, hiring committees and faculty mentors follow this implicit model of astraightforward academic pathway to the detriment of a diverse professoriate. We address thisby presenting an alternate model that better reflects alternate pathways that currently exist andcould be better encouraged and supported through infrastructure and social means.A Traditional Model of a Faculty CareerA traditional engineering faculty career moves from high school, to a bachelors degree, to a PhDprogram and then into a tenure track position, followed by promotions to associate and fullprofessor and then eventually a happy retirement, perhaps with an emeritus position to maintainan active mind until death. This is shown in Figure 2. In attempting to follow the
, were conducted intwo sections of a freshman engineering course at a large southwestern university in the UnitedStates. Evaluation data were collected regarding student knowledge gains and attitudes. Both theoverall gain in technical knowledge and positive attitudes toward the field of biogeotechnicalengineering were reflected in participant responses. With the advent and development of thisnew field, this work represents a pioneering effort in the biogeotechnical engineering educationspace. Looking ahead, the study could contribute toward longitudinal research in understandingthe best practices of interdisciplinary approaches to developing engineering instruction.IntroductionThis study is situated in the context of an interdisciplinary
English or mathematicsclassrooms. The advantage of the TAGS framework is that science/engineering content andpractice can be reflected together as integration. In contrast, the revised Bloom’s taxonomy doesnot have this advantage, because the integrative nature of science and engineering content andpractice is missing. Therefore, we chose TAGS in this research.Process of Design (POD), Engineering Literacy, and Technology Literacy The Process of Design (POD) is a framework derived from the key indicators identifiedby Moore, Glancy, Tank, Kersten, Smith, & Stohlmann12 within their Framework for QualityK-12 Engineering Education. It is a research-based, rigorously evaluated framework which mapsto the common design processes
working on better understanding of students’ learning and aspects of tech- nological and engineering philosophy and literacy. In particular how such literacy and competency are reflected in curricular and student activities. His interests also include Design and Engineering, the human side of engineering, new ways of teaching engineering in particular Electromagnetism and other classes that are mathematically driven. His research and activities also include on avenues to connect Product Design and Engineering Education in a synergetic way.Kate A Disney, Mission College Kate Disney has been teaching engineering at the community college level since 1990. Her interests are promoting greater gender and racial balance in
added new content to reflect the latest advances in theengineering discipline. The author was exposed to Model Based Systems Engineering (MBSE)at the 2010 International Council on Systems Engineering’s International Symposium inChicago; by 2011, he had begun the first steps to integrating MBSE into the MPD curriculum.Early attempts included the use of DoDAF (the Department of Defense Architecture Framework)in addition to SysML.3 However, DoDAF did not add sufficient incremental value to warrant itsuse; it has been dropped from the courses and both Systems Architecture and SystemsEngineering now focus solely on the use of SysML. Instead of requiring students to learn, inessence, two systems engineering languages, the courses instead focus on
be situatedin a world with social and material components, in which they interact. The sociomaterial worldshapes our students’ cognition (red arrows directed at subject), and then as part of their cognitiveprocess, they act in the world, reflecting their understanding back onto it (blue arrows).Figure 1: Situated cognition in a sociomaterial world. The subject, indicated by the head silhouette, issituated within and interacts with social and material agents within the world. The social and materialagents are intertwined such that they must be studied as a system, rather than individually. As one of thosesocial agents, the subject thinks, indicated by gears, about the world they are in, and the problem they wishto solve. This cognitive
Undergraduate Community Lifelong Colleges Learning Figure 1 - Promoting lifelong learningPre College Programs The FREEDM Center’s precollege program was revised in 2016 to reflect the vision andmission of the Center via modernizing the electric grid and to engage participants in engineeringeducation-problem solving, engineering
the engineering community of practice. What isunclear from the engineering identity research and related literature is if students are providedopportunities for reflective learning regarding their leadership experiences, the fourthenvironmental condition. As shown through the discussion of engineering identity this reflectionis typically left to chance at best or, at worst, actively discouraged through the viewpoint thatleadership is a “soft” skill not worthy of consideration in an engineering curriculum. Thequestion of incorporating effective reflective learning is central to the work underway.Moving engineering students from a positional to relational understanding of leadership has twobenefits: first, they should have a more stable sense
design ofretaining walls. Additionally, a reflection assignment was created to guide students in criticallyexamining what they have learned and where they feel they need to concentrate their efforts.Real-world homework assignments directly linked to the course learning objectives were devisedto scaffold student understanding of the key geotechnical concepts.To further deepen the understanding of the geotechnical engineering concepts and help with thedevelopment of teamwork and leadership skills, students were asked to design an appropriatefoundation system for a proposed two-story steel frame building structure on campus. Studentswere divided into teams of five, and teams were selected based upon overall academiccompetence and learning styles
Utilizing Modules as an Objective in ATE Projects”) to the Community CollegeJournal of Research and Practice and the manuscript has been published. The ATE-RAMPLeadership Team also submitted an abstract to the American Society for Engineering Education(ASEE) which has been accepted as a poster presentation at its Annual Meeting (June 2017 –Columbus, Ohio).E. AcknowledgementThis paper was made possible through funds from the National Science Foundation under grantnumbers DUE-1501828. Any opinions, findings, and conclusions or recommendations expressedin this paper are those of the authors and do not necessarily reflect the views of the NationalScience Foundation.
