students’experience of the given project within the informal environment, as well as, their understandingtheir learning through this non-curricular setting. Open-ended questions were developed toencourage students’ natural statements about their experiences.The interview protocol included open-ended questions. The open-ended questions provided themeans to explore students’ thinking about their learning. Sample questions included “How wouldyou describe your process?” The purpose for this question was to understand how studentsthought about the design of their product (ABET student outcome [c]), problem solving (ABETstudent outcome [e]), and experimentation processes (ABET student outcome [b]). We did notspecifically prompt them to consider these processes
Paper ID #25506Student Perceptions of Interpersonal Skills Intertwined in an EngineeringClassroomMiss Carmen Angelica Carrion, Georgia Institute of Technology Doctoral studies in Science Education. Specifically in informal settings and through the application of problem based and project based learning.Prof. Joseph M. LeDoux, Georgia Institute of Technology Joe Le Doux is the Associate Chair for Undergraduate Learning and Experience in the Department of Biomedical Engineering at Georgia Tech and Emory University. Dr. Le Doux’s research interests in engineering education focus on problem-solving, diagrammatic reasoning, and on
mechanism for ensuring course consistency was the course andsubordinate lesson objectives, as approved by the department program director. In all cases, theseobjectives were not altered, either to increase or reduce content.Using lesson objectives as the guiding parameter, lesson restructuring followed a generallyconsistent pattern. First, any lessons under the 40 class format that were “drop periods” (used toprovide students with compensatory time) were eliminated from the schedule. Additionally,lessons used as working group sessions for larger projects and laboratories were rolled intoadjacent lessons that presented new material. It should be noted that this action reduced workinggroup session time from 55 minutes to a shortened period as allowed
design [25]. Table 1 outlines a list of validated creativityassessments and identifies them as measures of creative person, process or product.Attributes of assessment toolsThe intent of this project is not to judge assessment metrics, recognizing that differentapplications require different attributes and outcomes of assessment metrics. Instead, the intent isto provide guidelines for engineering educators and researchers interested in creativity forselecting appropriate metrics to be used in classrooms and research studies based on metricattributes. but rather to compile a These metrics are examined for applicability to science andengineering, ease of administration and completion, expertise required to score, cost toadminister, and time
) for the Academy for Excellence in Engineering Education (AE3) at UIUC. At the national level, she served as the Executive Director of the biomedical engineering honor society, Alpha Eta Mu Beta (2011-2017) and is an ABET evaluator (2018-present).Ms. Angela Wolters, University of Illinois, Urbana-Champaign Director, Women in EngineeringDr. Brian S. Woodard, University of Illinois, Urbana-Champaign Dr. Woodard received his Ph.D. in Aerospace Engineering from the University of Illinois at Urbana- Champaign in 2011. His Aerospace research interests currently focus on the effects of icing on the aero- dynamics of swept-wing aircraft. In engineering education, he is also interested in project-based learning and
the reporting of havinga close relative in the field. As the National Academy of Engineering asserts, engineering is not avery public facing discipline for the most part [2] and so while it is understandable that themajority of student who select engineering as a major may not fully understand all that theprofession entails, the researchers thought that having a relationship with an engineer might be amitigating factor in perceptions of the profession.Additionally, these results differed from the findings in Besterfield-Sacre, Moreno, Shuman, &Atman [3] that skill perceptions differed by gender. The current research did not reveal any suchdisparity in how females and males view engineering skills.LimitationsThis project was initiated in
Information Systems (MIS) from the department of Business Administration at the Faculty of Economics and Administrative Sciences at the Hashemite University, in Zarqa, Jordan, in 2007. His research interest are focused on Engineering management and systems engineering applica- tions in healthcare, manufacturing, operations management, business, and other industries, modeling and simulation of complex systems, distributed networked operations, and Engineering Education.Dr. John C. Kilburn Jr, Texas A&M International University John C. Kilburn Jr. is Associate Vice President for Research and Sponsored Projects and Professor of Sociology at Texas A&M International University. He has been awarded grant funds from the NSF
