specific industries- could offerimportant linkages for the development of industrial affiliate programs, co-op activities, summertraining opportunities, and employment opportunities for new graduates. They may also providenew ideas for senior design projects, topics for graduate theses, or render help in theestablishment of collaborative research programs.When a choice has been made and the candidate has accepted, it is important that he/ she feelswelcome and be assisted in becoming familiar with his/ her new surroundings. To expedite theprocess, new adjuncts should sit together with their new colleagues and go over all relevantmatters related to their assigned tasks, ranging from course objectives, to teaching logistics, andincluding prevailing
agents of the social norms that privilegewhite students in engineering classrooms and organizations. In a study of African-Americanmale experiences on multiracial student engineering teams, Cross and colleagues found that thesocial norms of the engineering community decreased African-American students’ sense ofbelonging.18 Contributing factors included but were not limited to indifferent faculty interactions.The authors recommended that multiracial team projects should be monitored carefully byfaculty to ensure positive experiences of all team members.A study of Asian and Asian-American students in engineering showed that many students facedstereotypes from peers and faculty that detrimentally impacted their education, including that ofbeing the
helping students form studygroups9. The STEP retention project has resulted in an increase in 2nd-year retention rate toCEAS from a baseline of 57.4% (averaged 2000-2004) to 67.6% (averaged 2005-2009), and 5-year graduation and 6-year continuation rate in CEAS from a baseline of 32.3% to 42.4%.Details on how the CEAS-STEP cohorts are constructed for first-year students can be foundelsewhere10, 11.In Fall 2013, the CEAS-EXEP Cohort program was created. Students in CEAS-EXEP Cohortwere enrolled in the same section of Algebra II, and a First-Year Experience (FYE 2100)seminar taught by a CEAS academic advisor. Depending on a student’s intended CEAS major, athird course – Engineering Graphics – was added to the CEAS-EXEP Cohort schedule. Inaddition
was effectively over—quite a change from thehours or days of sitting that a figure model could expect to endure in a traditional sculptingstudio.The 24 trans-planar slices were then projected, one by one, onto a screen using a magic lantern.21Artisans and shop workers would trace the outline of the silhouette, using a mechanical devicethat would carve the contours into a piece of clay. Rotating the clay and repeating the process 23times resulted in a mostly-defined bust that featured a photographically-exact representation ofthe subject. Workers in Willéme’s shop would add final touches to the bust, mostly in order tosmooth out the gaps in-between the 24 carved slices, and often to cast the sculpt in a layer ofbronze. Importantly, these final
declare a pre-major.Additionally, some students may be exposed to the different engineering disciplines throughliving-learning communities, student project teams, and other organizations. These types ofexposures are beyond the first-year engineering program, but they may have a significantinfluence in students’ major selection and their learning more broadly.In order to create a representative data set for the disciplines, responses were only analyzed if thestudent answered all three of the surveys. This could be done as students were given an identifierthat persisted throughout each survey. Through the identifiers, we were able to not only track themovements of the students as a group, but the identifiers allowed the students to beindependently
-year engineering classes, and theinternational module (i.e., connecting to a class). For example, one student referenced a projectthat was assigned in the first year engineering program during the visit to Lamborghini:“Lamborghini used a line tracking technology to navigate small robots around the factory and itwas the same line tracking technology we used in 1st year engineering.” Another studentconnected the group's solar-powered boat tour to a class project from the previous semester: “From research I've done on solar panels for two classes second semester I knew that most solar panels only run on about 30% efficiency which is not very cost effective. The man who was telling us about the boat told us that this boat ran
Wisconsin, Milwaukee. Papadopoulos has diverse research and teaching interests in structural mechanics, biomechanics, appropri- ate technology, engineering ethics, and engineering education. He is PI of two NSF-sponsored research projects and is co-author of Lying by Approximation: The Truth about Finite Element Analysis. Pa- padopoulos is currently Chair of the ASEE Mechanics Division and serves on numerous committees at UPRM that relate to undergraduate and graduate education.Dr. Aidsa I. Santiago Roman, University of Puerto Rico, Mayaguez Campus Aidsa I. Santiago-Rom´an is an Associated Professor in the General Engineering Department at the Uni- versity of Puerto Rico, Mayaguez Campus (UPRM). Dr. Santiago earned a BA