streamlining and strategizing to maximize efficiency to prepare for sustainabilityas our grant funding comes to an end.AcknowledgementsPrior versions of some of the information provided in this executive summary has been presentedin various forms in previous ASEE papers1,2,3,4,5 that address other aspects of this project. Thedata provided here has been updated to reflect the state of the project at the time of this writing.This project, entitled First-Year Initiatives for Retention Enhancement, is supported by theNational Science Foundation under Grant No. 0969382. Any opinions, findings, and conclusionsor recommendations expressed in this material are those of the authors and do not necessarilyreflect the views of the National Science Foundation.1
and do not necessarily reflect the views of the federal government.References[1] Oakes, W., Duffy, J., Jacobius, T., Linos, P., Lord, S., Schultz, W. W., & Smith, A. (2002). Service-learning inengineering. In Frontiers in Education, 2002. FIE 2002. 32nd Annual (Vol. 2, pp. F3A-F3A). IEEE.[2] Duffy, J., Tsang, E., & Lord, S. Service-learning in engineering: What why and how? ASEE Annual Conference 2000.[3] Eyler, J., & Giles Jr, D. E. (1999). Where's the Learning in Service-Learning? Jossey-Bass Higher and Adult EducationSeries.[4] Sax, L. J., Astin, A. W., & Avalos, J. (1999). Long-term effects of volunteerism during the undergraduate years. Thereview of higher education, 22(2), 187-202.[5] National Academy of Engineering
necessarily reflect the views of the National Science Foundation.Bibliography[1] Online tutorial available at:http://www.education.rec.ri.cmu.edu/products/cortex_video_trainer/[2] Online VEX parts available http://www.vexrobotics.com/vexedr[3] C. Ronald Kube and Eric Bonabeau, titled ‘Cooperative Transport of Ants and Robots’materials http://webdocs.cs.ualberta.ca/~kube/research.html[4 C. Ronald Kube and Eric Bonabeau, titled ‘Cooperative Transport of Ants and Robots’https://pdfs.semanticscholar.org/673e/763db5add397b7f29ebf796f82c4b54bd1c5.pdf[5] A Cooperative Architecture Based on Social Insects Iain Brookshaw, Dr. Tobias Lowhttp://www.araa.asn.au/acra/acra2013/papers/pap117s1-file1.pdf
this material are those of the author(s) and donot necessarily reflect the views of National Science Foundation.References[1] Wohlers Associates (2016). Wohlers Report 2016, ISBN 978-0-9913332-2-6, Available online: http://wohlersassociates.com/2016report.htm (last accessed: 2/5/2017).[2] Price Waterhouse and Coopers & Lybrand (PwC) (2016, April). 3D Printing comes of age in US industrial manufacturing. Available online: http://www.pwc.com/us/en/industrial-products/publications/assets/pwc-next- manufacturing-3d-printing-comes-of-age.pdf[3] International Data Corporation (IDC) (2016, January). Worldwide Semiannual 3D Printing Spending Guide. Available online: https://www.idc.com/getdoc.jsp
more Ecoflex 00-30. This less-elastic layer of therobot gripper creates the curve of the gripper when inflated; it is essential that the bottom andseal are airtight so that they inflate! Students use wax or parchment paper as a work surface (seeFigure 3). A piece of fabric, slightly larger than the finger or gripper, is placed on the worksurface and covered in Ecoflex. The silicone mixture should saturate the fabric (you can help itby spreading forcefully with a plastic knife) and evenly cover the area where the top half of therobot will sit. The top layer of liquid Ecoflex should be deep enough that there is good surfacecontact with the top of the gripper or finger—looking at an angle, the surface should be smoothand reflective, not pocked by
education that havealready occurred over the last number of years. That question was, “Are we actually making anyprogress?” This question addressed the core purpose of the workshop and raised the issue of thetrue opportunity for change. The workshop organizers considered this question and decided thatan unplanned reflective exercise would be valuable using the simple prompt, “What progresshave we made?” Each group of two representatives from the attending institutions was asked toreflect and comment on the progress made in the areas of the 5 themes identified earlier in theworkshop at either their home institution or nationally within the engineering educationlandscape.Responses to this simple prompt were illuminating and in many ways inspiring
reflection integration of academic/ student interactions. activities difficult. professional development activities. Weekly Site visits, service Many students expressed Continue site visits, meeting learning, and dissatisfaction with service learning, and activities professional diversity workshops, citing professional mentoring. mentoring helped that they were disconnected Encourage students to students develop from professional practice. interact directly with professional identity diverse