Paper ID #22630Fostering an Enriching Learning Experience: A Multisite Investigation of theEffects of Desktop Learning Modules on Students’ Learning Experiences inEngineering ClassroomsDr. Nathaniel Hunsu, University of Georgia Nathaniel Hunsu is currently an assistant professor of engineering education at the University of Georgia. He is affiliated with the Engineering Education Transformational Institute and the school electrical and computer engineering at the university. He holds a Bachelor’s degree in electronic and computer engi- neering from the Lagos State University in Nigeria, a Masters in Project management from the
, and associate professor of electrical engineering at Kettering University. Dr. Finelli’s current research interests include student resistance to active learning, faculty adoption of evidence-based teaching practices, the use of technology and innovative pedagogies on student learning and success, and the impact of a flexible classroom space on faculty teaching and student learning. She also led a project to develop a taxonomy for the field of engineering education research, and she was part of a team that studied ethical decision-making in engineering students. c American Society for Engineering Education, 2018 Impact of Prior Experiences on Future Participation in Active Learning
the role of peer mentoring andsocialization in most graduate departments 19–21. Other research at the graduate level has hinted atthe role that non-technical competencies have in the ability to complete, such as academicengineering writing 22. However, the psychological decision-making processes by which studentsdecide to leave their programs is still unknown and represents an enormous gap in the scholarship.Furthermore, it is important to employ creative sampling methods in order to study students whoare actually considering leaving or who have left their programs, but this has proven to be quitedifficult.The explicit objective of a broader project this paper represents is to capture and analyze thenarratives of engineering graduate student
and corporate instructors.Dr. Katharyn E. K. Nottis, Bucknell University Dr. Nottis is an Educational Psychologist and Professor of Education at Bucknell University. Her research has focused on meaningful learning in science and engineering education, approached from the perspec- tive of Human Constructivism. She has authored several publications and given numerous presentations on the generation of analogies, misconceptions, and facilitating learning in science and engineering educa- tion. She has been involved in collaborative research projects focused on conceptual learning in chemistry, chemical engineering, seismology, and astronomy.Dr. Margot A. Vigeant, Bucknell University Margot Vigeant is a professor of
constructive and developmentalfeedback. We also would like to thank former Teaching Assistants, Wenbo Shi, Anuj Mittal,and Anirudh Ramakrishna, of IE 341 Production Systems for their assistance in implementingthis project. Finally we would like to thank the Department of Industrial and ManufacturingSystems Engineering for generous support in the form of teaching assistants. References1. Hong, E., O'Neil, H. (1992), Instructional strategies to help learners build relevant mentalmodels in inferential statistics. Journal of Educational Psychology, 84, 150-159.2. Wheat, I. D. (2007), The feedback method of teaching macroeconomics: is it effective?System Dynamics Review, 23, 391-413.3. Felder, R. (2002), Learning
Charles B. Murphy Teaching Award (Purdue University), Purdue’s Help Students Learn Award, the Special Boilermaker Award (given here for contributions to undergraduate education) and is the 2011 recipient of the ASEE Mechanics Division’s Archie Higdon Distinguished Educator Award.Dr. David B. Nelson, Purdue University, West Lafayette David B. Nelson is Associate Director of the Center for Instructional Excellence at Purdue University. He received his Ph.D in World History from the University of California, Irvine in 2008 David has been involved in many educational research projects at Purdue, including published worked in the programming education, student engagement and academic performance in dynamics engineering
personal networks, as well those of our project advisory board members. Due toour focus on the participants’ personal testimonies of their unearned advantages anddisadvantages, we chose not to select or reject any participant based on our perception of theirrace, gender, sexual orientation or any other demographic characteristic. In an effort to be opento the unseen dimensions of participants’ experiences, we are not making assumptions abouttheir realities. To date, some participants revealed how they self-identify with traditionaldemographic characteristics during their testimony, while others did not.MethodsThroughout our entire research process, we utilize the quality management framework developedby Walther, Sochacka, and Kellam as a guide for
potential: A collaborative road map for increasing African-American women in engineering,” 2017. [Online]. Available: http://www.nsbe.org/getattachment/News- Media/NSBE-News/ignored-potential/NSBE-Ignored-Potential-Whitepaper-2-27- 17.PDF.aspx. [Accessed: 19-Mar-2018].[17] D. E. Z. Maldonado, R. Rhoads, and T. L. Buenavista, “The student-initiated retention project: Theoretical contributions and the role of self-empowerment,” Am. Educ. Res. J., vol. 42, no. 4, pp. 605–638, 2005.
adopted the Connor-Davidson Resilience Scale (CD-RISC) tomeasure resilience in a student resilience project that we have embarked upon. Although theinstrument is a highly studied and cited resilience measure, we found no empirical study thatdocuments the validity of its use with engineering students.The CD-RISC is a 25-item resilience instrument that measures the resilience construct and itscognates. Although the literature identifies the CD-RISC as a reliable measure, efforts to replicatethe factorial structure in different samples have not been successful [15, 16]. Because resiliencescores are evaluated under different risk conditions and ethnic settings, the interpretation of factorscould be construed differently among various populations
, 2002.[12] S. K. Al-Qudah and N. Romond, "An Outcome-Based Assessment of Engineering Writing Proficiency Classes," in IIE Annual Conference Proceedings, 2017, pp. 1205– 1211.[13] J. D. Gassert and L. Milkowski, "Using rubrics to evaluate engineering design and to assess program outcomes," in Proceedings of the ASEE 2005 Conference, 2005.[14] A. Cheville and M. S. Thompson, "Aligning design to ABET: Rubrics, portfolios, and project managers," in Proceedings of the ASEE 2014 Conference, Indianapolis, IN, 2014.[15] E. O. C. Mkpojiogu and A. Hussain, "Assessing Students’ Performance in Software Requirements Engineering Education Using Scoring Rubrics," in AIP Conference Proceedings 1891, 020092 2017.[16
University of Louisville’s NSF funded ATHENA ADVANCE initiative. Be- tween 2004 and 2008, she has co-organized the yearly WebKDD workshops on User Profiling and Web Usage Mining at the ACM KDD conference. She has served on the program committee member, track chair, or senior program committee of several Data mining, Big Data, and Artificial Intelligence con- ferences, including ACM KDD, WWW, RecSys, IEEE Big Data, ICDM, SDM, AAAI, etc. In summer 2015, she served as Technical Mentor/Project Lead at the Data Science for Social Good Fellowship, in the Center for Data Science and Public Policy at the University of Chicago. She is a member of ACM, ACM SigKDD, senior member of IEEE and IEEE-WIE. She is also on the
influence of students’ “likes” and “dislikes” ofvarious aspects of their engineering programs on the change in the level of commitment,persistence and, hence, doggedness.III. MethodologyThis study takes a longitudinal, multi-method approach to investigate the engineeringexperiences of undergraduate engineering students at four U.S. universities. Participatinginstitutions varied in their designations as public or private; research or technical orientations;the size of their undergraduate student populations; and the ratio of female to male students.Data for the larger study, of which this project represents a subset, was initiated in 2004. A total
example, for use in “enumerating various attributes” forthe ABET Criterion 3 outcomes5. In that project, each of the ABET outcomes [i.e., the Criterion3 (a) through (k)] was broken into a larger number of component parts, and each component part Page 13.658.2of an outcome was described as it might be addressed by a student operating at the various levelsof Bloom’s taxonomy. Verbs from their list 4 were used here in the writing of the performancecriteria because these verbs accurately describe levels of learning as described by Bloom’staxonomy.Taken together, the several performance criteria comprising a particular outcome indicate therequired or
Education, 29(3), 291-302.2. Macaskill, A., & Taylor, E. (2010). The development of a brief measure of learner autonomy in university students, Studies in Higher Education, 35(3), 351-359.3. Deakin Crick, R., Broadfoot, P., & Claxton, G. (2004). Developing an effective lifelong learning inventory: The ELLI project, Assessment in Education, 11, 247-271.4. Deakin Crick, R., & Yu, G. (2008). Assessing learning disposition: Is the Effective Lifelong Learning Inventory valid and reliable as a measurement tool? Educational Research, 50, 387-402.5. Guglielmino, L.M. (1977). Development of the Self-directed Learning Readiness Scale, Unpublished doctoral dissertation, University of Georgia, Dissertation Abstracts
. Teaching interests relate to the professional development of graduate engineering students and to leadership, policy, and change in science, technology, engineering, and mathematics education. Primary research projects explore the preparation of engineering doctoral students for careers in academia and industry and the development of Page 23.557.1 engineering education assessment tools. She is a National Science Foundation Faculty Early Career (CA- REER) award winner and is a recipient of a Presidential Early Career Award for Scientists and Engineers (PECASE). c American Society
student assessment techniques as well as looking at the socio- economic sustainability of educational institutions.Dr. Shelley Lorimer P.Eng., Grant MacEwan University Dr. Shelley Lorimer, P.Eng. is Chair of the Bachelor of Science in Engineering Transfer Program (BSEN) at Grant MacEwan University in Edmonton, Alberta. She teaches undergraduate courses in statics and dynamics, as well as courses in engineering professionalism. She is currently participating in a research project with Alberta Innovates – Technology Futures in the oil sands and hydrocarbon recovery group doing reservoir simulation of enhanced oil recovery processes. She has a Ph.D. in numerical modeling from the University of Alberta, also in Edmonton
. Advancing research in this area is consistent with an increased emphasison preparing students for professional practice5. Stakeholders’ varying definitions of keyabilities makes it more difficult to assess professional skills6 relative to technical outcomes, suchas ability to apply theories or formulae7-9. Conducting multi-institution studies on theseoutcomes has been a challenge because professional skill assessments have relied on a variety ofmeasures, including feedback from multiple sources such as faculty, peers, and self-reflections10,peer evaluations11, project rubrics12, and portfolio analyses13-17.Lattuca, Terenzini and Volkwein18 assessed outcomes across multiple institutions in anevaluation of the impact of new ABET accreditation
shown in Table 3. The scales we selected for this analysis wereincluded because they represent active learning and student centered teaching strategies. Table 3. Dependent variable scales with item components. The Cronbach’s alpha indicates the internal consistency reliability. Hands-on activities/assignments In-class, small-group learning Student-Centered Group projects Teaching (alpha=.70) In-class discussions Reverse-engineering exercises Case studies/real-world
). Art and artifact of children's designing: A situated cognition perspective. Journal of the Learning Sciences, 5(2), 129-166.5. Penner, D., Giles, N. D., Lehrer, R., & Schauble, L. (1997). Building functional models: Designing an elbow. Journal of Research in Science Teaching, 34(2), 125-143.6. Krajcik, J. S., & Blumenfeld, P. C. (2006). Project-based learning. In K. L. Sawyer (Ed.), The Cambridge handbook of the learning sciences (pp. 317-333). Cambridge: Cambridge University Press.7. Crismond, D. (2001). Learning and using science ideas when doing investigate-and-redesign tasks: A study of naive, novice, and expert designers doing constrained and scaffolded design work. Journal of Research in
modeling intervention was beingincluded in the course and in what ways modeling might help them with their own projects. Thisadded reflection allowed us to uncover students’ evolving conceptions, as well as how to modifythe implementation to make it clearer.Post-conceptions were later recorded approximately one month after the end of the interventionand prior to the start of the new term to identify changes that may or may not have occurred fromthe intervention.Data AnalysisAn open-coding approach was taken to identify emergent categories in the data. A single raterfirst read each student’s response to determine a set of categories compiled into a rubric. Therubric was then used to code each student’s response. A second rater then used the rubric
various phases of thecurriculum in order to simplify the process of evaluating the outcomes of the curriculum. The development of appropriate and comprehensive concept maps and correspondinginventories is a bit cumbersome, but once such development is completed then the inventory maybe repeatedly deployed to many students. The goal of this project is to develop enoughcomprehensive maps and inventories that this software is useful for a variety of applications at avariety of universities.Future Work The system currently only allows for the parsing of responses to multiple-choice ormultiple-answer questions. A useful extension to this tool would be the incorporation of naturallanguage processing techniques in order to process responses
. Even in cases where concepts were considered to be interrelated, theparticipants did so without sound reasoning. This paper reports the results of the longitudinalstudy and is an update to the interim findings reported in earlier conferences20, 21.The study completes the initial steps of an overall project aimed at formulating a strategy forimproving the teaching of service courses at the undergraduate level. The future steps willinvolve further collection of data and a subsequent intervention in the learning process toenhance student understanding. The intervention would require restructuring of the coursecontent, development of online modules and making better use of e-learning tools. We plan toimplement these interventions in a systematic
in enabling scientists to do research work using software de- veloped with the help of NCSA as well as teaching good software principles during this process. He is interested in software deployment and scaling software deployments from small research projects to larger installations with many users.Mr. Chirantan Mahipal, University of Illinois at Urbana-Champaign I’m a Computer Science grad student at University of Illinois, Urbana-Champaign, working under the mentorship of Prof. Lawrence Angrave. Prior to this, I was working as a Research Fellow at Microsoft Research in the Technology for Emerging Markets (TEM) group.Prof. Yun Huang, University of Illinois at Urbana-Champaign Dr. Yun Huang is faculty in the