyaccess to the learning management system.While our literature review provided us with general guidance on developing online courses, wefound no studies discussing online courses for Ph.D. students. We were particularly interested inPh.D. level courses that require reading, analysis, discussion, and writing with feedback.We hoped to answer three questions ourselves: (1) Given the Ph.D.’s students’ high levels ofmotivation, what kind of environment would foster their engagement in online courses? (2)How can an institution best support faculty members for designing, developing, and deliveringthis kind of course? (3) What are the students’ experiences in these courses?Developing Online Courses for the Graduate
highlight best practices and solution pathways that are moreconsistent with how the material was presented in class.- Engage with the students’ metacognitive responses! Answer questions that they bring up, orcomment on the good realizations that they have. If they write about needing to improve in acertain way, ask them later how this effort is going, and if they need any ideas.[1] P. C. Wankat, “The Role of Homework,” ASEE Conf. Proc., 2001.[2] P. C. Wankat and F. S. Oreovicz, “Testing, homework, and grading,” in Teaching Engineering, 1st ed., McGraw-Hill College, 1993, pp. 213–234.[3] W. Li, R. M. Bennett, T. Olsen, and R. McCord, “Engage Engineering Students In Homework: Attribution of Low Completion and Suggestions for
Society, 2015.[4] B. Swartz, S. B. Velegol, and J. A. Laman, “Three Approaches to Flipping CE Courses : Faculty Perspectives and Suggestions,” 120th ASEE Annu. Conf. Expo., 2013.[5] A. Lee, H. Zhu, and J. A. Middleton, “Effectiveness of flipped classroom for mechanics of materials,” ASEE’s 123rd Annu. Conf. Expo., no. May, 2016.[6] A. B. Hoxie, T. Shepard, and R. Feyen, “The Flipped Classroom : A Means to Reduce Cheating?,” 122nd ASEE Annu. Conf. Expo., no. Paper ID #11445, p. 16, 2015.[7] J. Laman, M. L. Brannon, and I. Mena, “Classroom Flip in a Senior-Level Engineering Course and Comparison to Previous Version,” in American Society for Engineering Education, 2012.[8] G. S. Mason, T. R. Shuman, and K
: Transforming undergraduate education for future research biologists”. Washington, DC: The National Academies Press, 2003.[2] F.A. Banakhr, M.J. Iqbal and N. Shaukat, "Active project based learning pedagogies: Learning hardware, software design and wireless sensor instrumentation," in 2018 IEEE Global Engineering Education Conference (EDUCON), Tenerife, Spain, April 17-20, 2018, pp. 1870-1874.[3] D. Perkins, “Beyond Understanding,” in Threshold Concepts Within the Disciplines, R. Land, J.H.F. Meyer, and J. Smith, Eds. Rotterdam: Sense Publishers, 2008, pp. 3-19.[4] D. Reeping, L. McNair, M. Wisnioski, A. Patrick, T. Martin, L. Lester, B. Knapp, and S. Harrison, “Using Threshold Concepts to Restructure an Electrical and Computer
thesuccessful results with the take-home tests and to increase student engagement with the coursematerials, the instructor will increase the number of take-home tests to three such that studentswould take one test before their midterm exam and the other two tests between the midterm andfinal exams.AcknowledgmentThe researcher acknowledges the assistance, mentoring and reflection on teaching sessionsoffered by the Center for Teaching and Learning at UC San Diego.ReferencesAhern, A., O’Connor, T., McRuairc, G., McNamara, M., & O’Donnell, D. (2012). Criticalthinking in the university curriculum - The impact on engineering education. Journal ofEngineering Education 37(2), 125-132.Baghdadchi, S., Hardesty, R., Hadjipieris, P. A., & Hargis, J. (2018
; 1 SB Mentor Tenets: Community & Legacy 3 SB Growth ID Empathy Activity SS Basic Mentoring Skills D A D a S Hardware Introduction a PS Mental Health Skills for Mentors y SS Hacker Card Game y SS Afternoon Social 2 PS Art of Listening 4 SS Afternoon SocialThe training delivered by the Bulls-EYE PRIDE PI. Each day of the training program and itsusefulness to culturally responsiveness is described as followsDay 1: The first day of the training begins with introductions. Mentors mention what major theyhave declared and do brief