Stakeholder Meetings Faculty and administration meet with program advisory board. Interviews Faculty chair meets individually with senior students to discuss educational experience. Course Related Data Exams, quizzes, assignments, projects, presentations Instructor Objective Evaluation Course instructors complete self-assessment of the achievement of outcomes.Figure 2. The mapping of Perceptions, Ability, and Behavior dimensions onto outcome (i)We organized our findings into what we call the “Curriculum-Outcomes Matrix.” This matrix(Figures 3–5) organizes the items identified throughout the self-studies into similar components
challenges. The focus of this research project is to explore several factorsto help analyze and distinguish the most efficient wind turbine blade designs. The researcherstest the design the wind turbine blades by implementing two methods; Computational FluidDynamic analysis and 3-D printed prototype testing using Windlab laboratory apparatus. Thedata and analysis helps determine how to maximize the power extraction from wind energy. Thevalue of undergraduate research experience is highlighted.KeywordsLow speed wind turbine, blade design, Computational Fluid Dynamic analysis.Introduction and TheoryWind turbine energy methods and the usage of electrical power have been in practice for morethan a century. Wind energy has been investigated heavily due
factors such as: the ability to extract the key technical concept of the paper, thetechnical knowledge of the subject matter, proficiency and confidence in presenting, and thequality of the written report. Due to the hands-on nature of educational strategy, the laboratorycomponent is an integral part of any course offered in the SoT, and the EM course is noexception. Every week, the course-enrolled students have an opportunity to apply the knowledgethey gain in the classroom to the industrial equipment. By the end of the course, students have atleast 33 hours of hands-on activities. The knowledge gained via theoretical and practicalexercises is reinforced by the computer projects utilizing MATLAB simulation software.In 2009, the first attempt at
DLR_School_Lab RWTHAachen, is further developed in the IMA/ZLW & IfU institute cluster’s training model [13]. 3. Related projects in the field of extracurricular learning venuesThere is increasing interest in extracurricular learning venues where students and scientistscan promote and deepen interests in their specific field. In the United States and Japan, forexample, there are some excellent universities concerned with robotic science e.g. theUniversity of California at Berkeley, the Robotic Society of Japan, and the University ofYork. However, in contrast to these laboratories, which are exclusively available for seniorresearchers or at least PhD students, the DLR School Labs focus on a much younger targetaudience. The project aims to awaken
employing the ExCEEd Teaching Model highly, many, if not most,of them were not retaining essential information from one course to the next. The bestexplanation for the students’ lack of retention was that they were only minimally engaged withthe material. Analysis of student time survey data consistently showed that students spent largeamounts of time cramming for tests and major projects immediately before the event, smalleramounts of time completing homework the night before it was due, and almost no time in dailypreparation.To rectify this issue various instructors developed a variety of different initiatives. Problem SetZero (1) experimented with making the first homework assignment in a given class a review ofthe materials from the previous
-based solution to a problem (question 5, av. =3.93/5.00) and many felt (question 4, av. = 3.93/5.00) that there was a high likelihood theywould directly apply what they learned in a future project (e.g. senior capstone project,employment, etc.). Finally, the survey shows that students left the course with an increasedenthusiasm for the Internet-of-Things as well as the desire to continue study of this topics afterthe conclusion of the course (question 8, av. = 4.28/5.00).Figure 5. Student Opinion Survey of Course Content and Attainment of Learning Objectives5. Discussion and Future WorkThe assessment results of section 4 show that the course was successful in providing studentswith a solid technical foundation for the Internet-of-Things. By way
as a social experience particularly in terms of gender and race among underrepresented college students in STEM (science, technology, engineering, and mathematics). He has presented his scholarship at research conferences organized by the American Educational Research Association, Association for the Study of Higher Education, and Out in STEM Incorporated. Luis holds professional experience in various STEM student support initiatives at Rutgers University including the STEM Talent Expansion Program, Upward Bound Math-Science, and Project Advancing Graduate Edu- cation. He is a certified K-12 mathematics teacher in New Jersey with a Master’s degree in Mathematics Education and Bachelor’s degree in Mathematics from
