intuitive learning” [10]. The underlying themefrom their research indicates that technology students typically prefer an active, hands-onapproach. A survey carried out b y Ibrahim indicated that students loved the idea of learningby doing as t h e y learned a great deal about microcontrollers and their applications bysolving real engineering problems [6].The TransformationUnder the original version of the course, the students completed weekly laboratory experimentssimilar to the ones described by Taylor and Jackson [7] and Rosen and Carr [1]. Each laboratorysession was approximately two hours in length and focused on basic understanding of thatweek’s particular subject matter. Very little time was available to tackle real world problems. Abrief
/Innovation_Through_Diversity.pdf , accessed February 12, 2017. 5. Association of Public and Land Grant Universities, http://www.aplu.org/about-us/history- of-aplu/what-is-a-land-grant-university/index.html, accessed February 12, 2017. 6. Hurtado, S. M., K. Eagan, T. Figueroa, and B. Hughes. "Reversing underrepresentation: The impact of undergraduate research programs on enrollment in STEM graduate programs." (2014). 7. Institute for Higher Education Policy, “Supporting First-Generation College Students through Classroom-Based Practices”, September 2012.
, Kitts serves as the Mission Operations Director for a series of NASA spacecraft, as an affiliate researcher at the Monterey Bay Aquarium Research Institute, and as a KEEN Fellow for Santa Clara’s program in undergraduate innovation and entrepreneurship education. Kitts’ previous experience includes service as a satellite constellation mission controller in the U.S. Air Force, as a technical con- tractor for NASA Ames Research Center, and as a DoD Research Fellow at the U.S. Philips Laboratory. He holds degrees from Princeton University, the University of Colorado, and Stanford University. He is a Fellow of the American Society of Mechanical Engineers.Ms. Anne Mahacek, Santa Clara University Anne Mahacek received her
students worked on these research teams they were asked to do peerassessments of their team members. Many times students want to be nice to everyone and sayeveryone did above average. To avoid this the following method was used. For a four personteam, you need to assign 400 points to the team (including yourself). If some gets more than a100, then someone else must get less than 100. An example from fall 2014 is shown below intable 4. The shaded boxes are scores that students gave to themselves. Table 4 Example of student peer assessments of team members Assessments received Assessments Student A Student B Student C Student D Range in
: Section Details for Fall 2015 Section Instructor Enrollment Category A Prof Y 50 Control B Prof Z 22 Intervention C Prof X 44 Control D Prof X 48 InterventionSpecifics of the control and intervention groups are discussed in the following section.In Spring 2016, five sections of the class were offered. Table 2 shows some details for Spring2016. Table 3 shows similar details for Fall 2016 when Prof. Z coordinated and instructed
a good learning experience. They were, also,more likely to recommend the session to others. Many showed interest in learning more. Binary-To-Decimal Conversion Emulator: In addition to the device being demonstratedat a number of events, in an informal setting, such as the Maker-Faire and Discover EngineeringDay, the emulator was demonstrated at an Electrical Engineering Laboratory event conducted forhigh school students in-order to expose them to the field of Electrical Engineering. Thirty-twostudents participated in the lab event. As part of the exit survey conducted, students were askedtheir views on three statements to assess the impact the B-to-D converter made on theirunderstanding of the underlying concept. Figure 5 depicts the
command of the material.Requiring extra instruction between the second and third attempts at a concept was one of twosignificant changes made during the semester this scheme was used. The other was a broadeningof the retake criteria. After the first exam cycle, the “Almost Correct” score window was widenedto include the high B, making its floor 88% – still higher than possible on the second attempt, butalleviating some of the grading burden (at a school with no graduate teaching assistants). Table 1: Exam scoring scheme (initial) Attempt at Problem Assessment 1st
