Enthusiasm for Mathematics through RoboticsAbstractThis evidence-based practice paper describes the study of generating enthusiasm for mathematicsthrough robotics. A survey of Rensselaer Polytechnic Institute undergraduate students taking theRobotics I course showed that, while many students have a great interest for mathematics, morethan 1 in 4 of those same students expressed that they were not adequately prepared for themathematics required. This is particularly concerning for those teaching engineering coursesbecause concepts of robotics and mathematics are very much intertwined. Therefore, thisinspired a study of younger middle school and high school students to i) assess preexistingnotions of mathematics and robotics, ii) introduce an
thesame term.Requirements diagrams are not used; they are inefficient in representing requirements linkages(low density of information). Requirements are instead represented in tables/matrices withappropriate relationships displayed.Tables and MatricesOne of MagicDraw’s strengths is its ability to generate tables and matrices on demand of directand multi-order relationships between elements. Students are shown how to use tables andmatrices to investigate model consistency, completeness, and as a basis for rich self-explorationof a system model.Figure 5: Table of OperationsThis table lists operations from the PRZ-1 model; it also shows the owning block, the definitionof the function, what call operation nodes reference it, and what activity
33 4 31 4 31 9 30 24 30 Ethnicity Native Am. & 0 0 1 8 0 0 1 8 1 3 3 4 Pacific Islander Black 2 15 5 42 2 15 7 54 16 53 32 40 Asian 4 31 0 0 3 23 0 0 2 7 9 11 Hispanic 3 23 1 8 2 15 5 39 10 33 21 26 White 4 31 5 42 6 46 0 0 1 3 16 20 First Generation College Student Yes 5 39 3 25 6 46 5 39 5 17
versionused in this study is widely accepted as a measure of chronic stress due to ongoing lifecircumstances and expectations about future events. In this format, responses to 10 questions, ratedon a scale of 0 (Never) – 1 (Almost Never) – 2 (Sometimes) – 3 (Fairly Often) – 4 (Very Often),are scored to yield a number which serves as a measure of the respondent’s stress level. Individualscores are then grouped to determine the average and standard deviation. High stress levels areconsidered to be indicated by scores more than one standard deviation above the mean in thisstudy.It is generally recognized that high stress levels, experienced over an extended period of time, willnot prove beneficial to successful academic performance. An effective
knowledge, skill, and experience are alsoleaving the workforce. The electric utility industry, like many others, is feeling the effect of babyboomers’ exodus to retirement. A variety of factors, including the growing retirement eligibilityand “…the generational shift in the traditional utility workforce…”1 is having an adverse effecton the utility industry.According to the U.S. Bureau of Labor, 46.2 million baby boomers, 46.9 million generation xand 46.4 million millennials were employed in the fourth quarter of 2014. Baby boomers beganto reach retirement age, 65, in 20112. All baby boomers will be over 65 by 2029 and will makeup more than 20 percent of the U.S. population3.To get ahead of the curve, EASi partnered with one of the largest electric
electrical circuits,” Am. J. Phys. 72 (1) 98-115 (2004); doi: 10.1119/1.1614813.26 R. Ross, E.P. Venugopal, G. Hillebrand, M. Murray, and M. Gonderinger, “Results of a Multi-Year Assessment of Inquiry-Based Second Semester General Physics Laboratory Activities,” in Proceedings of the 2014 American Society for Engineering Education (ASEE) Annual Conference & Exposition, Indianapolis, IN, (2014).27 R. Ross and P. Venugopal, “Inquiry-based Activities in a Second Semester Physics Laboratory: Results of a Two-year Assessment,” in Proceedings of the 2007 American Society for Engineering Education Annual Conference & Exposition, Honolulu, HI, (2007).28 Kuder–Richardson Formula 20. (2016, November 18). In Wikipedia, The
identified asengaged vs. non-engaged during the classroom observation. The three most frequent categoriesfor each group are highlighted in Table 1. From Table 1, the engaged students at both ASU andPitt most frequently noted 1) application and active learning via games, 2) an actual positiveimpact of games on technical learning and performance, 3) the motivating and fun nature ofgames, and 4) an overall desirableness of games for learning. Although the non-engagedstudents most frequently noted positive benefits such as engagement and motivation also, thenon-engaged students at ASU noted a lack of challenge with their games, including alreadybeing familiar with the material. The non-engaged students at both schools also most-frequentlyindicated that
present our University’s efforts to contribute to this need by way of a hands-onactivity designed for high school students. The workshop was devised to achieve three primarygoals: 1) Encourage consideration of a career in electrical and computer engineering 2) Buildexcitement about the Internet-of-Things and provide students with a future technical focus and 3)Introduce students to the fundamental building blocks that make up the Internet-of-Things. Duringthis activity, students complete a project in which they first construct a circuit to read data from atemperature sensor using a microcontroller platform. The students then write software to transmitthat data over a short-range wireless network and then eventually to an Internet-connected
