are desirable for engineeringeducation. The interviews have also led us to think about the process of change and what isnecessary for faculty development. These insights point to the next steps in this project which areto use the interviews to describe a model of change. In this model, we would like to include thatthere may be individuals who felt the dialog process facilitated their development, while therewere others who did not.AcknowledgmentsThis material is based on work supported by The Leona M. and Harry B. Helmsley CharitableTrust through funding of the Consortium to Promote Reflection in Engineering Education(CPREE), a collaboration of twelve educational institutions.References[1] J. Dewey, (1933) How We Think, Boston: D.C. Heath and
-efficacybeliefs are assumed to be acquired through four primary informational or learning sources: (a)personal performance accomplishments; (b) vicarious learning; (c) verbal persuasion; and (d)physiological and affective states (Bandura, 1997, p.79). Learning experiences thus play acentral role in developing self-efficacy, and are therefore adopted as a focus of this study.3.0 Research QuestionThis paper addresses the question of how learning experiences (extracurricular collegeactivities related to innovation and entrepreneurship to be more specific) may be connected toinnovation self-efficacy (ISE.6).4.0 Method4.1 Engineering Majors SurveyThe Engineering Majors Survey (EMS) is a 35-question online survey administered toupwards of 30,000 engineering
Process for Continuous ImprovementA well-structured process of continuous improvement is designed to be self-driven. Itincludes automatic triggers for action and has checks and balances in place to lead theaction plan through completion. Faculty involvement at every step is the key for thesuccess of the program and hence training for faculty becomes a critical element of thisprocess. A continuous improvement model was presented by the author at the CIECconference in 2007.13 This model has been revised to include new assessment tools andpresented in Section a. Section b presents the implementation of the model and efforts toinstitutionalize the process.a. The Assessment and Continuous Improvement ModelThe plan for assessment and continuous
. Schirmer & H. Schelhowe (Eds.), Gender designs it: Construction and deconstruction of information society technology (pp. 175-188). Wiesbaden, Germany: VS Verlag für Sozialwissenschaften.5. Yoder, B. L. (2014). Engineering by the numbers. Retrieved from: https://www.asee.org/papers-and-publications/publications/14_11-47.pdf6. Trimmer, B. (2013). A journal of soft robotics: Why now? Soft Robotics, 1(1), 1-4. doi: 10.1089/soro.2013.00037. Polygerinos, P., Lyne, S., Wang, Z., Nicolini, L. F., Mosadegh, B., Whitesides, G. M., & Walsh, C. J. (2013). Towards a soft pneumatic glove for hand rehabilitation. Paper presented at the 2013 IEEE/RSJ International Conference on Intelligent Robots and
using a Mastery approach. Eachassignment had three or four objectives (Appendix A). All work was marked as unsatisfactory,approaching mastery or mastery. Teachers were permitted to resubmit course products multipletimes or to extend the timeframe needed to complete the course products. After each submission,the instructor provided feedback along with the grade.Methods In our single-case pilot study, course products, NOE perceptions, and teacher reflectionswere assessed. All data were assessed by the first two authors (both engineers and educators)collaboratively and shared with other authors. When a disagreement occurred, authors referredback to the teacher responses and rubrics (Appendix B), discussed their reasoning, and reached
Traditional GCE ‘A’ Levels Grades B,C in Maths, 29 Physics and / or Chemistry Traditional GCE‘A’ Levels Grades ‘A’ / ‘A*’ in 5 Maths, Physics and / or Chemistry (High Achievers) Vocational Qualifications 12 College Based Access Course 3 Undergraduate Bachelor’s Degree 1Having completed the content analysis, the next stage of the project was to put in place a numberof interventions and actions specifically aimed at supporting those students identified as being‘at risk’ of failure. The next section discusses these interventions in some detail