. Daneshi, H. Khorashadi-Zadeh, "Microgrid energy management system: A study of reliability and economic issues", Power and Energy Society General Meeting 2012 IEEE, pp. 1-5, 2012, ISSN 1944-9925.[2] B. Kroposki, R. Lasseter, T. Ise, S. Morozumi, S. Papathanassiou, N. Hatziargyriou, "Making Microgrids Work," IEEE Power and Energy Magazine, vol. 6, no. 3, pp. 40-53, 2008[3] I. Colak, "Introduction to smart grid," 2016 International Smart Grid Workshop and Certificate Program (ISGWCP), Istanbul, 2016, pp. 1-5.[4] G. Fabbri, C. M. Medaglia, D. Sbordone and B. Di Pietra, "A tool for the analysis of energy systems in Smart Cities," 2016 IEEE 25th International Symposium on Industrial Electronics (ISIE), Santa Clara, CA, 2016, pp
before coming back to campus, and offering coping resources such as a debriefingsession, counseling or stress relief techniques. 12References[1] Heyborne, R. L. (1978). A crisis in cooperative education. Engineering Education. 68(4), 334-337.[2] Wilkins, J. E. (1987). Factors influencing student participation in cooperative educationprograms at selected post-secondary institutions. Retrieved from ProQuest Dissertations andTheses. (Order No. 8811649).[3]Fletcher, T. L., Main, J. B., Ramirez, N. M., & Ohland, M. W. (2014). From Interest to Decisionin Cooperative Education Programs. Frontiers in Education Conference (FIE), IEEE, 1-3.[4] Ramirez, N. M
P. Magleby, Carl D. Sorensen, Bret R. Swan, and David K. Anthony. A survey of capstone engineering courses in north america. Journal of Engineering Education, 84(2):165–174, 1995. ISSN 2168-9830. doi: 10.1002/j.2168-9830.1995.tb00163.x. URL http://dx.doi.org/10.1002/j.2168-9830.1995.tb00163.x. [3] N. Hotaling, B. B. Fasse, L. F. Bost, C. D. Hermann, and C. R. Forest. A quantitative analysis of the effects of a multidisciplinary engineering capstone design course. Journal of Engineering Education, 101(4):630–656, 2012. [4] R. L. Miller and B. M. Olds. A model curriculum for a capstone course in multidisciplinary engineering design. Journal of Engineering Education, 83(4):311–316, 1994. [5] J. T. Allenstein, B. Rhoads
limited web access to prevent them from searching for solutions to the design problem onother web sites.Coding development. In typical protocol analyses the researchers commence with a pre-existingcoding scheme and modify it based on the task and events in the current protocol. In this projectwe will use a principled coding scheme based on the FBS ontology developed by Gero andcolleagues (Gero, 1990; Gero & Kannengiesser, 2004). The FBS ontology contains three types ofvariables: Function (F), Behavior (B) and Structure (S). Function (F) represents the designintentions or purposes of the design; behavior (B) represents the object’s attributes that can beeither directly derived from a representation of the object (Bs) or expected to be derived
representative “takeaways” from a classmate wereselected from the overall set captured in real time during the presentations. Subsequently, theserepresentative “takeaways” were coded and aligned with the corresponding element of theinnovation fishbone diagram, including: A) Triggers; B) Personal Attributes; C) Skills;D) Process for Innovation; and E) Environment. A) Triggers (Customer (or Business) or Societal Need OR Technical Opportunity)Engaging with customers is critical to successful innovation management, and this realizationhas been powerful for multiple innovation management interns.Example Customer Need takeaways:“Learn about your customers – each one is different.”“Understanding users’ needs and wants is fundamental. Profit maximization is
Paper ID #19983The Social Mechanism of Supporting Entrepreneurial Projects Beyond theClassroomMr. Alexander Joseph Zorychta, University of Virginia Alex Zorychta finds, guides, connects, and builds community for student entrepreneurs. He has been guiding and building community for student entrepreneurs for the past four years. A student entrepreneur himself, he was triggered by winning the grand prize of the UVA Entrepreneurship Cup. While pursu- ing this startup post-graduation for two years near the University, he helped to guide other student en- trepreneurial projects. He joined the staff of the Technology