. 4 For simple domains, i.e., homogeneous properties and simple boundary conditions, thegoverning equation can be solved analytically. In general, an analytical solution does not existand the governing equation must be solved numerically.Contaminant Transport by Advection-Dispersion A model that includes only advection and dispersion can be solved numerically and maybe solved analytically for certain domains and properties. The contaminant will flowdownstream with the groundwater and the front will spread out through dispersion. Thegoverning equation is C x, t 2C x, t C x, t D v (1) t x 2
1ELCIR Program – Engineering Learning Community Introduction to Research: A research andglobal experience program supporting first generation, low-income, and underrepresentedminority students.INTRODUCTION:The College of Engineering at Texas A&M University has set some ambitious goals: to increasediversity in engineering and to better prepare the engineers who are joining today’s global anddynamic workforce. Some of the issues that need to be addressed at our college are: 1) increasethe retention of underrepresented minority (URM) and first generation students in engineering,2) enhance the participation of those students in engineering research and study abroadprograms, and 3) pave the way for those students to enroll in graduate programs in
the necessary pre-requisites for engineering, which waslinked to a higher percentage of FGS students choosing to major in business, vocational fields,social sciences, and health sciences rather than engineering18. The literature shows FGS haveunique experiences in college and are more likely to be unprepared for the engineering rigorneeded. Despite these claims, many FGS in engineering often succeed to graduation, yet littlework has examined the experiences and attitudes that aided in their success. The researchquestions that are directing this study are the following:RQ 1: How do first generation college students’ experiences within engineering influenceengineering belongingness?RQ 2: How is engineering belongingness and engineering identity
Results using PowerPoint, Camtasia and YouTube Videos to Create an‘Introduction to Engineering (EE110)’ CourseIn 2015, the Colorado Technical University started an initiative to deliver engineering coursesonline. Senior leadership wanted to expand its undergraduate and graduate engineeringprograms. The engineering faculty decided to develop a freshman-level course entitled,Introduction to Engineering (EE110) using a flipped classroom approach1-3.EE110 provides the beginning engineer with fundamental knowledge and skills associated withthe electrical or computer engineering professions. Table 1 illustrates the lab assignments that thestudents must complete during class. It will introduce common electronic components, basiccircuit configurations
Professor in the George W. Woodruff School of Mechanical Engineering at the Georgia Institute of Technological. Dr. Linsey received her Ph.D. in Mechanical Engineering at The University of Texas. Her research area is design cognition including systematic methods and tools for innovative design with a particular focus on concept generation and design-by-analogy. Her research seeks to understand designers’ cognitive processes with the goal of creating better tools and approaches to enhance engineering design. She has authored over 100 technical publications including twenty-three journal papers, five book chapters, and she holds two patents. c American Society for Engineering Education, 2017
course was alsodesigned and implemented by the Communication Lab Director and tutors from the EECS Com-munication Lab, together with the EECS Department Head and a faculty advisor. It provided anoverview of relevant technical communication tasks, detailed below, facilitated by guest lecturesand hands-on workshops.3.2.1 The communication course’s operationThe course consisted of a weekly, two-hour session. Topics covered a range of technical com-munication tasks, as outlined in Table 3. Typically each session began with an introductory guestlecture (∼30 min), followed by small-group workshops run in parallel, in separate rooms, and ledby Communication Lab tutors. Guest lecturers were selected based on (1) their example as goodcommunicators and
College Student in EngineeringAbstractThis research study explored first-generation college students’ in engineering post-graduationcareer intentions based on responses to a quantitative survey. In this paper, we answer thefollowing research questions: 1) How do first-generation college students’ measures of physics,mathematics, and engineering identity constructs differ compared to non-first-generation collegestudents? and 2) How does a physics identity influence first-generation college student’s choice ofan engineering major and career aspirations? The data came from the Intersectionality of Non-normative Identities in the Cultures of Engineering (InIce) survey. InIce was completed by 2,916first-year engineering college students enrolled in
