question throughout all of education, is a question posed by students irrespective ofage, socio-economic background, aptitude or course subject is, “When are we ever going to use this?” Theresponse that is oft provided typically references some a future class or an ultra-specific career. The strugglethat K12 teachers have faced over the past few decades is well documented. What is less documented, ishow collegiate level faculty can leverage the knowledge and experiences of these K12 teachers. Theconstantly evolving pedagogical best-known practices within K12 science, technology, engineering, andmathematics (STEM) exist to alleviate the underlying problem: students generally fail to see the relevance,cross-cutting ideas, and real world connections
2017 Best Paper, “MeasuringStudents’ Subjective Task Values Related to the Post-Undergraduate Career Search” [9] reads:“The PEPS study is grounded in Expectancy-Value Theory (EVT), which conceptualizesengagement in a task as a function of four subjective task values: attainment value, intrinsicvalue, utility value, and cost. The focus of this research paper is on the development andvalidation of survey measures to capture students’ subjective task values (STV) related to theirpost-undergraduate career search.” The top 10 keywords from that paper, based on their TFIDF,are shown in Table 1. Table 1. Top 10 Keywords in 2017 ERM Best Paper Word Term Frequency in Paper Document Frequency (n=157) TFIDF
pursue higher education in fully online programs has remainedremarkably consistent since the early years of online education through today - necessity andconvenience.10, 15-18 Learner preference among those who have previously had success withonline learning can also be seen as another reason, but to a much lesser extent.19 The literatureregarding online learning choice is not discipline specific, but applies to the needs of workingparents, no matter their careers. However, it is reasonable to assume that engineers (who alsohave careers and families) pursue online learning for the same reasons as everyone else. Onlinelearning continues to be primarily a vehicle for working adults to further their education whilestaying employed and/or
, University of Texas, El Paso America Fernandez is an undergraduate student majoring in Engineering Leadership at The University of Texas at El Paso with interest in Engineering Education. Her college career began with a compelling drive to succeed as an engineering major. Academic experiences she has participated include an engineering education internship at Berekuso, Ghana and the authorship of a published paper presented at the Frontiers in Education conference. America is currently working with the Center for Research in Engineering and Technology Education as a Research and Development Specialist focusing on advising procedures. She currently serves as the President in the American Society of Engineering Educators
security, and semantic web. He is a recipient of the US Department of Energy Career Award. His research has been supported by US Department of Energy, National Science Foundation, Air Force Office of Scientific Research, Air Force Research Laboratories, Ohio Supercomputer Center, and the State of Ohio.Prof. Chi-Hao Cheng, Miami University Dr. Chi-Hao Cheng received the B.S. degree in control engineering from National Chiao Tung University, Taiwan in 1991, and the M.S. and Ph.D. degrees from The University of Texas at Austin in 1996 and 1998 respectively, both in Electrical and Computer Engineering. He is currently a professor in the Department of Electrical and Computer Engineering at Miami University, Ohio. His primary
towardstaking computing courses in future, future interest in computer careers, and self-efficacy withregards to programming. Some of the key questions addressed in this survey include – for under-represented middle school students, can the approach applied in this course: 1. impact the choices regarding computing-related course work in the future? 2. alter perspectives on computing career choices? 3. enhance self-efficacy in programming? 4. provide better learning outcomes in programming?For our survey, a 4-point Likert scale (Strongly Agree, Agree, Disagree, Strongly Disagree) wasused. We calculated mean and standard deviation from the Likert items to produce a numericvalue for each of the questions mentioned above, in both the pre- and post
Directorate from West Point he has continued his research on unmanned systems under ARL’s Campaign for Maneuver as the Associate Director of Special Programs. Throughout his career he has continued to teach at a variety of colleges and universities. For the last 4 years he has been a part time instructor and collaborator with researchers at the University of Maryland Baltimore County (http://me.umbc.edu/directory/). He is currently an Assistant Professor at York College PA.Dr. Stephen Andrew Gadsden, University of Guelph Andrew completed his Bachelors in Mechanical Engineering and Management (Business) at McMaster University in 2006. In 2011, he completed his Ph.D. in Mechanical Engineering at McMaster in the area of
, Multidisciplinary Engineering Design major at Penn State Abington. His works focuses on robotic autonomy through ROS and MATLAB. Over the course of the past two years Cullen has worked with robots such as the TurtleBot and Parrot Bebop using ROS. Recently his work focused on using multiple robots. He hopes to continue this work in his career. c American Society for Engineering Education, 2018 Introductory Mobile Robotics and Computer Vision Laboratories Using ROS and MATLABAbstractRobot Operating System (ROS) is an open source, Linux-based robotics development anddeployment system which supports many commercial and research and development robots. Theeducational advantage of
of the ACM, vol. 50, no. 7, p. 30, 2007.[13] A. All, E. P. Nu˜nez Castellar, and J. Van Looy, “Towards a conceptual framework for assessing the effectiveness of digital game-based learning,” Computers and Education, vol. 88, pp. 29–37, 2015.[14] E. M. Gerber, J. M. Olson, and R. L. D. Komarek, “Extracurricular design-based learning: Preparing students for careers in innovation,” International Journal of Engineering Education, vol. 28, no. 2, pp. 317–324, 2012.[15] Z. Z. Li, Y. B. Cheng, and C. C. Liu, “A constructionism framework for designing game-like learning systems: Its effect on different learners,” British Journal of Educational Technology, vol. 44, no. 2, pp. 208–224, 2013.[16] V. S. Pantelidis, “Virtual reality and
and testing) and the reliability and maintainability of complex systems. Hehas been selected as both a NASA and an ONR Faculty Fellow. He regularly teaches courses in Ma-rine Engineering and in Maintained Systems. Most recently Dr. Dean was on the Headquarters Staffthe American Society of Naval Engineers. He received his Ph.D. from the Department of EngineeringManagement and Systems Engineering, and a B.S. in Nuclear Engineering Technology, from the BattenCollege of Engineering and Technology at Old Dominion University. Additionally, Dr. Dean receivedan MBA from the College of William and Mary. Prior to is academic career Dr. Dean was Director ofOperations and Business Development for Clark-Smith Associates, P.C., and served as an Electrician
complex systems. He has been selected as both a NASA and an ONR Faculty Fellow. He regularly teaches courses in Ma- rine Engineering and in Maintained Systems. Most recently Dr. Dean was on the Headquarters Staff the American Society of Naval Engineers. He received his Ph.D. from the Department of Engineering Management and Systems Engineering, and a B.S. in Nuclear Engineering Technology, from the Batten College of Engineering and Technology at Old Dominion University. Additionally, Dr. Dean received an MBA from the College of William and Mary. Prior to is academic career Dr. Dean was Director of Operations and Business Development for Clark-Smith Associates, P.C., and served as an Electrician in the US Navy
redundant array of independent disks (RAID) controllers. His research interests include engineering education, robotics, and literate programming.Ms. Jane N. Moorhead, Mississippi State University Jane received her B.S. in Electrical Engineering from North Carolina State University. Her career has been all about hardware and software development; with NASA she designed cut-down systems for weather balloons and telemetry systems. Working for IBM, she designing modems and routers and had the op- portunity to work at IBM Research Yorktown Heights on the first large-scale voice recognition system. Moving to Mississippi, Jane took a job at Mississippi State University teaching courses in Digital Design using FPGAs
from multiple assessors directly tied to the established criteria. Studentswere then given time to reflect upon, and then address, the comments received through theconceptualization and experimentation stages of the Cycle.In closing, the development of the cornerstone project described here has had an overall positiveimpact, as students appreciated being “given a chance to solve a real world, open ended problemthrough our coding which will be useful in both our college careers and our careers later in life.”Those interested in implementing a similar project at their institution are welcomed to contact theauthors for additional information.References1. D. A. Kolb, Experiential Learning: Experience as the Source of Learning and Development
Transformation of Engineering Education,” Int. J. Eng. Pedagog., vol. 6, no. 4, pp. 23–29, 2016.[8] M. G. Eastman, J. Christman, G. H. Zion, and R. Yerrick, “To educate engineers or to engineer educators?: Exploring access to engineering careers,” J. Res. Sci. Teach., vol. 54, no. 7, pp. 884–913, 2017.[9] K. Litchfield and A. Javernick-will, “‘“ I Am an Engineer AND ”’: A Mixed Methods Study of Socially Engaged Engineers,” J. Eng. Educ., vol. 104, no. 4, pp. 393–416, 2015.[10] L. Lin, “Exploring Collaborative Learning Theoretical and Conceptual Perspectives,” in Investigating Chinese HE EFL Classrooms: Using Collaborative Learning to Enhance Learning, Dillenbourg: Springer, 2015, pp. 1–310.[11] A. A. Gokhale and The