progressing at an accelerated pace in recent years. Most people perceiveAI as creating human-like robots or humanoids, it is more than that. AI is to use neural networktheories to simulate the human thinking processes by computers; to inject the human’s ability toscreening data, provide sound reasoning, to make self-reflection, and self-correction decisions tothe computers. According to TechTarget, artificial intelligence can be broken down into twomain categories: Weak AI (or called Machine Learning category), which is a machine’s ability tobe trained to perform specific tasks. Strong AI (or Deep Learning category) is the machine’sability when equipped with enough cognitive skills, to find solutions to problems on their own.Particular applications
National Science Foundation under GrantsNo. 1360987/1361028. Any opinions, findings, and conclusions or recommendations expressedin this material are those of the authors and do not necessarily reflect the views of the NationalScience Foundation.We would like to thank Amelito Enriquez for partnering with us to pursue this work. We wouldalso like to acknowledge the insight and contributions of advisory members Monica Cardella,Holly Matusovich, C. Judson King, and Mark Graham.References Cited 1. U.S. Department of Education, National Center for Education Statistics. (2016). Digest of Education Statistics, 2015 (NCES 2016-014), Chapter 3. 2. http://www.bestcolleges.com/features/49-best-colleges-for-older-students/; accessed: Feb 10
the student perspective and moving beyond traditionalinstitutional reporting begins to elucidate and provide evidence about the “true” engineeringgraduate experience. This increasingly accurate reflection of graduate experiences providesnovel insight into the experiences of students that have been traditionally ignored or unjustifiablylumped in with other students who share the title of graduate student.The initial findings of our qualitative analysis indicate that student perceptions of control and theability to utilize multiple resources to overcome barriers are fundamental to the successfuldevelopment of their identities and motivations. Students’ perceptions of control provide ameans of discerning the difficulty of a given choice or task
cohort, but they also have the PEEPS Support Team (i.e., Engineering Student Supportstaff, engineering faculty, AmeriCorps VISTA member, financial aid staff) available forassistance. We have multiple avenues of inquiry to the PEEPS experiences, such as quarterlycheck-ins (that are also individualized advising sessions), periodic reflections, and a end of theschool year focus group.Therefore, while the PEEPS project enables the cohort members to take certain courses together,study with one another, and socialize together, do they really support each other academicallyand emotionally to make a difference? How do the PEEPS Support Team and PEEPS activitieshelp students, if any? How can we take what we’ve been learning through the PEEPS project
Processing Technical Committee for the IEEE Circuits and Systems society. His research interests are in digital signal processing, speech processing, biometrics, pattern recognition and filter design.Nidhal Carla BouaynayaDr. Kevin D. Dahm, Rowan University Kevin Dahm is a Professor of Chemical Engineering at Rowan University. He earned his BS 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
staff.Furthermore, the statements are reconfirmed at least once annually or removed from thedatabase. This ensures that the statements are not outdated.As stated on the TRB website: An important function of the Transportation Research Board (TRB) is to stimulate research that addresses concerns, issues, or problems facing the transportation community. In support of this function, TRB Technical Activities standing committees identify, develop, and disseminate research need statements (RNS) for use by practitioners, researchers, and others. The RNS on this website have been developed by the technical committees.4To the authors’ knowledge, no other field maintains such an extensive research needs databasethat reflects the
detail todevelop a model that accurately reflects why and how students have difficulty with problemsolving in biomedical engineering design and (2) determine correlations between knowledgeretention and metacognitive awareness with problem solving success.The following research questions will be addressed: 1. How are problem solving schemas developed and used by students in biomedical engineering? How do these schemas differ for high and low performing students? 2. How do students’ problem solving abilities change during and throughout STEM courses? 3. How are students’ misconceptions related to knowledge retention and their mistakes with connecting different parts in problem schemas? 4. How is a students’ metacognitive