+ 𝐴 B) 𝐶!"𝑆! = 𝑃! 𝐶!!! + 𝑃! (𝐶!!! )𝑆! = 𝑃! 𝐶! + + 𝑃! 𝐶! = 𝑃! as 𝐶! = 0 for half adder𝑆! = 𝑃! 𝐶! + 𝑃! 𝐶! = 𝑃! 𝐺! + 𝑃! 𝐺!𝑆! = 𝑃! 𝐶! + 𝑃! 𝐶! = 𝑃! (𝑃! 𝐺! + 𝐺! ) + 𝑃! (𝑃! 𝐺! + 𝐺! )𝑆! = 𝑃! 𝐶! + 𝑃! 𝐶! = 𝑃! (𝑃! 𝑃! 𝐺! + 𝑃! 𝐺! + 𝐺! ) + 𝑃! (𝑃! 𝑃! 𝐺! + 𝑃! 𝐺! + 𝐺! )Example 2: Generate 1+𝑋 ! +𝑋 ! polynomial in a built-in-self test (BIST). Give the required diagram anddepict the comprehensive table.Solution: Clk Q(0) Q(1) Q(2) 0 1 1 1 1 0 1 1
metric reported isthe average quality score produced by the participant.NoveltyThe novelty metric is a measure of the uniqueness of a solution with respect to other (25,solutions generated for the same design problem during that idea generation session26) . The metric utilizes a bin system where solutions are sorted into one or more problemspecific bins. Once all solutions for the session are binned, each bin is assigned a noveltyscore according to the following equation. # 𝑜𝑓 𝑖𝑑𝑒𝑎𝑠 𝑖𝑛 𝑏𝑖𝑛 𝑁𝑜𝑣𝑒𝑙𝑡𝑦 = 1 − 𝑇𝑜𝑡𝑎𝑙 # 𝑜𝑓 𝑖𝑑𝑒𝑎𝑠
685mm x 355mm) without propellers 39” x 39” x 14” (990mm x 990mm x 355mm) with propellersWeight: 6 lbs. 14 ½ oz. (3132.5 gr.)Power: 1 kW (Max) 500 watts (Min)Rotors: 4Motors: 22 pole, out runner, brushless, 17 V (Max), 250 watts (Max)Propellers: 14” x 4.7” – Composite 6000 RPM (Max)Battery: 2 x 8000 mAh (C) 4S LiPo 10C (Max)Controller: 2 x Atmel SAM3X8E ARM Cortex-M3 CPU on Arduino Due development board @ 84 MHzWireless: XBee pro 60 mW (802.15.4)Acceptance Test. Since this is a project requiring new technical skills the following acceptancetests were proposed. The student also created videos on the test results and uploaded toYouTube
. The other is that courses have in general becomenarrower in their technical focus as the depth of knowledge has developed. In addition, thecross‐disciplinary content is often quite limited. To be a material engineer, one should notonly focus on the science research in materials but also in application of traditional andadvanced materials in a wide spectrum of areas. We all know that training Materialengineers for the next generation requires more than teaching them knowledge of materialscience. Learning to apply the design process as reported can be the key for students tounderstand the blending of Materials Science with humanity needs [1-3]. There are manyways to define “design” in different fields. Here we would like to use the
(75 minutes) and a weekly laboratory session (4 hours).Students complete six laboratory modules, each two weeks in duration, during the laboratorysessions (see Table 1). Most modules require two in-class laboratory periods to complete, oneperiod designated as a planning period and the other as an experimental period. Following thefirst laboratory period, students write a planning report (a technical memo) in groups of 3-4 andfollowing the experimental period the students individually write a summary report (a technicalmemo). The final laboratory module requires a 20-minute group presentation and a fulllaboratory report. Thus, the course, as implemented in the past, required 10-14 writtenassignments, but had been lacking instruction in
) enrollment for the first five years of the program. (Include majors only and consider attrition and graduation.) YEAR 1 2 3 4 5 Headcount 12 22 25 33 42 FTSE 10 18.3 20.8 27.5 35d. Students General recruitment efforts, including plans to recruit and retain students from underrepresented groups can be categorized as follows: Industry Professionals: As a professional master’s program, the main recruitment efforts will be focused on recruiting industry professionals from technical fields such as oil & gas, energy, construction, manufacturing, electrical
, dental, and physical therapy majors; the physics courses PH411 andPH413 are taken by engineering majors. PH201, PH301, and PH411 are first semester physicscourses in mechanics, PH202 and PH302 are second semester physics courses in electro-magnetism and optics, and PH413 is a third semester physics course in electro-magnetism. Thispaper focuses on the different results between PH201, PH301, and PH413 (PH411 results wouldhave been a more direct comparison however an insufficient number of those students weretested). The set of expected learning outcomes common to the courses are indicated below asPHY 1, PHY 2, and PHY 3. QCC lists ten General Education outcomes; the expected learningoutcomes evaluated contribute to QCC Gen. Ed. outcomes numbered
of its use (see Figure 1). A short practice problem followed where studentsapplied one card to a presented problem. Next, each participant was given the same set of 7 DesignHeuristic cards. Due to the time limit of the session, only a subset of cards was provided. Thissingle set of seven cards was chosen at random from the deck of 77 Design Heuristics and included:Scale up or down, Use multiple components for one function, Adjust function through movement,Bend, Reconfigure, Allow user to customize, and Change surface properties. We chose to give asingle randomized set to all participants in order to explore variations in the resulting designconcepts across participants.Next, the participants were asked to generate 5 conceptual solutions