2 3.5769 0.59832 0.653 Lower-middle income 4 3.5769 0.4594 Middle income 13 3.6568 0.4675 Upper-middle income 16 3.6683 0.47478 High income 5 3.9077 0.19911 a. Kruskal Wallis Test b. Grouping Variable: Would you describe your family as: (Mark one)MotivationGiven the respondents’ self-rating of average as compared to their peers, the researcher wasinterested in identifying university-level supports respondents utilized when they encounteredacademic difficulties. The small student-to- Table 10faculty ratio of 1:10 at
instrument as a means ofbetter understanding these groups of students in relation to broader cohorts. ReferencesABET. (2014). Criteria for accrediting engineering programs.Addis, B. (2008). Building (Repr. ed.). London [u.a.]: Phaidon Press.American Society of Civil Engineers. (2008). Civil engineering body of knowledge for the 21st century (Second Edition ed.). Reston, VA: American Society of Civil Engineers. doi:10.1061/9780784409657Anderson, C. L., Lorenz, K., & White, M. (2016). Instructor influence on student intercultural learning during instructor-led, short-term study abroad. Frontiers: The Interdisciplinary Journal of Study Abroad, XXVIII, 1-23. Retrieved from http
. Women in STEM: A Gender Gap to Innovation, ESA Issue Brief #04-11. U.S. Departmentof Commerce Economics and Statistics Administration: Washington, DC, 2011.15. Dasgupta, N.; Asgari, S. Seeing is Believing: Exposure to Counterstereotypic WomenLeaders and its Effect on Automatic Gender Stereotyping. J. Experimental Social Psychology2004, 40 (5), 642−658.16. Gibson, D. E. Role Models in Career Development: New Directions for Theory andResearch. J. Vocational Behavior 2004, 65 (1), 134−156.17. Karukstis, K. K.; Gourley, B. L.; Wright, L. L.; Rossi, M. Mentoring Strategies to Recruitand Advance Women in Science and Engineering. J. Chem. Educ. 2010, 87 (4), 355−356. Fall 2017 Mid-Atlantic ASEE Conference, October 6-7 – Penn State Berks18
of the authorsand do not necessarily reflect the views of the National Science Foundation. We would also liketo acknowledge the contribution of the STEM+C research team at INSPIRE, Purdue University,Imagination Station as well as all the families who participated in this study.ReferencesBarr, V., & Stephenson, C. (2011). Bringing computational thinking to K-12: what is Involved and what is the role of the computer science education community? Acm Inroads, 2(1), 48-54.Bell, P., Lewenstein, B., Shouse, A. W., & Feder, M. A. (2009). Learning science in informal environments: People, places, and pursuits: National Academies Press.Bennett, J., & Müller, U. (2010). The development of flexibility and abstraction in
engineering technology disciplines3. Thespecific ABET ETAC student outcomes for Engineering Technology are4: a. An ability to select and apply the knowledge, techniques, skills, and modern tools of the discipline to broadly-defined engineering technology activities b. An ability to select and apply a knowledge of mathematics, science, engineering, and technology to engineering technology problems that require the application of principles and applied procedures or methodologies c. An ability to conduct standard tests and measurements; to conduct, analyze, and interpret experiments; and to apply experimental results to improve processes d. An ability to design systems, components, or processes for broadly
Undergraduates program.Dr. Marietta Scanlon holds a BS in Chemical Engineering from Tufts University, an SM inMetallurgy from MIT and a PhD in Materials Science and Engineering from The Johns HopkinsUniversity. She is a Lecturer of Engineering in the Division of Engineering, Business andComputing at Penn State University, Berks Campus and serves as co-director of the FiERCEprogram. Her interests include 3D printing technologies as well as STEM education and outreachand innovative teaching delivery methods.References1. Marlett, D. (2015). The Virtual Reality of John Carmack. D CEO, September 2015.2. Carson, E. (2015). Virtual Reality in 2016: The 10 Biggest Trends to Watch. TechRepublic,December 2015.3. Sinclair, B. (2016). The Promise of Virtual Reality
