: Relation to self-efficacy,cohesion, and performance. Journal of Vocational Behavior. 2006;68(1):73-84.31. Marra R, Rodgers K, Shen D, Bogue B. Women Engineering Students and Self-Efficacy: A Multi-Year, Multi-Institution Study of Women Engineering Student Self-Efficacy. Journal of Engineering Education. 2009:27-38.32. Paretti M, Jones BD, Matusovich H, Moore J. Work in progress — A mixed-methods study of the effects offirst-year project pedagogies on the motivation, retention, and career plans of women in engineering. In: Frontiers inEducation Conference (FIE), 2010 IEEE.; 2010:T4H-1-T4H-3.33. Perna L, Lundy-Wagner V, Drezner ND, et al. The Contribution of HBCUS to the Preparation of AfricanAmerican Women for Stem Careers: A Case Study. Res High
) “Interprofessional Learning in Higher Education: Bridging Professional Cultures”,Journal of Cooperative Education & Internships, Vol. 44 (2), pp. 23-25.13. D. Hodges, B. Smith and P. Jones, (2004), The Assessment of Cooperative Education, International Handbookfor Cooperative Education. USA: Word Association for Cooperative Education, pp. 49-65.14. J. Moon, (2006). A Handbook of Reflective and Experiential Learning: Theory and Practice. London: RoutledgeFalmer.15. J. Griffin, G. Lorenz and D. Mitchell, (2010) “A Study of Outcomes-Oriented Student Reflection DuringInternship: The Integrated, Coordinated, and Reflection Based Model of Learning and Experiential Education”,Journal of Cooperative Education & Internships, Vol. 44 (2), pp. 42-50.16. D
. Journal of Counseling Psychology 52, 84-92 (2005).15 Schaefers, K. G., Epperson, D. L. & Nauta, M. M. Women's Career Development: Can Theoretically Derived Variables Predict Persistence in Engineering Majors? Journal of Counseling Psychology 44, 173- 183 (1997).16 Lent, R. W., Lopez Jr, A. M., Lopez, F. G. & Sheu, H. B. Social Cognitive Career Theory and the Prediction of Interests and Choice Goals in the Computing Disciplines. Journal of Vocational Behavior 73, 52-62 (2008).17 Silvia, P. J. Self-Efficacy and Interest: Experimental Studies of Optimal Incompetence. Journal of Page
25.526.6environment, see Figure 2. A detailed lab is provided to help students adapt to the newprogramming language and the simulation’s graphical user interface (GUI). Figure 2: 1st Lab, I/O Simulation GUIThe second, third, and fourth labs are more open ended with three different levels of criteria thatreflect A, B, and C level work. The second lab simulates a garage door application, see Figure 3,the third simulates a silo/filling operation, see Figure 4, and the fourth lab simulates a batchmixing application, see Figure 5. The simulation program has many realistic features andsimulates likely safety and programming errors, for instance if the silo filling valve is left open itwill flood the conveyor and set off alarms. The
. Michelene; Miriam Bassok; Matthew W. Lewis; Peter Reimann; Robert Glaser Chi. Self-explanations: How students study and use examples in learning to solve problems. In Cognitive Science, pages 145–182, 1989. [2] Richard E. Mayer. Cognitive, metacognitive, and motivational aspects of problem solving. Instructional Science, 26(1-2):49–63, 1998. [3] A.L. Brown and J.D. Day. Macrorules for summarizing texts: The development of expertise. Journal of Verbal Learning and Verbal Behavior, 22:1–14, 1983. [4] P.S. Steif, J. Lobue, A. L. Fay, and L. B. Kara. Improving problem solving performance by Page 25.246.9 inducing talk about salient
learning experience is taking place,including the past offering when 100% of the students received at least B- (80%) letter grade.Course evaluations also indicated ratings mainly in the range of 4 - 5 in 5 scale.In summary, students gain 15 weeks of hands-on practical experience on industrial grade robots.They learn about trajectory planning, program planning and logic with flow-charts and state-flowdiagrams. The students also study the wiring process of inputs and outputs to the robotcontroller. But, most importantly they get exposed to scenarios replicating real-life cases such ashand-exchange and setting of a TOOLFRAME, palletizing and depalletizing, and mostimportantly wiring and programming of an actual work-cell, possibly twice – one with an
possible answers: i) Excellent (A), Readingsare thoroughly outlined or summarized, and most assigned problems are worked to completion;ii) Good (B), Most readings are outlined or summarized, and many assigned problems areworked to completion; iii) Fair (C), A few readings are summarized, and some assignments arecompleted. Minimum passing effort; iv) Poor (D), Little, if any summary work, and very fewassignments completed. Below passing standard; v) Failure (F), Little or no evidence of readingor working assigned problems before class. Feedback from student course evaluation surveyssuggest that notebooks be collected approximately once every four weeks.Determining final grades: criterion-referenced gradingAssessment data for the technical content
include these skills into engineering solutions throughout theircourse. This method of using assignments throughout the curriculum allowed faculty tounderstand how students were building their competence throughout their collegiate careers toobtain the final desired level of performance 12.B. Depth of CE ProgramsThere is also motivation to ensure students are obtaining more depth on key topics, particularly Page 25.1217.4engineering design. One university implemented a converging–diverging model of design for asophomore –level course on engineering design and technical writing. This course initially useda semester long design project, but
results may only bemeaningful to specific instructors, given the unique nature of any one course, although we expectthat instructors who use question and answer style discussion boards will also find these resultsuseful. The next step in the study is to interview a second teacher, whose course workflows havebeen developed, starting with the results from this investigation.AcknowledgementsThe work was supported by the National Science Foundation, under Human-CenteredComputing grant #0917328. Page 25.177.8Bibliography 1. Deelman, E., Singh, G., Su, M., Blythe, J., Gil, Y., Kesselman, C., Mehta, G., Vahi, K., Berriman, G. B., Good, J
: Author. Retrieved January 8, 2008, from http://www.nae.edu/nae/engecocom.nsf/weblinks/MKEZ-68HQMA?OpenDocument2. Shartrand, A., P. Weilerstein, M. Besterfield-Sacre, and K. Golding. “Technology Entrepreneurship Programs in U.S. Engineering Schools: An Analysis of Programs at the Undergraduate Level." 2010 ASEE Annual Conference, Louisville, KY, June 20-23, 2010.3. Shartrand, A., P. Weilerstein, M. Besterfield-Sacre, and B. Olds. "Two Tools for Assessing Student Learning in Technology Entrepreneurship." 38th at the ASEE/IEEE Frontiers in Education Conference, Saratoga Springs, NY, October 22-25, 2008.4. see http://www.pui-eship.org/ for details5. Covin, J. G., & Slevin, D. P. (1989). Strategic management
survey 1 0 1 2 3 4 5 6 7 8 9 10 11 12 Knowledge Outcome Index (b) Figure 1. Pre and post survey results for knowledge outcomes: a) for CS470, Winter 2011; 2011 b) for EE440, Spring 2011. Similarly, the pre and post survey also measured the skill growth in CS470 and EE440. Table 3lists the specific skill outcomes (which are the same for both courses).Table 3. Skill sets evaluated via pre and post surveys in CS470 and EE440
identify patterns in the student perceptions of the engineering design processand the utility of science and math content. b In the group interviews, one student often dominated the conversation or all students wouldagree and co-construct a response. This made it near impossible to reliably attribute beliefs to Page 25.1191.4individual students. As such, we collapsed across the students in the group interviews
AC 2012-3661: PREPARING STUDENTS FOR WRITING IN CIVIL EN-GINEERING PRACTICEProf. Susan Conrad, Portland State University Susan Conrad is a professor of applied linguistics at Portland State University, where she teaches discourse analysis courses and collaborates with civil engineering faculty and local practitioners to study writing in civil engineering.Mr. Timothy James Pfeiffer P.E., Foundation Engineering, Inc.Mr. Tom Szymoniak, Portland State University Tom Szymoniak is a Civil Engineer with 28 years of professional experience. He is currently a full-time instructor at Portland State University in the Department of Civil and Environmental Engineering. His main area of focus is teaching the underclass students
the worst and should be deleted? Explain. 4. Do you have general suggestions for improvement of the module? Explain. 5. Please select the answer that best describes the amount of times you attended tutoring or used an online help tool. A. Never B. A few times C. Frequently D. Very FrequentlyResults from the long-term follow-up data will be available until the end of the Spring 2012semester. The first offering of Module 2 and Module 3 are currently underway. Module 2 isentitled: Math Applications in Disease Epidemiology – Modeling the spread of contagiousdiseases, with 31 students, and Module 4 is entitled: Math Applications in Health Hazards fromElectric Current
AC 2012-3651: FROM THEORY TO IMPLEMENTATION: MEETING IN-DUSTRY NEEDS THROUGH UNIVERSITY AND COMMUNITY COL-LEGE COLLABORATION IN DIGITAL LOGIC DESIGNDr. Nasser Alaraje, Michigan Technological University Nasser Alaraje is currently the Electrical Engineering Technology Program Chair, as well as a fac- ulty member at Michigan Technological University. He taught and developed courses in the computer engineering technology area at the University of Cincinnati and Michigan Technological University. Alaraje’s research interests focus on processor architecture, System-on-Chip design methodology, Field- Programmable Logic Array (FPGA) architecture and design methodology, engineering technology ed- ucation, and hardware
cracks in the shell). The egg may be surrounded with a protective covering.However, the covering cannot penetrate the shell or be bonded to it. GDC B – Vertical Limit Design and construct a mechanical system that will deploy froma prescribed initial size to a freestanding structure that reaches as high as possible. Deploymentmust be automatic upon activation of a trigger mechanism. The base structure is to be fixed tothe floor. For example, the system may be composed of a mechanism for extending a boom ortruss structure. GDC C – Reward Design and construct a mechanical system that will launch a YorkPeppermint Pattie taped to a CD so it hits an 9' W x 6' H target placed as far from the launchpoint as possible. The target will be
cracks in the shell). The egg may be surrounded with a protective covering.However, the covering cannot penetrate the shell or be bonded to it. GDC B – Vertical Limit Design and construct a mechanical system that will deploy froma prescribed initial size to a freestanding structure that reaches as high as possible. Deploymentmust be automatic upon activation of a trigger mechanism. The base structure is to be fixed tothe floor. For example, the system may be composed of a mechanism for extending a boom ortruss structure. GDC C – Reward Design and construct a mechanical system that will launch a YorkPeppermint Pattie taped to a CD so it hits an 9' W x 6' H target placed as far from the launchpoint as possible. The target will be
AC 2012-3395: DESIGN FOR THE OTHER 90% AND APPROPRIATETECHNOLOGY: THE LEGACIES OF PAUL POLAK AND E.F. SCHU-MACHERLindsey Anne Nelson, Purdue University, West Lafayette Lindsey Nelson is a doctoral student in engineering education. She has a B.S. in mechanical engineer- ing from Boston University and a M.A. in poverty and development from the Institute of Development Studies housed at the University of Sussex in England. Her research interests include sustainable de- sign, engineering design methodologies, the public’s understanding of engineering, poverty mitigation, global participation, and engineering education. She is a passionate advocate for inclusive and socially just engineering professional practice
] [First Authors Last Name] Page 17 test data for introductory physics courses. American Journal of Physics, 66(1), 64-74. doi: 10.1119/1.18809.Hasna, A. M. (2008, July). Problem based learning in engineering design. Paper presented at the SEFI 36th Annual Conference 2008 Aalborg, DK.Holt, J. E., Radcliffe, D. F., & Schoorl, D. (1985). Design or problem solving - a critical choice for the engineering profession. Design Studies, 6(2), 107-110.Hora, M. T. & Millar, S. B. (2008). A final case study of SCALE activities at UW-Madison: The influence of institutional context on a K–20 STEM education change initiative. WCER Working Paper No. 2008-6: Wisconsin Center for Education Research.Hsieh, C
ability).Results "Validity refers to the degree to which evidence and theory support the interpretation oftest scores entailed by proposed uses of tests" [55]. Evaluating validity requires developingsound scientific evidence for judging the interpretability of the instrument’s results andsubsequent decision-making based on this evidence [55, 56]. There are a variety of types ofevidence that may be used to validate an instrument, depending on the proposed interpretationand use of the resulting scale scores [55, 57]. For this paper we focused on aspects of validitythat were addressed through the scale development process. The results are organized based onthe type of validity examined: a) content validity, b) structural or construct validity
course they tutor with an A or B. Tutors are selected based on theiracademic history, previous tutoring experience, and faculty or instructor references. All tutorsare required to complete GEEKS training which includes instruction about effective ways totutor and how to differentiate the needs of students. Required weekly meetings provide tutors anopportunity to visit with advisors and other GEEKS tutors to discuss successful strategies andways to improve the tutoring provided. Tutors work closely with course instructors to ensure thatthey are prepared to tutor students in the areas being covered in classes. When possible,additional opportunities are provided for tutors to be well informed and prepared. For example,in fall 2011, tutors for
classroom,’ Retrieved: September 20, 2011. 15. Hou, Huei-Tse, ‘Exploring the Behavioural Patterns in Project-Based Learning with Online Discussion: Quantitative Content Analysis and Progressive Sequential Analysis,’ Turkish Online Journal of Educational Technology - TOJET, v9 n3 p52-60 Jul 2010 16. Goldberg, Nisse A.; Ingram, Kathleen W., ‘Improving Student Engagement in a Lower-Division Botany Course,’ Journal of the Scholarship of Teaching and Learning, v11 n2 p76-90 Apr 2011 17. Khalid, A., Nuhfer-Halten, B., Vandenbussche, J., Colebeck, D., Atiqullah, M., Toson, S., Chin, C., ‘Effective multidisciplinary active learning techniques for freshmen polytechnic students,’ Intellectbase International
models aremathematical in nature causing the modeling process to be more analytical. Adding to that the commonthinking preferences of engineering faculty and the majority of students are analytical it becomes clearthat creativity could be absent.Example 4:Studies on the thinking preferences of engineering students, based on the HBDI model shown in Fig. 7,were conducted at the University of Toledo6, and the University of Pretoria in South Africa7. Bothstudies concluded that diversity exists in profiles, but these profiles on average tend to be tripledominant with the primaries in quadrant A, then D and B and secondary in C as shown in Fig. 8. Figure 7 - The Herrmann whole brain model7
Economy of the 21st Century, Rising above the gatheringstorm: Energizing and employing America for a brighter economic future. The National Academies Press:Washington, D.C., 2005.3. Melsa, J. L., The Winds of Change, ASEE Banquet Keynote Speech. In American Society forEngineering Education Annual Conference and Exposition, Honolulu, Hawaii, 2007.4. Raizen, S. B., Technology education in the classroom: Understanding the designed world. Jossey-BassPublishers: San Francisco, CA, 1995.5. Brophy, S.; Klein, S.; Portsmore, M.; Rogers, C., Advancing engineering education in P-12 classrooms.Journal of Engineering Education 2008, 97, (3), 369-387.6. Mehalik, M. M.; Doppelt, Y.; Schunn, C. D., Middle-school science through design-based
chairing committees and commissions inand outside of the government [16].Dr. Gregory B. Jaczko is the current Chairman of the United State Nuclear RegulatoryCommission. As chairman, his responsibilities include conducting administrative, organizational,long-range planning, budgetary, and certain personnel functions of the agency, and serving as theauthority for Nuclear Regulatory Commission functions pertaining to a potential emergencyinvolving a licensee of Nuclear Regular Commission. Prior to the Chairmanship, Dr. Jaczkoserved as the appropriations director and science policy advisor for Senator Harry Reid as well asa congressional science fellow for Representative Markey. Chairman Jaczko has a Bachelor’sDegree in Physics and Philosophy and a
to persist within a given major or switch to anotherare complex. The factors that affect student decisions can be broadly classified into three groupsas (a) academic resources, (b) internalization and perceptions of the major and career, and (c)climate and experiential effects. The academic resources include lectures, recitations, andlaboratories; faculty and teaching assistants; university services such as advisors and careerplacement; and academic services such as study centers and academic progress monitoring.Internalization refers to perceptions of the self including confidence, self-efficacy, anddetermination to succeed. Perceptions of the major and career include students’ interest inchoosing and retaining engineering as a major and a
-based weekly assignment as means ofencouraging students to keep up with the material.Presentations served as a powerful tool to personally engage individual students. Roughly a halfof the presentation topics, c.f. Appendix B, were based on the students current/intended researchtopics. Presentation reviews served to both introduce students to the concept of peer-reviewprocess in scientific literature and to establish personal connection between the students in class.To accomplish the latter goal, students from different campuses were purposefully chosen toperform the reviews.Figure 1. Statistics of the hourly/daily access (number of visits) to web-based content (recordedlectures, posted homework assignments, etc.). Correlation between major
Conference, 2009. IPCC 2009. IEEE International. 2009.5. House, R., A. Watt, and J.M. Williams. Mapping the Future of Engineering Communication: Report on a Research Study of Engineering Faculty and Their Teaching of Writing as a Function of the ABET/EAC Criteria. in International Professional Communication Conference. 2007. Seattle.6. Paretti, M.C., et al., Reformist Possibilities? Exploring Cross-Campus Writing Partnerships. WPA: Writing Program Administration, 2009. 33(1-2): p. 74-113.7. Shwom, B., et al., Engineering Design and Communication: A Foundational Course for Freshmen. Language and Learning Across the Disciplines, 1999. 3(2): p. 107-112.8. Waggenspack, W.N.J., CxC and Engineering: A New
student’s overallexperience, satisfaction, and confidence with the course. Many entry-level students arrive at college undecided as towhich major they want to pursue. Our assertion is that if we can improve these factors for all of our students, thenwe can improve the percentage that chooses to pursue a STEM-based major. We further seek to learn whetherseating assignments can affect a student’s interest and perceived level of difficulty within the course. REFERENCES[1] M. T. Carlisle, T. Wilson, J. Humphries and S. Hadfieldand, "RAPTOR: a visual programming environment for teaching algorithmic problem solving," ACM SIGCSE Bulletin, 2005.[2] F. D. Becker, R. Sommer, J. Bee and B. Oxley
you influence the students’ academicand career choices?” and, “How did you influence the students’ conceptions of science andengineering?”. The complete undergraduate student and graduate student/faculty member Page 25.1308.7interview protocols can be found in Appendices A and B. 63.0 Results and Discussion3.1 Program Demographics In six years of this REU program, 64 Aundergraduate students have been supportedthrough funding from the National ScienceFoundation. These students are from 24different states and 46 institutions (Figure 1