past several decades, there has been an increasing emphasis on the importance of engineerspossessing important professional skills, including global readiness or awareness. In 2004, theNational Academy of Engineering (NAE) described the Engineer of 2020 as being proficient in“interdisciplinary teams [with] globally diverse team members” (p. 55).1 As the NAE stated,“While certain basics of engineering will not change, the global economy and the way engineerswill work will reflect an ongoing evolution that began to gain momentum a decade ago.” (p. 4).Engineering graduates will be called to solve increasingly global problems and to work in teamsthat contain members who are either from international locations or are globally distributed.Across the
assignments, quizzes, and/or classexams – and a majority of the courses do not include such assessments – towards the final gradein courses is minor. The final exam generally contributes 70-90% to the final grade in each coursewith the assessment of the students’ practical skills assessed during laboratory exercises and/orprojects contributing the bulk of the remaining portion of the final course grade.Grading of the laboratory exercises is, in large part, carried out by reviewing students’ laboratorynotebooks. Thus, the grades reflect not only the inclusion of correct results from analyses,simulations, and measurements, but also appropriate and timely record of observations andconclusions.Questions on the final exams are expected to have
understand the implications of early design steps until much later in the course whichdoes not allow for reflection and improved learning. One of the key early design process steps isthe analysis of customer needs. Through experience it has been observed that students struggleto grasp the importance and nuance of this stage of design. This unfortunately can lead to furtherchurn, rework, and major schedule impacts later in the time-constrained capstone. This struggleis not limited to only the educational domain, but is a challenge for many in the engineeringdesign industry.4Without a clear understanding of what lies ahead for a student, there is a tendency to take eachstep only at face value, without appreciating the integrated fashion in which
approach reflects a foundationalmisalignment in educational philosophies resulting in what might provocatively be characterizedas “bait-and-switch.” The bait-and-switch characterization reflects a mismatch between theengagement logics embedded in most K-12 engineering education and the exclusionary logicsunderlying most university engineering education. While we acknowledge from the start thatuniversity engineering programs are increasingly emphasizing student engagement, the rapidexpansion of K-12 engineering programs has outpaced reforms in higher education aroundengagement, thereby magnifying the problems associated with engineering bait-and-switchexplored in this paper.In popular vernacular, bait-and-switch is often associated with fraud or
exploring topics using the four elements inKolb’s5 theory (concrete experience, reflective observation, abstract conceptualization, andactive experimentation). For each topic all the elements exist, but entry into Kolb’s learningcircle can begin at any one of the four elements16 with some elements overlapping one another.A typical sequence would be: (1) study engineering concepts in a classroom setting, (2) travel tolocation see the application of these engineering principles, (3) complete a computationalassignment that incorporates classroom learning and field observations, and (4) complete a Page 26.640.5reflective assignment and/or develop
framework nor any otherframework for care ethics has yet been used as a lens to explore empirical data collected to betterunderstand how care might be reflected in what engineers do and the ways they might think(especially in situations that one might reasonably expect caring qualities to be important, suchas in problems of a humanitarian or social justice nature).Tronto begins by framing care ethics as a practice and notes that there are essentially four phasesof any care process as commonly understood: “caring about (noticing the need to care in the firstplace), taking care of (assuming responsibility for care), care-giving (the actual work of care thatneeds to be done), and care-receiving (the response of that which is cared for to the care)” [2
questions are critical to understand if theavailability of LTS opportunities to engineering students are to continue to grow and flourish. Page 26.1078.16AcknowledgmentsThis material is based upon work supported by the National Science Foundation under DUEGrant Nos. 1022927, 1022883, 1022738, 1023022, and 1022831. Any opinions, findings, andconclusions or recommendations expressed in this material are those of the author(s) and do notnecessarily reflect the views of the National Science Foundation.References1. Pew Research Center. 2010. Millennials: A Portrait of Generation Next. http://www.pewresearch.org/millennials/ Accessed 1/23/2015.2
Environmentalengineering by Fall in spite of her FoK in mechanics. She was extremely frustrated with the step-by-step formulaic process that her teacher taught in statics as it removed all creativity and desirefor understanding of the physical phenomena. Realizing that most of her 18-yr old classmates areaccustomed to this process and “just listen and do it” [her tone of voice actually hints that theydo this uncritically], in contrast, she says: “I actually stop and wonder if this is the right thingthat I should be doing [amazing sense of ethical responsibility towards her knowledge] or if thisprocess is actually going to teach me what the professor wants to teach me [amazing sense ofmeta-cognition].” Realizing that her critical reflection takes more time and
both (i) incorrectanswers and (ii) correct answers supported only by explicitly worked out computations. Sinceour data come from a final exam, we expected that many students would do explicit calculationseven if they thought of a quick, heuristic answer, in order to get “full credit” or to be sure of theiranswers. Therefore, we coded answers as reflecting mathematical sense-making if any part of astudent’s solution included mathematical sense-making, whether or not the student also did acalculation. The details of the sense-making coding on each problem are described in the nextsub-section.Our preliminary coding scheme was generated by three of the authors by looking at a smallsubset of the student responses (N=25). Two authors then coded 45
