own writing.4. Student Learning Outcomes AssessmentThe following learning outcomes have been established to assess student performance in theSummer Engineering Experience program. These student outcomes are as follows: (a) Students will demonstrate an ability to identify, formulate, and solve engineering problems by applying principles of engineering, science, and mathematics. (b) Students will demonstrate an ability to design and apply creativity in the design of engineering systems, components and process; (c) Students will demonstrate an ability to function effectively on teams that establish goals, plan tasks, meet deadlines, and analyze risk and uncertainty; (d) Students will demonstrate an ability to
PBL activity, participants mentioned some more frequently. Those were: a) the importance ofthe active learning and the collaborative learning in PBL, b) the importance of the autonomouswork of students and c) the importance of working on problems with real contexts. They alsomentioned: d) the importance of selecting the activity regarding the learning objectives and e) therecognition of the possibilities of working with active learning.Secondly, in the case of the “questions arising in the development of the activity” participantsreflected mostly on procedural questions. The most frequent were: a) the estimation of the timeneeded for the activity, b) determination of proper resources, c) how to create an interactive andadequate collaborative
/en/product/actuator/dynamixel/ax_series/dxl_ax_actuator.htm The Pincher robot arm is a 5 degree-of-freedom arm and an easy addition to the TurtlebotROS robot platform. The arm kit comes with everything needed to physically assemble andmount the arm as a stand-alone unit or as an addition to your Turtlebot platform. Shown inFigure 3 is one of our two robotic arms set up without the Turtlebot platform. Each of the servos in the chain needs to have an assigned unique id and this can beaccomplished using the Dyna-Manager software provided by Trossen robotics7. Due to the manypower software connection permutations available for the arm, this proved to be quite frustratingfor both the students and faculty. In the end we used method B
, as shown in Figure 5(a). This builds confidence withthe theory, specification equations, and the design tables. Further, often a conceptual lesson ishighlighted in this type of assignment, such as the critical difference between x- and y-axis flexuralbuckling, highlighted in Figure 5(b).When introducing combined axial and bending forces, students often do not have a good idea ofhow the relative magnitudes of axial and bending loads affect the overall capacity of the member.In one simple problem added to the normal assignment, students generate essentially randompairings of loads for a given section and plot them against the corresponding specificationequations, as in Figure 5(c). Through inspecting a range of values, exploring how the
responses are incorrect. Here the correct answer was Ab+cd. Figure 3 shows majorimprovements in the understanding when compared to figure 2. Here the answer is A. Figure 2. Student responses showing some improvement in accuracy. Figure 3. Student responses showing vast improvement in accuracy.As seen in Figure 4 and 5 below accuracy of student responses is significantly improved with a100% accuracy in figure 5. The correct answer here is A+C for Figure 4 and B+C for Figure 5. Figure 4 and 5. Student responses showing 96% and 100% accuracy.2.3. Immediate Feedback Assessment TechniquesIn this study, students were given IF-AT assessments directly after completing a unit quiz. TheIF-AT, is a transformed multiple
-groups analysis of predictors of higher level career aspirations among women in mathematics, science, and engineering majors. Journal of Counseling Psychology. 1998;45(4):483-96.5. Hutchison MA, Follman DK, Sumpter M, Bodner GM. Factors influencing the self-efficacy beliefs of first-year engineering students. J Eng Educ. 2006 JAN;95(1):39-47.6. Hutchison-Green MA, Follman DK, Bodner GM. Providing a Voice: Qualitative Investigation of the Impact of a First-Year Engineering Experience on Students' Efficacy Beliefs. J Eng Educ. 2008 APR;97(2):177-90.7. Marra RM, Rodgers KA, Shen D, Bogue B. Leaving Engineering: A Multi-Year Single Institution Study. J Eng Educ. 2012 January;101(1):6-27.8. Concannon JP, Barrow LH. A Cross-Sectional
of the students and faculty.” 8In addition, the components of the 2016-2017 ABET Criterion 3 for Student Outcomes willgreatly impacted by the educational facilities including the outcomes b, c, e, j, and k, as givenbelow9: (b) an ability to design and conduct experiments, as well as to analyze and interpret data (c) an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability (e) an ability to identify, formulate, and solve engineering problems (j) a knowledge of contemporary issues (k) an ability to use the techniques, skills, and modern
Analyst. She was the owner and chief systems engineer for Systems Engineering Services (SES), a computer systems design, development, and consultation firm. She joined the faculty of the School of Engineering and Computer Science at Baylor University in 1997, where she teaches a variety of engineering and computer science classes, she is the Faculty Advisor for the Women in Computer Science (WiCS), the Director of the Computer Science Fellows program, and is a KEEN Fellow. She has authored and co- authored over forty peer-reviewed papers.Dr. Kenneth W. Van Treuren, Baylor University Ken Van Treuren is an Associate Professor in the Department of Engineering at Baylor University. He received his B. S. in Aeronautical
, “Motivational and Self-Regulated Learning Profiles of Students Taking a Foundational Engineering Course,” J. Eng. Educ., vol.104, no. 1, pp. 74–100, Jan. 2015.[3] S. M. Lord and J. C. Chen, “Curriculum Design in the Middle Years,” in Cambridge handbook ofengineering education research, New York, NY: Cambridge University Press, 2014, pp. 181–195.[4] B. F. Tobolowsky, “Sophomores in transition: The forgotten year,” New Dir. High. Educ., vol.2008, no. 144, pp. 59–67, Winter 2008.[5] J. Gahagan and M. S. Hunter, “The second-year experience: Turning attention to the academy’smiddle children,” Campus, vol. 11, no. 3, pp. 17–22, 2006.[6] J. Gainen, “Barriers to success in quantitative gatekeeper courses,” New Dir. Teach. Learn., vol.1995, no
what courses would transfer andhow they would be accepted by the university. This transparency ensures that students are on theright track towards graduating from the university. Despite the efforts to ease the transfer process, the need for increased attention andresources devoted to transfer students is particularly evident and critical at mid-sizeduniversities. In a recent study conducted by a mid-sized university examining the experiences oftheir transfer students, the following university-focused recommendations were offered: (a)provide resources to all transfer students on academic warning to enhance their timemanagement, organizational, and attentional skills (e.g., a one-credit course or workshop); (b)include self-efficacy
engineering design and engineering entrepreneurship. a. Did the things you learned in the course about engineering design and engineering entrepreneurship help you with the designing your life course activities? Please explain. b. Did the designing your life course activities help you in the course about engineering design and engineering entrepreneurship? Please explain.The DYL activities used in the course were taken from the text and minimally modifiedto suit a classroom setting. The activities used in the course included: • Creation of a life-design team • Identification of key mentor(s) • Creation of health/work/play/love dashboard • Descritption of workview • Lifeview reflections • Good
: (a) valencedimension (positive or negative factors) and (b) activation dimension (focused or unfocusedenergy factors). Academic emotions differentially influence student performance. For example,positive emotions (e.g., joy) may increase engagement and nurture creative learning strategies,while negative emotions (e.g., boredom) may have an opposite effect, diminishing engagementand supporting superficial cognitive processing [2]. In other instances, negative emotions (e.g.,anger) may increase an individual’s desire to prevent future failure [2] and serve to improveperformance.Multi-componential measure of academic emotionsTraditionally, academic emotions are measured with self-reports [9], [10]. However, self-reportspose high risks of
7the long-term impact of the experience by implementinga longitudinal study with participants attending multiplenon-technical conferences. Finally, it would be interesting toexamine how participants implement the gained benefits intotheir academic work as well as their job search. R EFERENCES [1] B. E. Seely, “Patterns in the history of engineering education reform: A brief essay,” Educating the engineer of 2020: Adapting engineering education to the new century, pp. 114–130, 2005. [2] A. S. Bix, “From” engineeresses” to” girl engineers” to” good engineers”: a history of women’s US engineering education,” NWSA journal, vol. 16, no. 1, pp. 27–49, 2004. [3] E. Seymour, A.-B. Hunter, S. L. Laursen, and
. These tests offer threetrials based on the student’s performance. If the student passes the test with a grade of B (80%)or more on a trial, s/he does not have to take the next trial. Each new trial involves new questionsthat have similar difficulty levels to the previous trial. Therefore, if the student retake a trial,his/her grade will be reduced in the successive trials. The student will not receive a grade untilhe/she successfully solves the trial or exhaust all the trials. In other mastery applications,resubmission would involve an assignment or evaluation instrument that is slightly harder thanthe previous one; therefore, students who resubmit do not receive a reduced grade. The completedetail of the grade breakdown is explained in the
that detects the variableoccupancy level can save 15% every month (May through September) of the required coolingload and of the power consumed. This figure can significantly double to higher values whenconsidering higher occupancy density spaces such as theaters, class rooms, and large meetingrooms.The project revealed high impact on the level of understanding for students. Studentsperformance and project outcomes were assessed against ABET learning outcomes: (a) applyknowledge, techniques and skills to engineering technology activities, (b) apply knowledge ofmathematics, science, and engineering to engineering technology programs, (c) Conduct tests,measurements, calibration and improve processes, (e) Problem Solving: ability to identify
knowledge on the application of computerscience and engineering to UAV technologies and were able to acquire some of the skillsnecessary to conduct meaningful research in UAV technologies, understand research process, andlearn laboratory techniques. Most of the projects described below are highly interdisciplinary.Each REU student had a primary mentor. However, the students were co-supervised by othermentors depending on the nature of the projects.A. Autonomous Collision Avoidance of UAVs Utilizing ADS-B TranspondersFor the UAVs to be successfully integrated into the U.S. national airspace, the ability to detect andavoid both manned and unmanned aircraft is a necessity. This project involved the students indeveloping a method for collision
, respectively. a b c d e 7 Questions 16 Questions 16 Questions CU CU Results Full (3 removed) Results 7 16 Pre-test 16.8% - - 30.9% - Post-test 26.0% 17.8% 22.0% -- 54.3% Normalized 0.12 - - - - gainTable 2: Colorado upper-division electrostatics diagnostic results from this study (a-c) andresults previously published from the University of Colorado, Boulder (d-e) [5], [11].When comparing the results of the CUE-CMR of
graduate”, “five years after you graduate”, and “ten years afteryou graduate”. The Likert scale options included “Definitely will not” (0), “Probably will not”(1), Might or Might Not” (2), “Probably will” (3), and “Definitely will” (4).The second EMS question asked respondents: “How likely is it that you will do each of thefollowing in the first five years after you graduate?” Respondents were asked to rate each of theeight career options on a similar five point Likert scale: A. Work as an employee for a small business or start-up company B. Work as an employee for a medium- or large-size business C. Work as an employee for a non-profit organization D. Work as an employee for the government, military, or public agency (excluding a
objects.Dr. Scott T. Huxtable, Virginia TechMr. Sathyanarayanan Subramanian, Virginia Tech I am a Graduate Mechanical Engineer at Virginia Tech, specializing in Thermal-Fluid Sciences.Prof. Zahed Siddique, University of Oklahoma Zahed Siddique is a Professor of Mechanical Engineering at the School of Aerospace and Mechanical Engineering of University of Oklahoma. His research interest include product family design, advanced material and engineering education. He is interested in motivation of engineering students, peer-to-peer learning, flat learning environments, technology assisted engineering education and experiential learning. He is the coordinator of the industry sponsored capstone from at his school and is the advisor
exposing the freshmen to thevalues of Purpose, Responsibility, Individuality, Determination and Excellence, this non-pedagogical approach of teaching through Reverse Engineering indeed breeds PRIDE* in ourfreshmen students!_________________________References:[1] Cero Parametric 4.0, Pro/Engineer, and Wildfire are the trademarks of Parametric Technology Corp., MA, USA.[2] Quotes: Julius Caesar, 52 B. C.; Dave Ramsey; Walt Disney; Enrique Jardiel Poncela, Play writer, Spain;Abraham Lincoln; GD Naidu, Industrialist, India; and Michelangelo[3] http://chillingeffects.org/reverse/[4] Corrina Wu, “Some Disassembly Required,” ASEE PRISM, October 2008.[5] Kwabena A. Narh et al, “Innovations in Freshman Mechanical Engineering Curriculum at New Jersey
metacognition and its implications for learning. Much of this research focuses on learning processes in classroom settings. Dr. Menekse is the recipient of the 2014 William Elgin Wickenden Award by the American Society for Engineering Education.Miss Damji Heo, Purdue University, West Lafayette Damji Heo received B. A. degrees in Educational Technology and Psychology from Ewha Womans Uni- versity in 2012 and M. Ed. degree in Educational Psychology from the University of Texas at Austin in 2014 respectively. Currently, she is doing her Ph. D. in Learning, Design, and Technology program at Purdue University since 2015 and a graduate research assistant in School of Engineering Education at the same university. Her main areas
ethical conducts in an IT context. Accordingly, an interventional research(pre-post study) is designed and data were gathered from 347 computer stations in an IT-centric company in Iran. Due to the company's codes of ethics, six categories of unethical IT-related behaviors were defined as a) surfing social media, b) checking personal emails, c)sending organizational documents without authorized tools, d) sharing video or music files inlocal network, e) stockbroking, and f) installing non-job-related software on computers. Twonon-simultaneous phases with duration of three months were examined. In the first phase, atotal number of 906 unethical behaviors were observed by means of company-wide log-systems. Subsequently, for the second phase, every