) personal, b) professional, c) academic and d) community engagement. Each ofthese areas includes an ELI common reflection question (see Table 1) which serves as a prompt,to guide formulation of learning objectives in the intended direction. Students personalizeobjectives in each category, based on their unique project application, role and individuality. Table 1. ELI common reflection questions for each category of required learning objective. Category ELI Common Reflection Question Personal How do you expect to grow personally (e.g. in your self-awareness, your spirituality, and how you relate to others) through this experience? Professional Regardless of whether or not your ELI relates
Dissectiblemachine built as DC and AC Motor/Generator (a and b respectively) and also as classroomdemonstrations (c) on fundamental concepts of electro-mechanical energy conversion. The insetphotograph (d) in Figure 4 shows how the dissectible machine was coupled with the actuator forgenerator and motor testing. The dissectible machine’s shaft was modified to accommodate thebelt. Various tests were done on various system configurations and system integrity was sustainedon all of them. Optimization of the motor/generator configuration, and performance visualizationwere achieved through using programmable controller, actuator with built-in sensors and datarecorder thru the personal computer.Integration into the curriculumThanks to its inter-disciplinary
Beta Project.Alex B.: ACE mobile pollution monitorAlex developed the ACE, a low-cost, portable, and smartphone-connected set of sensorsthat measure the exposure of bicyclists to air pollution while cycling in car traffic. Thedevice also tracks the cyclists’ speed, heart rate, and proximity to vehicles. It can be usedto identify routes with high versus low exposure to pollutants, as well as providing inputto crowdsourcing of pollution maps. The project was awarded an additional $5,000 infunding from the Portland State Cleantech Challenge (https://www.pdx.edu/clean-challenge/), which allowed Alex to develop an improved prototype. Alex used thetechnology for his Ph.D. dissertation research. He graduated and continues to do researchon urban air
] Felicia, Patrick (2011). Handbook of Research on Improving Learning and Motivation through Educational Games: Multidisciplinary Approaches, IGI Global. ISBN 978-1-60960-496-7.[2] Learning and Teaching Styles In Engineering Education. Felder, R. and Silverman, L. 7, 1988, Engineering Education, Vol. 78, pp. 674-681.[3] Kolb, D. A. Experiential learning: experience as the source of learning and development. Upper Saddle River, NJ : Pearson Education, Inc., 2014.[4] Bloom, B. S., Engelhart, M. D., Furst, E. J., Hill, W. H., & Krathwohl, D. R. (1956). Taxonomy of educational objectives, handbook I: The cognitive domain.[5] Krathwohl, D. R., Bloom, B. S., & Masia, B. B. (1964). Taxonomy of educational objectives, handbook ii
program (Naval Reserve officers Training Corps) B Black M Sophomore Participated in PBSL 4, Veteran C Hispanic M Junior Participated in PBSL 2 D White M Senior Participated in PBSL 3 5.2 Procedure Our data collection procedure was approved by JU research board (JU IRB: 2016-042).Before each interview and Woofound survey, each participant signed a consent form agree thatthey allow us to present their results without identification information. This consent form wasreviewed and approved by our IRB too. Each interview was digital recorded and transcriptionwere coded to dig out interviewees’ vocabulary and concept
.* • Document results.*Learning Activities: a) Building an OS and then the ROS environment on a Unix micro machine (Ubuntu). Platform will be a NUC-I7, Raspberry Pi, ODroid XU4, or equivalent. This will be provided to the student. b) Interfacing with simulation software and GUI development in Python or C++. Demonstrate marker identification and other visual queues for use in autonomous navigation. Learn and use library functions in OpenCV, NumPY, FreeNect, and other enabling freeware. c) Interfacing with hardware. This includes microprocessors to video devices, joysticks, pan and tilt mechanisms, sensors, etc. Contribute to the community via GitHub and collaborate with U.S. Military Academy
). Emerging adulthood: A theory of development from the late teens through the twenties. American Psychologist, 55(5), 469-480.4. Oishi, L. (2012). Enhancing career development agency in emerging adulthood: An intervention using design thinking. Dissertation, Stanford University.5. Bandura, A. (1989). Human agency in social cognitive theory. American Psychologist, 44(9), 1175-1184.6. Brown, T. (2008). Design thinking. Harvard Business Review, 6, 84-92.7. Reilly, T. (2013). Designing life: Studies of emerging adult development. Dissertation, Stanford University.8. Burnett, B. and Evans, D. (2016). Designing your life: How to build a well-lived, joyful life. New York City, New York: Knopf.9. Crotty, M. (2012). The
northern lowerpeninsula of Michigan; (2) broaden and deepen science and technology teacher/faculty’s contentknowledge and pedagogical tools by engaging them in engineering research to solve open-endedproblems; (3) improve middle school, high school, and community college student science andtechnology achievement, and (4) stimulate student interest in STEM careers through improvedinstruction and curriculum delivered by RET participants in rural Michigan.These objectives were to be achieved through (a) engaging participants in cutting-edge researchon smart vehicles through a vibrant team of CMU engineering faculty mentors, communitycollege faculty (CCF), IST, PST, and undergraduate engineering students; (b) developing skillsand abilities of
Persons with Disabilities in Science and Engineering: 2011, National Science Foundation, Arlington, VA.[6] Seymour, E. and Hewitt, N.M. 1997. Talking about leaving: Why undergraduates leave the sciences, Boulder, CO: Westview Press.[7] Rovai, A. P. 2002. “Development of an instrument to measure classroom community.” The Internet and Higher Education, 5(3), pp. 197-211.[8] Courter, S. S., Millar, S. B., and Lyons, L. 1998. “From the students' point of view: Experiences in a freshman engineering design course.” Journal of engineering education, 87(3), pp. 283-288.[9] Smith, M. K., Jones, F. H., Gilbert, S. L., and Wieman, C. E. 2013. “The Classroom Observation Protocol for Undergraduate STEM (COPUS): A new
International Journal for Service Learning in Engineering, wasfounded. This journal is exclusively devoted to publishing works on the impact of servicelearning in engineering education. One issue in particular, Special Issue: University EngineeringPrograms That Impact Communities: Critical Analyses and Reflection, focused on communityimpact. Schools such asThis increase in project based and service learning has led to a need for students engaged in theseprojects to understand and address stakeholders who do not have a technical background.Zoltowski and Oakes (Carla B. Zoltowski, 2014) discuss this need as well as the need to developand maintain relationships with community partners. Additionally, the difficulty ofunderstanding conflicting priorities of
Homsher for championing the ideaand providing funding for the event.References [1] McIlwee, J. S. and Robinson, J. G., Women in engineering: Gender, power, and workplace culture. SUNY Press, 1992. [2] Lockwood, P., “Someone like me can be successful: Do college students need same-gender role models?,” Psychology of Women Quarterly, vol. 30, no. 1, pp. 36–46, 2006. [3] Rosenthal, L., London, B., Levy, S. R., and Lobel, M., “The roles of perceived identity compatibility and social support for women in a single-sex stem program at a co-educational university,” Sex Roles, vol. 65, no. 9-10, pp. 725–736, 2011. [4] Miyake, A., Kost-Smith, L. E., Finkelstein, N. D., Pollock, S. J., Cohen, G. L., and Ito, T. A., “Reducing the gender
; Jain, A. K. (1996). A self-organizing network for hyperellipsoidal clustering (hec). Neural Networks, IEEE Transactions on, 7(1), 16-29. doi: 10.1109/72.47838920. Tan, P.-N., Steinbach, M., & Kumar, V. (2006). Introduction to data mining (1st ed.). Boston: Pearson Addison Wesley.21. Barab, S. A., Bowdish, B. E., & Lawless, K. A. (1997). Hypermedia navigation: Profiles of hypermedia users. Educational Technology Research and Development, 45(3), 23-41.22. Rousseeuw, P. J. (1987). Silhouettes: A graphical aid to the interpretation and validation of cluster analysis. Journal of Computational and Applied Mathematics, 20, 53-65. doi: http://dx.doi.org/10.1016/0377-0427(87)90125-723. Spector, P. (2011). Cluster analysis