; Huggard, M. (2005). Computer Anxiety, Self-Efficacy, Computer Experience: An investigation throughout a Computer Science degree (pp. S2H–3–S2H–7). IEEE. https://doi.org/10.1109/FIE.2005.161224621. Turner, D. W. (2010). Qualitative Interview Design: A Practical Guide for Novice Investigators. The Qualitative Report, 15(3).22. Walther, J., Sochacka, N. W., & Kellam, N. N. (2013). Quality in Interpretive Engineering Education Research: Reflections on an Example Study. Journal of Engineering Education, 102(4), 626–659. https://doi.org/10.1002/jee.2002923. Patton, M. Q. (2014). Qualitative Research & Evaluation Methods: Integrating Theory and Practice (4 edition). Thousand Oaks, California: SAGE Publications, Inc.24
objective measure of the core reasoningskills needed for reflective decision making concerning what to believe or what to do.” [6]Initial Offerings and Course ModificationsThe original concept for the course included a hands-on component using Lego Mindstorms.The original conception also restricted the course to non-engineering majors [8], largely becauseengineering majors were thought to have a considerable advantage working with the LegoMindstorms. The hardware requirement imposed severe constraints on another important coursegoal, online delivery. Ultimately we decided not to implement the hands-on component. Thathad the side benefit of allowing us to open the course to all majors, including engineeringmajors. The course discussion boards have
students, as well as tothemselves. Furthermore, it shows that some of the REU students started to reflect about theeffectiveness of their “teaching” and of ways to further improve the benefit to other students inthe future.Given that the outreach activity took place close to the end of the school year, efforts to get thealready time-strapped elementary school teachers to complete a survey were unsuccessful.However, email feedback from the teachers indicated that they were very happy with theactivities as they saw their students engaged and excited about engineering and hands-onactivities. Efforts will be made in the future to obtain additional assessment data to gage theimpact on the K-5 students.All and all, this was a positive experience for all
IntroductionAlthough there are many standardized questionnaires used to assess students’ self-regulatorybehavior and motivation to learn, the MSLQ is one of the more widely used in general educationresearch [1, 2, 3]. The MSLQ is a self-report instrument specifically designed to assess students'motivational orientations and their use of different learning strategies. . By focusing on the rolesof both motivation and cognition during learning, the MSLQ reflects the research on self-regulated learning, which emphasizes the interface between motivation and cognition [4, 5].Prior research using the MSLQ has found relationships between constructs on its motivationalsubscales such as: intrinsic goals, extrinsic goals, task value, control of learning beliefs, self
global, h. economic, environmental, and societal context i. A recognition of the need for, and an ability to engage in life-long learning j. A knowledge of contemporary issues An ability to use the techniques, skills, and modern engineering tools necessary for engineering k. practice.In addition to ABET student outcomes, learning outcomes listed in the TUEE Phase 1 reportwere considered carefully because they reflect industry perspectives. Outcomes are rated byimportance and by extent to which they are observed in engineering graduates [1]. Becauseneither ABET nor TUEE outcomes were defined in terms that are consistently interpreted, theauthors developed definitions of fifteen top outcomes that
by choosing a different path of study. Phase II of the project begins in Fall 2017with data collection on self-regulated decision making, major fit, and self-regulated learning inorder to map real-world behaviors (major changes) to self-regulated decision-making theory20.AcknowledgementThis material is based upon work supported by the National Science Foundation (NSF) underGrant No. 1554491. Any opinions, findings, and conclusions or recommendations expressed inthis material are those of the author(s) and do not necessarily reflect the views of the NSF.References1. Pascarella ET, Terenzini PT. Predicting voluntary freshman year persistence/withdrawal behavior in a residential university: A path analytic validation of Tinto’s model. J