connections thatallow free rotation, see Figure 2. More sophisticated models may be made using metal for membersand screws and bolts for the connections. Fig. 1 Deployment sequence of a 8-sided ring made of angulated units (a) (b) (c)Fig. 2 (a) Laser-cut pieces; (b) Students making connection details; (c) Deployable ring structureProject 2. Deployable gridScissor units using straight members are used to construct frames and grids. The motion of scissorunits whose members are hinge-connected at their mid-lengths, is translational. However, whenthe same units are connected at an eccentricity, the resulting motion is curvilinear, see Figure 3.The latter are referred to
., technicalskills; 52%) and systemic sources (e.g., lifelong learning; 12%).Our second sub-question was: (b) In what ways (if any) does gender and level of engineeringeducation influence students’ perceptions of engineering? In the Technical Communicationcourse, primarily composed of Caucasian male students in their junior year, findings suggestthat the students focused on the need to develop individual and systemic skills (Tables 3 and 4)whereas for the Women in Engineering course resulted in a change from individual sources tosocial skills (Tables 3 and 4).DiscussionFor the central research question, preliminary findings suggests that most students, regardlesson the course and point in time that the data was collected, commonly identified that one of
address students in terms that they easily recognize andcomprehend. For effective instruction to follow, educators should accommodate the needs of thelearner. Brown, B. suggested that authentic learning requires the learner to communicate detailedunderstanding of a problem or issue rather than memorize sets of isolated facts, and must resultin achievements that have relevance beyond the classroom [6].One of the hardest things to do in our profession is to motivate and inspire students to learn.There are numerous examples of methods used to motivate students [7]. These various strategiesinclude incorporating instructional behaviors, varying course structure, de-emphasizing grades,providing feedback, and emphasizing preparation, which provide many
wererepeating the course from the Fall 2015 semester, and the students in the Spring 2016 sectionswould not have had more course preparation than those who took the course in the Fall 2015sections.An independent-samples t-test was conducted to compare students’ final grades of the Fall 2015traditional classroom (M = 74.38, SD = 19.32) and students’ final grades of the Spring 2016 flippedclassroom (M = 79.36, SD = 17.97). There was not a statistically significant difference in the finalgrades, t(84) = -1.06, p = .29. These results suggest that the flipped classroom does not have aneffect on students’ final grades; however, we find the increase from C to C+, almost B-) to be avast improvement. The increase in grades could be explained by students being
object b in the direction of the motion as object b moves distance d then the work WFab exerted by object a on object b is given by WFab = (Fab )(d). Think “work = force times distance”. 2. Recall the units used for Work: Quantity English Metric kg m Force lb N ewton or s2 Work ft lb joule or N m m g (gravitational constant) 9.8 2
bodydiagrams (FBDs). The instructional faculty were charged to identify pedagogical methods toimprove student performance in Statics and the retention of key concepts. Two novel approacheswere implemented over the 2016 academic year in the Statics course and continue to be used. Amnemonic device to remember the key components of free body diagrams was developed anddemonstrated consistently in class. The device is referred to as “The ABC’s of FBD’s”. The firstfour letters of the alphabet identify an item that must be included in FBDs. The letter “A” standsfor “All reactions and applied loads”, “B” stands for the “Body”, “C” stands for the “CoordinateSystem” and “D” stands for “Dimensions”. It is then stressed that the equilibrium equations or“E” comes
, D Anguelov, D Erhan, V Vanhoucke, A Rabinovich. Going Deeper with Convolutions, Computer Vision and Pattern Recognition, 2015.7. C Szegedy, V Vanhoucke, S Ioffe, J Shlens, Z Wojna. Rethinking the Inception Architecture for Computer Vision, Computer Vision and Pattern Recognition, 2015.8. A G. Howard, M Zhu, B Chen, D Kalenichenko, W Wang, T Weyand, M Andreetto, H Adam. MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications, Computer Vision and Pattern Recognition, 2017.9. Y Shibberu. Introduction to Deep Learning: A First Course in Machine Learning, ASEE Annual Conference & Exposition, Columbus, Ohio, 2017. https://peer.asee.org/2858210. TensorFlow Team, Installing Tensorflow on Windows
2016. [Online]. Available: https://www.cdc.gov/ncbddd/autism/data.html. [Accessed 30 January 2018].[5] R. C. Schaaf, S. Toth-Cohen, S. L. Johnson, G. Outten and T. W. Benevides, "The everyday routines of families of children with autism. Examining the impact of sensory processing difficulties on the family," Autism, vol. 15, no. 3, pp. 373-389, 2011.[6] E. J. Marco, L. B. N. Hinkley, S. S. Hill and S. S. Nagarajan, "Sensory Processing in Autism: A Review of Neurophysiologic Findings," Pediatric Research, vol. 69, pp. 48R-54R, 2011.[7] A. E. Robertson and D. R. Simmons, "The Relationship between Sensory Sensitivity and Autistic Traits in the General Population," Journal of Autism and