learning-disabled student learn to stay focused in such environments. 3. The Lecture Check11. In this method, the instructor lectures for about 20 minutes. Then poses a question, such as a multiple-choice question, and asks the students to raise their hand if the think ‘a’ is the correct answer. Then the same for ‘b’ and so on. If a large percentage of the class answers incorrectly then the instructor asks the students who answered correctly to turn to their neighbor and explain or convince them of the correct answer. An easy solution is for the instructor to allow any student that does not feel prepared to not answer without penalty or singling them out. This way the learning- disabled students
Paper ID #18097Stickiness of Nontraditional Students in EngineeringMr. William Barrett Corley, University of Louisville William B. Corley, M.S., is the graduate research assistant on this project. He is an experimental psychol- ogy (cognitive concentration) graduate student with the Department of Psychological and Brain Sciences at University of Louisville. He has a bachelor’s degree in psychology and a master’s degree in experimen- tal psychology with a cognitive psychology concentration. His background includes several educational research projects and extensive training in statistical methods.Dr. J. C. McNeil
. The critical role of retrieval practice in long-term retention. Trends in Cognitive Sciences, 15:20–27, 2011.[5] D. Rohrer, K. Taylor, and B. Sholar. Tests enhance the transfer of learning. Journal of Experimental Psychology Learning Memory and Cognition, 36:233–239, 2010.[6] K. E. Train. Discrete Choice Methods with Simulation. Cambridge University Press, second edition, 2009.[7] M. West and C. Zilles. Modeling student scheduling preferences in a computer-based testing facility. In Proceedings of the Third (2016) ACM Conference on Learning @ Scale, pages 309–312, 2016. doi: 10.1145/2876034.2893441.[8] C. Zilles, R. T. Deloatch, J. Bailey, B. B. Khattar, W. Fagen, C. Heeren, D. Mussulman, and M. West. Computerized testing: A
the student course evaluations are reported in Table 4. Students answered eachquestion on a five-point Likert scale where 5 is “Strongly Agree” and 1 is “Strongly Disagree”.Table 4. Engineering Student Course Evaluations Fall 2015 Fall 2016 Section A Section B Section A Section B Evaluation Question (Response Rate: (Response Rate: (Response Rate: (Response Rate: Average 14 of 16 enrolled 14 of 18 enrolled 16 of 17 enrolled 11 of 12 enrolled students, 87.5%) students, 77.8%) students, 94.1%) students, 91.7
., & Corlett EN. RULA: a survey method for the investigation of work-related upper limb disorders. Appl Ergon. 1993;24(2):91-99.18. Plantard P, Shum HPH, Le Pierres AS, Multon F. Validation of an ergonomic assessment method using Kinect data in real workplace conditions. Appl Ergon. 2016:1-8. doi:10.1016/j.apergo.2016.10.015.19. Burns B, Samanta B. Human Identification for Human-Robot Interactions. November 2014:V04BT04A044. doi:10.1115/IMECE2014-38496.20. Morato C, Kaipa KN, Zhao B, Gupta SK. Toward Safe Human Robot Collaboration by Using Multiple Kinects Based Real-Time Human Tracking. J Comput Inf Sci Eng. 2014;14(1):011006-011006. doi:10.1115/1.4025810.21. Bernier E, Chellali R, Thouvenin IM. The MobilAR
allocatedfor the specification of the question, its choices, the feedback to be presented, as well as thelocation in the animation for reviewing that concept. By integrating the customization in theanimation itself, the customizer can see exactly how the question specification and feedback fitwithin the space allocated. The animation will use scroll bars to present the information ifrequired. a. IntroDB Multiple-Choice Question answered correctly b. QueryDB True/False Question answered incorrectlyFigure 1. Samples of Checkpoint Questions and FeedbackEvaluation: ContextBased on teaching assignments at their respective universities, the authors used the checkpointsfor learning for the first time in their classes for computer science majors. One author