rubric gradingcan be good assessments for students and their work, but other forms of assessment may showevidence for growth. Blogs and other reflections could help assess student progress [20]. As theCEE Department increases its commitment to diversity and inclusion, the faculty will strive todiscover multiple avenues to improve the current curriculum.AcknowledgementThis material is based upon work supported by the National Science Foundation underIUSE/PFE:RED Grant No. 1632053 and EEC 1539140. Any opinions, findings, and conclusionsor recommendations expressed in this material are those of the author(s) and do not necessarilyreflect the views of the National Science FoundationReferences[1] S. Hooker and B. Brand, " College knowledge: A
://www.nvision3d.com/success-stories/nvision-fain.html3. “Mission Support Inc. Overhauls U.S. air Force B-52s using the FaroARM,” www. Faro.com4. “Blade Inspection and Repair,” Aerospace Manufacturing and Design Magazine, Oct 2012, Page 82.5. “3D Printing: A new Mindset in Product Design,” NASA Tech Briefs Magazine, Mar. 2013, page16.6. “3D Printing’s New Materials,” Desktop Engineering Magazine. Nov 2014, Page 53.7. “Design and Fabrication of a Radio Frequency Grin Lens Using 3D Printing,” Aerospace & Defense Technology Magazine, June 2014 , page 448. “Aluminum Rocket Engine Injector Fabricated 3D Additive Manufacturing,” NASA Tech Briefs Magazine, June 2015, page44.9. “3D Printer Creates First Object in
and Feedback,” a necessary condition for knowledgeattainment and retention and skill development; and (3) “Balance,” wherein the instructorbalances the needs of students with different learning styles, provides training in both basics andhigh-level skills, blends lecturing and active learning, and assigns individual and group work.22-31Nine learner-centered teaching techniques based on those principles were implemented. Thetechniques fell into four categories: (A) Course setup, (B) Course delivery, (C) Formativeassessment, and (D) summative assessment. The nine techniques 1) through 9) are nowdiscussed in order in the categories (A) through (D).(A) Course setup1) Graphic organizer targeted to authentic VLSI applications in industry and
/ITU- T/recommendations/rec.aspx?rec=y.2060 , accessed on Feb. 2017. 6. Stapko, T.J., “Practical Embedded Security: Building Secure Resource-Constrained Systems”. Amsterdam: Newnes, 2008. 7. Pfleeger, Charles, et. al., Security in Computing”, 5th Edition, Prentice Hall, 2015. 8. Mu, D., Ma, B., Mao, B., & Hu, W., A bottom-up approach to verifiable embedded system information flow security. IET Information Security, 8(1), 12–17. doi:10.1049/iet-ifs.2012.0342, 2014. 9. Xiang, W., Zexi, Z., Ying, L., & Yi, Z. (2013). A design of security module to protect program execution in embedded system. 2013 IEEE International Conference on Green Computing and Communications and IEEE Internet of Things and
of comparable STEM students is 34.5%, thus establishing a target of 114% over the baseline. Milestones include: (a) completion of at least 30 units within two years, (b) completion of an Associate in Arts (AA) degree, (c) attaining “transfer ready” status, (d) transferring to a four-year university.Objective #3 The applicant pool of SESMC students who are in an underrepresented ethnic group will be at least 60% and those who are female will be at least 40%. The baseline percentage of underrepresented students in STEM programs was 45%, while the percent female in STEM was 29%; the targets represent 33% increases over the baselines.Objective
. (1993). Reliability and PredictiveValidity of the Motivated Stradigies for Learning Questionnaire (MSLQ). Educational andPsychological Measurement 53, 801-813.Rath, T., and Conchie, B. (2008). Strenghts Based Leadership: Great Leaders, Teams, and WhyPeople Follow. Gallup: New York, NY.Semsar, K., Knight, J.K., Birol, G., and Smith, M.K. (2011). The Colorado Learning Attitudesabout Science Survey (CLASS) for use in Biology. CBE Life Sci Educ 10, 268-278.Shi, J., Wood, W.B., Martin, J.M., Guild, N.A., Vicens, Q., and Knight, J.K. (2010). Adiagnostic assessment for introductory molecular and cell biology. CBE Life Sci Educ 9, 453-461.Singer, S.R.N., N.R.; Schweingruber, H. A. . (2012). Discipline-Based Education Research:Understanding and
engineering education. Springer, 10(2), 343–351.Presidential Commission on the Space Shuttle Challenger Accident. (1986). Report to the president by the presidential commission on the space shuttle challenger accident (Tech. Rep.).Richards, L. G., & Gorman, M. E. (2004). Using case studies to teach engineering design and ethics. Proceeedings of the 2004 American Society for Engineering Education Annual Conference & Exposition.Vohs, K. D., Baumeister, R. F., Schmeichel, B. J., Twenge, J. M., Nelson, N. M., & Tice, D. M. (2008). Making choices impairs subsequent self-control: A limited-resource account of decision making, self-regulation, and active intiative. Journal of Personality and Social Psychology
Publications.Fredborg, L. (2013). No Ti. Retrieved January 23, 2017, from http://www.thedoctools.com/downloads/basComments_Extract.basKrippendorff, K. (1980). Content analysis: An introduction to its methodology (2nd ed). Thousand Oaks, CA: Sage Publications.Lincoln, Y. S., & Guba, E. G. (1985). Naturalistic Inquiry. Newbury Park, CA: Sage Publications.Lovejoy, J., Watson, B. R., Lacy, S., & Riffe, D. (2016). Three Decades of Reliability in Communication Content Analyses: Reporting of Reliability Statistics and Coefficient Levels in Three Top Journals. Journalism & Mass Communication Quarterly, 93.4 (2016, 1135–1159.Miles, M. B., & Huberman, A. M. (1994). Qualitative data analysis: An expanded sourcebook (Second Edi
as making a B+ in anintroductory class).Power of story: In this narrative research project, we found that the power of an individual’sstory is difficult to ignore. Through students stories and their lived experiences in engineering,we can get a vibrant snapshot of engineering to begin to transform engineering education toattract diverse people to engineering and to ultimately be situated to address grand challengesthat we are facing today.Sense of community: In the second and third year, many students began to experience a sense ofcommunity and this was the time that they began to experience more positive emotions anddemonstrated qualities such as ambition and resilience.Family influence: In the fourth year, students from underrepresented
, Title II, Part B) administered by the Wyoming Department of Education(MSP Grant #1601506MSPA2); and 2) NSF Noyce – called SWARMS - (NSF Grant# 1339853).ReferencesBasu, S., Dickes, A., Kinnebrew, J. S., Sengupta, P., & Biswas, G. (2013). CTSiM: A Computational Thinking Environment for Learning Science through Simulation and Modeling. In CSEDU (pp. 369-378).Berland, L. K., & Reiser, B. J. (2011). Classroom communities' adaptations of the practice of scientific argumentation. Science Education, 95(2), 191-216.Blikstein, P. (2011, February). Using learning analytics to assess students' behavior in open- ended programming tasks. In Proceedings of the 1st international conference on learning analytics and knowledge (pp. 110-116
listed by Dunbar & Klahr10 and Giere.11 1. Problem solving 6a. Deductive Reasoning 2. Design and modeling 6b. Inductive Reasoning 3. Hypothesis testing 6. Reasoning à 6c. Abductive Reasoning 4. Concept formation 6d. Casual Reasoning 5. Conceptual change 6e. Analogical ReasoningThe processes involved in practices of engineers and scientists are actually similar and can beconsidered of having three spheres of activity, namely: a) investigation and empirical inquiry,b) construction of a model (e.g., a scientific concept/theory or an engineering design) usingreasoning, and creative thinking
performance. Journal of Educational Psychology. 82: 33–40. 5. Pintrich, P.R. (2000). An achievement goal perspective on issues in motivation terminology, theory, and research. Contemp. Educ. Psychol. 2000, Vol. 25, pp. 92–104. 6. Matusovich, H., Streveler, R., Miller, R., and Olds, B. (2008). Will I succeed in engineering? Using expectancy-value theory in a longitudinal investigation of students' beliefs. Proceedings of the ASEE Annual Conference. Pittsburgh, PA. 7. Jones, B. D., Paretti, M. C., Hein, S. F., & Knott, T. W. (2010). An Analysis of Motivation Constructs with First-Year Engineering Students: Relationships Among Expectancies, Values, Achievement, and Career Plans. Journal of Engineering Education
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