. Shekar, "Project-based Learning in Engineering Design Education: Sharing Best Practices", https://peer.asee.org/22949, 2014. [Online]. Available: https://peer.asee.org/project-based-learning-in-engineering-design-education-sharing-best-pr actices. [Accessed: 01- Feb- 2019]. [3] . Haag, N. Hubele, A. Garcia, and K. McBeath, “Engineering undergraduate attrition and S contributing factors,” Social and Personality Psychology Compass, 01-Jan-1970. [Online]. Available: https://asu.pure.elsevier.com/en/publications/engineering-undergraduate-attrition-and-contri buting-factors. [Accessed: 01-Feb-2019]. [4] P. Howard and P. Wolfs, Balancing project based and lecture centric education in a restructured
Smith1 Smarr1 Gilbert1 jam323@ufl.edu kyla@cise.ufl.edu tiffan3@ufl.edu ssmarr@ufl.edu juan@ufl.edu 1 Department of Computer & Information Science & Engineering University of FloridaAbstractIn 2014, an American land-grant research university in the South began a new cycle of theNational Science Foundation (NSF) Scholarships in Science, Technology, Engineering, andMathematics (S–STEM) grant entitled the Human-Centered Computing Scholars (HCCS):Fostering a New Generation of Underrepresented and Financially Disadvantaged Researchers.This project was a continuation of NSF Grant No. 1060545, which supported students at
, June), Advising Engineering Students to the BestProgram: Perspective, Approaches, and Tools Paper presented at 2012 ASEE AnnualConference & Exposition, San Antonio, Texas. https://peer.asee.org/20898[8] Bonwell, C.C., and J. A. Eison, “Active Learning: Creating Eccitement in theClassroom,” ASHEERIC Higher Education Report No.1, George Washington University,Washington, DC , 1991.[9] Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., &Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering,and mathematics. Proceedings of the National Academy of Sciences, 111(23), 8410-8415.[10] Johnson, D., R., Johnson, and K. Smith, Active Learning: Cooperation in the CollegeClassroom
and programming willalternate between interactive content delivery and team-based work periods. Session participantswill apply design thinking to a narrowly-scoped project, guided by one or more facilitators.AcknowledgementsThe authors wish to thank T.J. Nguyen for his work on the CyberAmbassadors project; thevolunteers and staff members of TBP who make the EF program possible; and our partners at theNational Research Mentoring Network (NRMN) and the Center for the Improvement ofMentored Experiences in Research (CIMER). This material is based upon work supported by theNational Science Foundation under Grant No. 1730137. Any opinions, findings, and conclusionsor recommendations expressed in this material are those of the author(s) and do not
predefined projects, with the knowledge they had coming into the course and with theadditional resources.Qualitative responsesTable 4-6 lists some representative responses from the students open-ended statements.Table 4: Project Preference Qualitative Statements Given the three available options (RAD, AGP, and Pre-defined Projects), describe which project(s) you would prefer and why. 1. I prefer something where there are a set of rules and principles that I would follow. I do not feel confident in creating anything because of my current lack of technical knowledge. 2. AGP [prompt-based OEP] because there is structure but also it is open ended. 3. RAD [free-choice OEP] because it gives the best relevant experience to creating, designing
agree.While the overall intent of this self-grading exercise was to give students another learningopportunity as they completed their homework assignment, it was observed that some studentscompleted their self-grading during the break immediately before class on the day that the gradedassignment was due; in retrospect, this defeated the purpose of the self-grading exercise. As analternative, students could be asked to qualitatively explain why a mistake was made, if oneoccurred. This tactic might be more conductive to learning; if the student is not grasping the rootcause(s) associated with errors in thinking then the effectiveness of this approach misses itsintended objective.ConclusionsA homework assignment represents one method to gauge student
, When, Why, and How” behind participants’ initial statements andask them to describe differences and similarities among their own statements.AcknowledgementsThis project has been supported by a Marie Sklodowska-Curie Actions (MSCA) individualfellowship from the European Union (Call identifier: H2020-MSCA-IF-2016, Project 747069,Project acronym: DesignEng, Project title: Designing Engineers: Harnessing the Power of DesignProjects to Spur Cognitive and Epistemological Development of STEM Students) and UCL’sCentre for Engineering Education.ReferencesÅkerlind, G. S. (2012). Variation and commonality in phenomenographic research methods. Higher Education Research & Development, 31(1), 115-127.Anthony, K. H. (1991). Design juries on trial: The
felt they did not have enoughinformation to interpret them. During their exit interview, researchers shared with faculty members theprofiles that emerged from the cluster analysis and discussed the findings from the TPI and COPUSobservations. They were also given references to articles on Stains et al.’s (2018) profile analysis for moreinformation on each profile. Faculty clearly placed value on the clusters, but longed for more detail.For example, one faculty member said,” [It was] nice to know I wasn’t in cluster 1 or 2, but how to interpret…?...I don’t know that I want every class period to be cluster 7….[It’s] not clear yet on the differences between the profiles other than student centered is better than interactive or didactic. I’m
, M.D.. Journal of Documentation, 2003, 59, 647-672.(4) Mayer, R.E.; Bove, W.; Bryman, A.; Mars, R.; Tapangco, L. Journal of Educational Psychology1996, 88, 64-73.(5) McGrath, M.B.; Brown, J.R. IEEE Computer Graphics and Applications, 2005, 25, 56-63.(6) Arnheim, R. Visual Thinking. Berkeley: University of California Press, 1969.(7) González-Espada, W. J. Revista Electrónica de Enseñanza de las Ciencias, 2003, 2, 58-66.(8) McCloud, S. Understanding Comics. Northampton: Tundra Publishing, 1993.(9) Hanson, D. J. “Gains In Chemistry Grads Persist”. Chemical and Engineering News, 2009, vol. 87,47, 38-48.(10) Yoder, B.L., “Engineering by the numbers,” College profiles printed by the Amer. Soc. Eng.Educ., Washington, DC, USA, 2011.(11) Willingham
, October 2017. She and her co-authors also received the AIST Josef S. Kapitan Award in 2005, 2016, and 2017, the AIST Computer Applications Best Paper award in 2006 and 2017, the 2017 AIST Hunt-Kelly Outstanding Paper Award – First Place, and the 2014 International Thermoelectric Society Outstanding Poster Award, She was named ”One of 12 Most Influential over 50” by Northwest Indiana Business Quar- terly Magazine in 2014. Dr. Zhou received the awards of Outstanding Faculty in Teaching, Research, and Engagement at Purdue University Northwest. Dr. Zhou has been a Fellow of the American Society of Mechanical Engineers since 2003. Dr. Zhou has been very active in professional societies. She has served as the chair of the
one that maynever reach a final resting state, however, it is accurate, scalable, and defendable, all of which areof utmost importance in assessment today.References [1] C. E. Kulkarni, R. Socher, M. S. Bernstein, and S. R. Klemmer, “Scaling short-answer grading by combining peer assessment with algorithmic scoring,” in Proceedings of the first ACM conference on Learning@ scale conference. ACM, 2014, pp. 99–108. [2] M. Zhang, “Contrasting automated and human scoring of essays,” R & D Connections, vol. 21, no. 2, 2013. [3] K. N. Ballantyne, G. Edmond, and B. Found, “Peer review in forensic science,” Forensic science international, vol. 277, pp. 66–76, 2017. [4] C. H. Davis, B. L. Bass, K. E. Behrns, K. D. Lillemoe, O. J
for addressing Sustainability: a = 0.88 global resource scarcity in my work/career. Table 3: Effect Coding of Independent Variables for Linear Regression Models Characteristic Variable Effect Coding Name(s) Engineering Business = -1; Education = -1; Environment = -1 Business Type of Major Business Business = +1; Education = 0; Environment = 0 Education Education Business = 0; Education = +1; Environment = 0 Environment
appropriate to its solution; (2) design, implement, and evaluate a computer-basedsystem or program to meet desired needs; and (3) develop software system(s) within teams.4.3.2 EFFECT Learning Objectives and OutcomesIn the context of improving lane departure guidance systems, students will learn aboutrequirements for the sensing system on driverless vehicles (e.g., drones) and the embeddedvehicle control system (e.g., drone controller). Through hands-on experimentation, students willdevelop an understanding of the necessary specifications for the sensors and vehicle controlsystem to ensure that driverless vehicles can safely navigate complex topologies and physicalenvironments. Specifically, students were required to inquire and study the
. Recognition was also central in Barton et al.’s [8]longitudinal study tracing the identity work of girls from nondominant backgrounds. They foundthat girls imagined for themselves possible futures in science when their identity work wasrecognized and scaffolded while they engaged with science in formal and informal learningsettings. These studies contribute to a growing realization of the complex work girls face inconstructing and sustaining a disciplinary identity in STEM. These researchers, along withothers, call for further studies to enrich our understanding of the aspects of identity construction,especially with regards to the interaction between gender, ethnicity, and STEM in the transitionto adulthood.One avenue that holds promise to transform
Development, vol. 72, pp. 187-206, 2001.[9] M. K. Ponton, J. H. Edmister, L. S. Ukeiley, and J. M. Seiner, "Understanding the Role of Self- Efficacy in Engineering Education," Journal of Engineering Education, vol. 90, pp. 247-251, 2001.[10] A. R. Carberry, H. S. Lee, and M. W. Ohland, "Measuring engineering design self‐efficacy," Journal of Engineering Education, vol. 99, pp. 71-79, 2010.[11] T. D. Fantz, T. J. Siller, and M. A. Demiranda, "Pre-Collegiate Factors Influencing the Self-Efficacy of Engineering Students," Journal of Engineering Education, vol. 100, pp. 604-623, 2011.[12] H. M. Matusovich, R. A. Streveler, and R. L. Miller, "Why Do Students Choose Engineering? A Qualitative, Longitudinal Investigation of
aspirations in an urban community college: Differences between immigrant and native student groups. Community College Review, 37(3), 209-242. [9] Donaldson, J.F., and Graham, S. (1999). A model of college outcomes for adults. Adult Education Quarterly, 50(1), 24-40. [10] Goldrick-Rab, S. (2010). Challenges and opportunities for improving community college student success. Review of Educational Research, 80(3), 437-469. [11] National Center for Education Statistics (2018). Digest of Education Statistics. Retrieved from https://nces.ed.gov/programs/digest/d17/tables/dt17_104.80asp?current=yes. [12] US Census Bureau (2018). Educational Attainment. Retrieved from https://www.census.gov/topics/education/educational
: An emerging paradigm for educational inquiry,” Educ. Res., vol. 32, no. 1, pp. 5–8, 2003.[6] S. Barab and K. Squire, “Design-based research : Putting a stake in the ground,” J. Learn. Sci., vol. 13, no. 1, pp. 1–14, 2004.[7] L. T. Louca and Z. C. Zacharia, “Modeling-based learning in science education: Cognitive, metacognitive, social, material and epistemological contributions,” Educ. Rev., vol. 64, no. 4, pp. 471–492, 2012.[8] M. Kapur and K. Bielaczyc, “Designing for productive failure,” J. Learn. Sci., vol. 21, no. 1, pp. 45–83, 2012.[9] M. Kapur, “Productive failure,” Cogn. Instr., vol. 26, no. 3, pp. 379–424, 2008.[10] H. A. Diefes-Dux, T. Moore, J. Zawojewski, P. K. Imbrie, and D. Follman, “A framework