construction education and training oppor- tunities, emphasizing construction-based workforce development. He has contributed to, and developed curriculum for, construction management training programs in Mexico, Egypt, and Tunisia. He is pas- sionate about connecting underrepresented and unemployed populations with sustainable employment opportunities in the construction industry. Jon has over five years of experience in construction and his commercial project management experience focused on core and shell office building projects and historic building restoration/rehabilitation in Washington DC Page 26.732.1
Hrastinski, KTH Royal Institute of Technology Stefan Hrastinski is Associate Professor at the The School of Education and Communication in Engineer- ing Science, KTH Royal Institute of Technology, and Visiting Professor with specialization in e-Learning, Mid Sweden University. His research focuses on online learning and collaboration in educational and or- ganizational settings. Stefan has conducted research and development projects across various contexts, including higher education, school settings, companies, municipalities and the public sector. He teaches courses in e-learning, and supervise theses on bachelor, master and Ph.D. level.Prof. Inga-Britt - Skogh
spring 2014 panels as a service project as achapter officer served as a member of the panel voluntarily, not for credit in CE 3311. Thestudent chapter participated by drafting the survey given to students (survey was reviewed by theinstructor and adjusted slightly) that is presented later in this paper, administering the survey, andproviding the results after grades had been submitted to the instructor.3.0 AssessmentsSchilling et al.5 describes a taxonomy based approach (i.e. to assign a given written commentinto one or more categories) to qualitatively assess written comments on student evaluations. Asimilar approach was used in a few instances for the assessments that follow.3.1 Student EvaluationsFigure 3 provides a summary of
Paper ID #12638Honing Interpersonal Communication Skills for Difficult Situations: Evi-dence for the Effectiveness of an Online Instructional ResourceMs. Amy Elizabeth Dawson, Arizona State University Amy Dawson, M.A., is a doctoral student in the Counseling Psychology program at Arizona State Uni- versity. Amy is also a research assistant for the NSF funded CareerWISE project housed at ASU.Prof. Bianca L. Bernstein, Arizona State University Bianca L. Bernstein, Ph.D. is Professor of Counseling and Counseling Psychology in the College of Let- ters and Sciences at Arizona State University. Dr. Bernstein is Principal Investigator
various active learning methods. Forexample, only 9 percent said they never had students discuss problems in pairs or groups, and Page 26.890.3only 18 percent never had students work on problems sets or projects in pairs or small groups.There are some important limitations of this work. First, it is unclear the extent to whichinstructor self-reporting is accurate (as noted by the author) or the extent to which therespondents were representative of all instructors. Responses might be more likely from facultyactively engaged in trying to teach statics most effectively. The quality of implementation of thevarious methods varies widely. As shown in a
course, students learnthe basic skills necessary for visual technical communications and spatial visualization. Topicsinclude engineering sketching and drafting, orthographic projection of multi, sectional, andauxiliary views, dimensioning, tolerances (the first half of the semester), and solid modelingusing the Computer Aided Design (CAD) tools (the rest of the semester). In a typical class, theinstructor delivers a short lecture followed by a class activity based on the lecture. For example,in a class that teaches multi-view of objects, the class activity is to derive the multi-view for agiven set of objects on an assignment sheet. The instructor helps the students during this activity.Once they complete the class activity, they are allowed to
Page 24.1357.6solution steps while explanations and commentary may be more efficiently conveyed by voiceinstead of by writing or projecting them on the screen. While the absence of voice narrationfrom a screencast may not impede student learning, do students consider voice narration asadded value when it comes to their learning?When asked about the importance of including explanatory narration in the screencasts and thecompleteness of this narration, the students rated these aspects as being important to theirlearning. According to the survey results in Figure 4, the students almost unanimously (56students, or 97%) agreed that including some level of narration is important to their learning,with 71% (40) of these students rating narration as
Paper ID #13484”It’s Too Hard,” to ”I Get It!” – Engaging Developmental Science as a Tool toTransform First Year Engineering EducationProf. Carmela Cristina Amato-Wierda, University of New Hampshire Carmela Amato-Wierda is Associate Professor of Materials Science at the University of New Hampshire. She shifted her research focus several years ago to the area of cognitive development of STEM concepts and practices in grades K-16. She has held NSF funded curriculum projects in General Chemistry and Materials Science, and has recently developed two science courses for non-scientists, titled: The Science of Stuff and
were achieving their goals.”4 This challenge led to some programs being dropped fromconsideration due to a lack of documentation and evaluation data.4 In addition, minorityretention issues in STEM are complex phenomena, compounding the research and evaluationchallenge.6 While the need for more qualitative studies to understand these complex nuances isevident, there is also a need for more rigorous quantitative work. For example, in a review of 28Louis Stokes Alliances for Minority Participation (LSAMP) projects, although studies wereprimarily quantitative or mixed methods designs, the focus was on participation numbers andgraduation rates of URMs in STEM with no experimental designs.6Tinto7 argues for improved assessment and evaluation efforts
exam was administered. Improved security measures haveprevented additional problems. Development of new problem resources puts considerabledemands on instructor time. During the initial implementation period for the surveying coursesand BREG 321, the author’s time was allocated for LON-CAPA resource development. Oncethe project was underway, all conventional homework problems in those courses were convertedto online delivery through LON-CAPA. Page 26.37.7Table 1. Information about courses in the study. # of Course Title and Notes
implemented with the intention ofmaking assessment more formative, though the differences in perceptions between in classexams and out of class homework may make a difference for students. Though the data onstudent learning is limited in these studies, they did indicate that students reported giving moreattention to instructor feedback [9] and that the mastery system was more “fair” [10], showingpromise for the methods and echoing similar results found in this study.Because the focus of this project was on homework assignments conducted outside of theclassroom, the design of the automated assessment systems were used as a starting point, thoughthe evaluation itself would not be automated. The authors instead focused on emulating theprocess of
stories to the overall project and to the community to “hear” the testimonies and to facilitate adhering to of engineering education the participants’ reality during analysis. -We co-construct meaning-making within the research team so as not to mis-construe or stray from participants’ testimony The concepts underlying the research design The knowledge produced needs to be meaningful
Paper ID #13824Developing an Intensive Math Preparation Program to Enhance the Successof Underrepresented Students in Engineering ˜Prof. Denise Hum, Canada College Denise Hum is an Associate Professor of Mathematics at Ca˜nada College in the San Francisco Bay Area. She received her M.S. in statistics at California State University, East Bay. Her academic interests in- clude accelerated math pathways, Reading Apprenticeship, and increasing the number of women and underrepresented groups in STEM.Ms. Anna Marbella Camacho, Canada College As Project Director for a $5.9 million Hispanic-Serving Institution
of the course, students have atleast 33 hours of hands-on activities. The knowledge gained via theoretical and practicalexercises is reinforced by the computer projects utilizing MATLAB simulation software.In 2009, the first attempt at converting the existing traditional model of the EM course into theblended version has been made. Utilizing the hybrid methodology, several lectures wereconverted into the online format and gradually introduced to the class of 40 students. Feedbackcollected from the students showed an interest in the hybrid/blended version of the course. Astandard assessment model previously conducted for traditionally taught EM coursesdemonstrated an increase in comprehension of the subject. The last contribution was due to
Paper ID #11436Epistemic Network Analysis as a Tool for Engineering Design AssessmentMs. Golnaz Arastoopour, University of Wisconsin, Madison Before becoming interested in education, Golnaz studied Mechanical Engineering at the University of Illi- nois at Urbana-Champaign with a minor in Spanish. While earning her Bachelor’s degree in engineering, she worked as a computer science instructor at Campus Middle School for Girls in Urbana, IL. Along with a team of undergraduates, she headlined a project to develop a unique computer science curriculum for middle school students. She then earned her M.A. in mathematics
from a broad viewpoint to a specific focus (converge). Divergence is associated with activitieslike brainstorming, ideation, building, and prototyping. Convergence is associated with activities such asanalysis, selection, evaluation, and testing.Altogether, five stages comprise this framework. The shape in figure 1 was created to represent and showthis framework as an iterative process versus a linear one. Stage 1 focuses on conversations or actionspertaining to defining requirements, project scoping, and gathering information about a particular project Page 26.1038.5or the needs of stakeholders. Stage 2 focuses on conceptual