deployed about a dozen more improved LynchBots to Iraq. His team also assisted in thedeployment of 84 TACMAV systems in 2005. Around that time he volunteered as a science advisor andworked at the Rapid Equipping Force during the summer of 2005 where he was exposed to a number ofunmanned systems technologies. His initial group composed of about 6 S&T grew to nearly 30 between2003 and 2010 as he transitioned from a Branch head to an acting Division Chief. In 2010-2012 he againwas selected to teach Mathematics at the United States Military Academy West Point. Upon returningto ARL’s Vehicle Technology Directorate from West Point he has continued his research on unmannedsystems under ARL’s Campaign for Maneuver as the Associate Director of Special
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
by a user with a web browser • Safe operational constraints in the event of network errorsSpecifications for the mobile telepresence robot’s design are based on the desire to make a robotsufficiently large to interact with humans, sufficiently small enough to navigate normally-sizedhallways, and that had a platform substantially sturdy and robust. The robot needed to be capableof driving forward at approximately 4.0 ft/s. The robot will also be expected to be able to turn in-place at 60 degrees per second and halt motion if impending collision is detected by the onboardsensors. This should allow for the robot to navigate through doorways and around corners whilestill being able to avoid a collision with both fixed and moving objects.IV
, theauthors will attempt to provide some insight on what worked, as well as what could useimprovement, through contrast of the three projects.Individual Team Member and Group Composition DynamicsProject 1Not surprisingly, Project 1’s team membership might be described as a ‘Dream Team.’Motivated Ph.D. students, with a combination of strong technical expertise, as well aspast, hands-on experience building and flying R/C aircraft, and buttressed by aparticipatory faculty member, created a tested solution that maximized both reliabilityand validity. What do these terms imply? In Martin’s book on Design Thinking, TheDesign of Business, [12] he develops an argument of the difficulty in creating solutionsthat are both reliable – function as intended; and
Through Humanistic And Global Perspectives. Paper presented at 1999 Annual Conference, Charlotte, North Carolina. https://peer.asee.org/7632.5. Parkhurst, R., & Moskal, B., & Lucena, J., & Bigley, T., & Downey, G., & Ruff, S. (2006, June), A Comparative Analysis Of Online And In Class Versions Of Engineering Cultures Paper presented at 2006 Annual Conference & Exposition, Chicago, Illinois. https://peer.asee.org/672.6. Jesiek, B. K., & Chang, Y., & Shen, Y., & Lin, J. J., & Hirleman, D., & Groll, E. A. (2011, June), International Research and Education in Engineering (IREE) 2010 China: Developing Globally Competent Engineering Researchers Paper presented at 2011 Annual
good.Instructors appear most satisfied with the ability of students to write for intended audience(s),provide appropriate data representations, and adhere to appropriate document formats, and leastsatisfied with their ability to develop coherent and grammatically correct writing. Table 9. In general, what is your perception of undergraduate students' writing skills in each of the following areas? Poor Fair Good Very Good Excellent MeanStatement (1) (2) (3) (4) (5)Appropriateness for 4 22 18 7 2 2.64intended audience(s)Appropriate data 4
. Content problematizing in this casewas unsuccessful in involving students in grappling with and reflecting on key issues of domainknowledge. It encouraged uninspired rote learning and failed to help student to construct aknowledge base to support problem solving, leading to substantial mismatches between teachingand learning objectives. Table III. Group Discussion Discourse s for Case ILine Verbal Discourse (Group FL, N=20) Content StyleNo. Code Code1 P2: Cut this into half? Add two? P SO2 P1" Yeah---Since this has different
Sustainability Education, 8.3. Gotch, C. M., Langfitt, Q., French, B. F., and Haselbach, L. (2015). “Determining Reliability Scores from an Energy Literacy Rubric.” Proceedings of 122nd ASEE Annual Conference & Exposition, Seattle, WA.4. Asif, M., and Muneer, T. (2007). “Energy supply, its demand and security issues for developed and emerging economies.” Renewable and Sustainable Energy Reviews, 11(7), 1388–1413.5. Turcotte, A., Moore, M. C., and Winter, J. (2012). Energy Literacy in Canada. School of Public Policy, University of Calgary.6. US Department of Energy (DOE). (2011). “Strategic Plan.” DOE/CF-0067.7. DeWaters, J. E., and Powers, S. E. (2011). “Energy literacy of secondary students in New York State (USA): A
developed based on the grant objectives and specificactivities. Additionally, all practicing teacher participants completed Horizon, Inc.’s LocalSystemic Change (LSC) survey during the first week of the program and in December of 2015.32The LSC teacher questionnaire tracks systemic change in teachers’ attitudes and perceptionsregarding their mathematics and/or science content preparedness, pedagogical preparedness,classroom practices, and principal support for math and science teaching. For the cohort,changes in the attitudes towards teaching were significantly higher at the 0.01 level. Mathteacher participants completed the Mathematics Teaching Efficacy and Belief Instrument orMTEBI.33 Science teacher participants completed the Science Teaching
FPGAthroughput capable of 28MS/s (when supporting both TX and RX) and a host maximumbandwidth similarly of 20MS/s (half-duplex) via the USB 3.0 interface. Hence, the hostconnection limits the maximum bandwidth to 20MHz of complex sampled I/Q data.Mid-Range SystemsMid-range systems, as with the full-featured systems, generally function as transceivers, withfairly wide sampling rates and spectral bands. However, these devices offer fewer choices interms of RF frontend configurations and host interfaces. Furthermore, mid-range systems relymore on host processing and do not offer stand-alone systems. However, these devices still offerimpressive SDR functionality and are fully compatible with the same tools as their moreexpensive counterparts at a
%), the best model for AIC, AICc, and BIC was to only include three variables in a linearmodel: Prior Semester GPA, Calculus II grade, and the Time of Day binary variable (e.g.,morning or afternoon – with morning students performing worse on Test 1). The summary ofthis information is provided in Tables 4-6. These results were consistent across all demographics(e.g., gender, race, age); however, we cannot report on whether these demographic results weresignificant for specific demographics due to sample size.In each of the Tables 4-6, the results provided include an analysis of variance (ANOVA), valuesfor the performance metrics (s, R2, Adjusted R2, AIC, AICc, and BIC), and parameter estimates.Since the resulting models were all linear, the
teacher training: A critical literature review, Journal of Turkish Science Education,vol. 2, pp.2-18.[3] Levin, T. and Wadmany, R. (2006). Teachers’ beliefs and practices in technology-basedclassrooms: A developmental view, Journal of Research on Technology in Education, vol. 39,pp.417-441.[4] Mcmahon, G., 2009. Critical thinking and ICT integration in a Western Australian secondaryschool. Educational Technology and Society, vol. 12, pp.269–281.[5] Fu, J. S. (2013). ICT in Education: A Critical Literature Review and Its Implications.International Journal of Education and Development using Information and CommunicationTechnology, 9(1), 112.[6] Lowther, D. L., Inan, F. A., Strahl, J. D. and Ross, S. M. (2008). Does technology
94.1 (2005): 103-120. 4. Bucciarelli, Louis L. Designing engineers. MIT press, 1994. 5. Sheppard, S. D. "A description of engineering: an essential backdrop for interpreting engineering education." Proceedings (CD), Mudd Design Workshop IV. 2003. 6. Savransky, Semyon D. Engineering of creativity: Introduction to TRIZ methodology of inventive problem solving. CRC Press, 2000. 7. Goel, Parveen S., and Nanua Singh. "Creativity and innovation in durable product development." Computers & Industrial Engineering 35.1 (1998): 5-8. 8. Suh, N. 2001. Axiomatic Design: Advances and Applications. Oxford University Press, UK. 9. Fellows, Sharon, et al. "Instructional tools for promoting self-directed learning skills
those practicalbarriers.There has been a shift in education abroad in recent decades. As part of the growing awarenessof Globalization, both students and employers have become more interested in education abroadas a means to develop intercultural skills, instead of simply going abroad to “soak up” the cultureor embarking upon a “Grand Tour” of Europe to become cosmopolitan. Within engineering, thisshift to an intercultural emphasis has been translated into the pursuit of “global competency.”The specific term for, and the component elements of, this set of knowledge and skills can vary,but Downey et al.’s definition of what it means provides a useful umbrella: global competencefor engineers involves the “knowledge, ability, and predisposition to
preferences is shown in Table 1. The value of nshown for each cohort is the total number of students registered (summing the numbers forMBTI preference pairs in the table yields a slightly lower value since not all students reportedtheir MBTI). The distribution of MBTI by gender is shown for all years in Table 2. Page 26.813.5Table 1: Distribution of MBTI Types by Cohort. I: Introversion, E: Extraversion, S: Sensing,N:iNtuition, T: Thinking, F: Feeling, J: Judging, P: Perceiving. Gender MBTICohort N M F I E S N T F J P 2013 121 91 30 66 54 64 56 92