dominantnarrative that success in engineering is impossible without being good at math. .The other prominent way we see Rachel counter the “suck at math” narrative is through culturaland circumstantial explanation. Instead of seeing math performance as a reflection of her Page 26.1582.7inherent ability, Rachel tells a story of how her high school preparation and experiencecontributed to her being inadequately prepared in math. This includes early instructionaldeficiencies (“going back to middle school I had really weak algebra training”), structuraldisadvantages (at her private all-girls’ school in Connecticut, even good students rarely tookcalculus), and
and had breakfastwith a faculty member from the Industrial and Systems Engineering department at theUniversity. The culminating event was a group trip to an art/science exhibit in New York City.ProcedureThis paper combines data from different sources in order to understand the different programcomponents that have impacted the 2012 and 2013 cohorts. Internal program evaluations fromthe office reflect student feedback about the effectiveness of the peer and industry-mentoringprogram. Data presented in this paper utilizing the AWE LAESE survey were part of a grantprovided by the Engineering Information Foundation to implement and evaluate the impact of asecond-year program for undergraduate women in engineering. Additionally, as part of a
found that focusing library instruction heavily on improving search skills showed a much higher percentage of students using quality resources in their bibliographies. These gains highlight the importance of reflection and continuous improvement within the process of information literacy instruction, assessment, and revision. Literature Review Information literacy skills are vital for undergraduate students and particularly critical in the 4,5,6engineering design process . To be successful the design process requires students to identify the scope of a project’s information needs, find quality research and information that both
steel bbeamfor a buillding structu ure using a sy ystematic appproach that ensures life safety and sserviceabilityy,but also to t understand exactly wh hat they are doing, what behavior deesign equatioons reflect, aandhow chan nging certainn parameterss will affect the t design soolution. At this level, sttructural dessignis all abo out systematiic application n of principlles and equaations, but thhe applicationn must be doonein an eduucated manneer.The decision to shift from a moree classical co ourse structuure to an invverted classrooom format inthe Strucctural Design n course disccussed in thiss paper was motivated bby a number of
experiences.MethodDesignThe quasi-experimental study design was developed to compare students from inverted sectionswith those in control sections (i.e., traditional course model). Treatment and control students Page 26.1253.2completed the same measures (e.g., content assessments and student attitude surveys) and facultymembers, who taught in both conditions, also completed reflection papers related to theirexperiences. The guiding research questions for the study and an overview of the assessmentmeasures are shown in Table 1 below (more details on assessment measures are included in asubsequent section of this paper). Table 1. Evaluation Questions and Outcome
or who lack maturity commonly takeadvantage of group-based work and ‘hitchhike’ on the efforts of their teammates.22 At the other Page 26.1266.3end of the spectrum, students who do not trust the capabilities of their teammates and feel a needto control situations often dominate their groups, taking on more of a role than is appropriate anddisallowing other members an opportunity to fully participate.23Students typically view overall group grades as unfair, and these grades must be adjusted forindividual performance.22 If grades do not reflect individual efforts, students cannot be heldaccountable, hard-working students may resent others, and
representation of engineering solutions to better reflect thedemographics of the U.S. population42. However, there are few actions targeting explicitly first-generation college students in engineering, this population is not specifically targeted in typicalrecruitment or outreach efforts, although this group has been growing in numbers and offersignificant opportunities to the nation’s engineering workforce23. First-generation collegestudents are more likely to be of Hispanic origin and historically, this group has not had as higheducational attainment as majority groups. In the years to come, this group is projected to growsignificantly and will soon outweigh other populations in college enrollment23. This increasewill likely result in not only more
and challenges of using robotics, in this case LEGOMindstorms NXT kits, as a manipulative to teach science content within the core scienceclassroom, particularly within less-than-optimal, but very common, types of school settings. Itwill cover the issues of materials management and constraints, resource and time requirements indifferent settings, the effects of variability in student prior knowledge, and the necessaryscaffolding of robotic-based activities to ensure that students focus adequately on science content.Data sources include design reflections and documentation, classroom observations, projectcommunications, teacher surveys and interviews, and teacher reports of curriculum enactment.IntroductionScience Learning Integrating Design
likely to experience more overt behaviors, while students andfaculty predominantly described comparatively subtle comments or behaviors that gave them asense that they did not belong as women in engineering. Below we provide examples of some ofthe different types of inappropriate behaviors that women encountered.All groups discussed receiving comments reflecting the belief that women are not engineers.For example, one female engineer stated, A lot of times, when women come to meetings, most of the time, the men think they're either the secretary, not an engineer, or they expect me to do the writing or something like that. Sometimes they don't talk to you or look at you. They talk at you, which is not good, or they assume