common to all university students. Technicalcommunication is one of the most relevant and utilized across disciplines. Technical andprofessional communication genres and strategies are defined by their context and purpose in theworkplace (Hart-Davidson, 2001). Engineering students who understand how technicalcommunication works and deploy its strategies typically add three kinds of value to a technicalproject by effectively 1) designing documents that convey information in usable forms, 2)working with and refining collaborative practices to maximize collaborative output, and 3)recognizing patterns and structures across specific problems or projects as well as providingstrategic thinking that can productively impact large systems and data sets
Program at BridgeValley CTC stands to serve other programs and majorswithin the college by creating a model that supports the students academically and socially, inaddition to financially. Through this model, and through outreach that strengthens partnershipsbetween community colleges and area industries, the program meets the needs of many first-generation college students in the region and helps to create a more educated workforce in WestVirginia. ReferencesHistory and Locations of BridgeValley Community and Technical College:http://www.bridgevalley.edu/history; http://www.bridgevalley.edu/campus-locationsSTEM Scholars Scholarship Program:http://www.bridgevalley.edu/stem-scholars-scholarship
interviewee has and memberships in esteemed professional societies.Questions in the Gender section focus on challenges and differences that the interviewee faceddue to her gender in STEM fields. Questions in the Reflection section focus on advice pertainingto the original five personal research questions and general advice that the interviewee wishes toshare.Oral History Preservation at IEEE Engineering Technology and History Wiki (ETHW)The IEEE History Center’s historical material is made available through a wiki-based portalknown as the Engineering and Technology History Wiki (ETHW).1-3 The oral history collectionof over 800 interviews of prominent engineers and scientists in IEEE’s fields of interest is one ofthe most important in the world. The
. When students come to class, they perform weekly labassignments. Because labs require students to collaborate in teams, the College of Engineeringidentified several challenges for delivering the course fully online in the future3. The paper willsummarize the results of the flipped classroom and its implementation using Google Docs andinteractive video for EE110.Grading results and course surveys were used to assess and improve the effectiveness of theflipped classroom over several course offerings. Various technologies include: (1) using worddocument with links to YouTube videos followed by with quiz questions in the first offering; (2)adding Google Docs (or Google Forms) with embedded YouTube Videos and quizzes in the nextclass session; and
andill-structured industry problems in mining, milling, and manufacturing. There are no courses inthe IRE curriculum; rather, every semester students generate (with the help of faculty) a series ofsyllabi that describe how they will meet the required technical and design competencies thatcomprise the IRE curriculum. A majority of IRE learning and assessment activities are organizedand indexed by the aforementioned team-based, semester-long industry projects. For example, anIRE team designed and implemented a condenser performance test to be applied to a powerplant’s power generation condenser. To solve the problem, students learned cycle analysis,conduction heat transfer, convection heat transfer, heat exchanger design, engineeringeconomics, and
Paper ID #19079Engagement in Practice: Not Just Technical Education; An AnthropologicalPerspective on a Community-Based Engineering Internship ProgramKenzell Huggins, University of ChicagoMs. Asha Barnes Currently a student of the University of Notre Dame, my long term goals are to become a citizen of the world, a metropolitan learner. As Anthropology is my passion, I hope to continue to better my skills in ethnographic research.Dr. Susan D. Blum, The University of Notre DameDr. Jay B. Brockman, University of Notre Dame Dr. Jay Brockman is the Associate Dean of Engineering for Experiential Learning and Community En
Design Heuristics in a concept generation session for their project. Studentswere first asked to individually generate 4 concepts for their design problem in 20 minutes.Then, they were given instruction on Design Heuristics as an idea generation technique andpractice on an unrelated problem. The detailed instruction video can be found onwww.designheuristics.com.Then, the students were asked to apply Design Heuristics to generate4 new concepts in 20 minutes. Design Heuristic cards were divided before the session into twosets of 5 (“A” and “B”) to include a variety but limited number of cards appropriate to the timelimit (See Table 1). We selected several cards that encouraged user interactions and productmodifications. Each team was given either