providing equal opportunities to students from all backgrounds.Mr. Alisan Oeztuerk , German ArmyMr. Ben Servoz, Dartmouth College c American Society for Engineering Education, 2018 Data-Driven Curricular Decisions in Introductory Computing Classes1. IntroductionComputer programming has become an essential skill in young people’s trajectories foracademic success in STEM, entry into STEM professions, and increasingly across a broaderspectrum of career choices. Yet, drop-out rates remain high in overcrowded introductoryprogramming courses. At the same time, recruiting and retention of a diverse student body,particularly women and students from underrepresented populations, into computing and STEMcareers remains a
[14]. Studentsperformed proficiently in the course and felt much more confident in their computing abilities,and felt the course was important and useful to both current studies and future careers. Tilburydeveloped web-based MATLAB learning materials in the domain of automatic controls; thelearning materials were coupled with MATLAB homework [15]. Tilbury found that studentbehavior while working on MATLAB homework included frequent quick references to thelearning material.Researchers have also analyzed student learning and usage of small auto-graded coding exercisesin introductory programming courses that are not based on MATLAB[6][7][8][9][10][11][12][13]. Edgcomb found that students completed 25% of assigned exerciseswhen no points were
andredesign certain features of the modules I developed. The mental work it took to problem solving,in turn, gave me a better understanding of hardware design and is a practical tool that I can use inmy future career.”References[1] F. Folowosele, T. J. Hamilton and R. Etienne-Cummings, "Silicon Modeling of the Mihala¸s– Niebur Neuron," IEEE Transactions on Neural Networks, vol. 22, no. 12, pp. 1915-1927, December 2011.[2] D. Johnston, S. Wu and R. Gray, Foundations of Cellular Neurophysiology, Cambridge, MA: MIT Press, 1995.[3] T. Pearce and J. Williams, "Microtechnology: Meet neurobiology," Lab Chip, vol. 7, no. 1, pp. 30- 40, January 2007.[4] J. Wijekoon and P. Dudek, "Compact silicon neuron circuit with spiking and bursting behavior
feedback to correct mistakes.If CS 1 only has MSPs, when will students learn to write larger programs? Our thoughts: ● Majors will learn to write larger programs in CS 2. ● Non-majors, if they need to program in their careers, are more likely to have to write programs similar to the MSPs, like writing a small add-on function for a statistical analysis tool, for google docs, for a database query, etc. If they need to write more substantial programs, they will probably take a CS 2 class (or more). ● With the above said, we note that we intentionally ran the experiment in a more “extreme” manner, to see what effect would occur. Going forward, our instructors plan to give one large assignment mid-quarter and one
core is easily scalable and designed for higherdimensional data.5 Table 2: Rating scale pre-survey questions analyzed. For each of these eight statements, the learners were asked “To what extent do you agree with the following statements?” and could select from a five-point ratingscale ranging from “Strongly Agree” to “Strongly Disagree.” The statements are shown here in the order asked. Pre-course survey statement (i.e., question) Code “I'm taking this because I want to learn about the subject” Personal Interest “I'm taking this course to do my current job better” Personal Interest “I'm taking this course to improve my career prospects
education to help students develop deep understanding. This work hasmostly been at the K-12 level; but argumentation is even more important for undergraduates in en-gineering and computing (and other STEM fields). Not only will argumentation help engineeringstudents master concepts, it will also better prepare them for their professional careers where theycan expect to engage in vigorous arguments about trade-offs in various approaches to addressingproblems in their design/implementation projects.Prior research has shown that some key requirements must be met to ensure that argumentationis most productive: The argumentation must be in small groups of 4–5 students each; each groupmust include students with different approaches to the topic; and the
and how we empower learners to be interdisciplinary.Tyler J. Kerr, University of Wyoming Tyler Kerr received a B.A. in Geology from Franklin & Marshall College in Lancaster, PA in 2011, and an M.S. in Geology (Paleontology) from the University of Wyoming in 2017. His background in pale- ontology and interest in emergent technology has led him to pursue a career 3D scanning, rendering, and digitizing museum collections. In addition to his digitization work, he runs the University of Wyoming’s Coe Student Innovation Center (CSIC), the university’s newest educational STEAM-oriented campus makerspace for students, faculty, and staff.Mr. Larry Schmidt, University of Wyoming Larry Schmidt is an associate librarian at