Page 26.302.2disciplinary skills. In particular, we highlight part of a report [2] which aims to develop theglobal dimension in shaping the future engineer and highlights the need and importance of theseskills in several areas.Generic Skills from [2]: 1. holistic thinking, critical enquiry, analysis and reflection 2. active learning and practical application 3. self-awareness and empathy 4. strong communication and listening skillsHence, the need to develop holistic thinking as an important skill for students and future citizensof the 21st century appears explicitly. Based on this request –to train students from basiceducation in this area- we decided to explore this part. Holistic thinking is also related toSystems Thinking
. • Part 2 focuses on the students’ experience, reflecting on how engineering is included in the Next Generation Science Standards. • Part 3 discusses forms of assessment required when students do open ended creative work, and the new relationship the teacher must have with the students. • Part 4 describes the next step, the many possibilities in the Engineering course, for students who successfully finish Intro to Engineering. • Part 5 describes the next frontier for this program, a preparation for younger students prior to Intro to Engineering.The story this program tells, like engineering itself, is very dynamic, so elements from all fivesections are subject to continuous improvement.Part 1 The design of a
Mean Change Z SignificantProblem Deviation Deviation 2013 2014 In Mean Value α = 0.01 2013 2014 P3 8.90 2.37 9.32 2.18 +0.42 4.06 YES P6 10.09 2.64 10.75 2.08 +0.66 5.77 YES P7 9.89 3.04 10.76 2.20 +0.87 6.56 YES P8 7.17 3.13 8.27 2.75 +1.1 8.09 YESTable 4 lists the topics covered in each exam problem and reflects the increased emphasis anarrays and loops
could examine other ways to view studentvolunteerism and the potential effects that those experiences have on the attitudes of personaland professional social responsibility in engineering students.AcknowledgementsThis material is based on work supported by the National Science Foundation under Grant#1158863. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation.Bibliography1 A. W. Astin, L. J. Vogelgesang, E. K. Ikeda and J. A. Yee, How Service Learning Affects Students, Los Angeles: Higher Education Research Institute, 2000.2 J. S. Eyler, D. E. Giles, C. M. Stenson and C. J. Gray, "At a Glace: What We
the characteristics thatlifelong learners would possess.Mourtos7 developed a different strategy for looking at the definition of lifelong learning and itsrelationship to the ABET student outcome. In his work, he divided the ABET outcome into thetwo parts of: • recognizing the need for lifelong learning and • the ability to engage in lifelong learning.Mourtos7 developed 14 attributes to measure lifelong learning in students in both of thesecategories. These measures were then used in course design to ensure that lifelong learning wasincluded and assessed in the curriculum. The methods of assessment included student work,student course reflections, and student surveys. Mourtos7 recognizes that the 14 attributes oflifelong learning
learning objectives. Also, designemphasis (cognitive objective) and proficiency with 3D-printing processes (skill learningobjective) are reflected in ABET General Criterion 3, Student Outcomes23 (c) “an ability todesign a system, component, or process to meet desired needs within realistic constraints such aseconomic, environmental, social, political, ethical, health and safety, manufacturability, andsustainability” and (k) “an ability to use the techniques, skills, and modern engineering toolsnecessary for engineering practice.” In addition, physical models that provide tactile, visual, andmanipulative feedback to learners have been implemented successfully in general education for along time.The 3D-printing lab includes nine inexpensive 3D
methods asan early version of the system was being prepared for use, and it was found that grading on thedigital rubrics was equivalent in speed or faster for all graders versus paper, but the specifictiming data was not retained once the decision to continue with development was made.Therefore, it is difficult to make quantitative statements about the improvements to efficiencyand reliability offered by the new computerized course tools. However, as the new systems offernew capabilities and eliminate certain classes of grading error entirely, some effects can bereported on qualitatively. In the cases, the effects and benefits reflect a consensus of the facultyand grading staff actively involved with the use of the computer tools.Computer Tool
knowledge required to initiatecreative project/problem based lessons reflecting the modern maker renaissance.Documented use of 3D printing in FabLabs and Makerspaces has provided someinsight,1,2 but these workshops are the first of their kind, so the survey responses providecrucial insight for improving future workshops and informing the maker community onthe use of 3D printers in K-12.RepRap 3D PrintersRepRap (self-replicating rapid prototyper) 3D printers3,4 are open-source 3D printerdesigns available for anyone to build. It is built on structural components that arethemselves produced by another RepRap; they are indeed self-replicating.5,6 Designs areproven and rapidly maturing and given that they are built with readily available parts,they are
predict the work students will likely produce. This information will provide helpful insights in how to present problems to best educate future engineers. Acknowledgements The authors would like to acknowledge funding and support from Tufts University Center for Engineering Education and Outreach, Tufts University Department of Mechanical Engineering, the Center of Science and Mathematics in Context at the University of Massachusetts Boston, USAID and The Sampoerna University . This work was also supported by the National Science Foundation DRK12 program, grant # DRL1020243, and grant # DRL1253344. Any opinions, findings, conclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect