and holder of the Ned Adler Professorship in Mechanical Engineering at Louisiana State University. He obtained both his baccalaureate and master's degrees from LSU ME and his doctorate from Purdue University's School of Mechanical Engineering. He has been actively engaged in teaching, research and curricula development since joining the faculty in 1988. He currently serves as Co-Director of the Education and Outreach program with LSU’s NSF-EPSCoR Center for Bio-Modular Multi-Scale Systems (CBM2) and is responsible for the development and implementation of several of the centers K-12 and public outreach programs.Lillian B Bowles, Louisiana State University Lillian Bridwell-Bowles is a
AC 2008-679: AN INVESTIGATION OF GAPS IN DESIGN PROCESS LEARNING:IS THERE A MISSING LINK BETWEEN BREADTH AND DEPTH?Christine B. Masters, Pennsylvania State University Christine B. Masters is an Assistant Professor of Engineering Science and Mechanics at The Pennsylvania State University. She earned a PhD from Penn State in 1992. In addition to raising four children with her husband of 20 years, she has been teaching introductory mechanics courses for more than 10 years, training the department graduate teaching assistants for 7 years, coordinating the Engineering Science Honors Program undergraduate advising efforts for 5 years and currently participates in a variety of engineering
: A Study of the Impact ofEC2000. 2006: ABET. http://www.abet.org/papers.shtml, accessed.9. R. Martin, B. Maytham, J. Case and D. Fraser, Engineering graduates' perceptions of how well theywere prepared for work in industry. European Journal of Engineering Education, 2005. Vol. 30, No. 2, pp. 167-180.10. N. Spinks, N. Silburn and D. Birchall, Educating Engineers for the 21st Century: The Industry View,Henley, England: Henley Management College, 2006.11. V. K. Domal and J. P. Trevelyan. Comparing Engineering Practice in South Asia with Australia. inAmerican Association for Engineering Education (ASEE) Annual Conference. 2008. Pittsburgh.(submitted forreview).12. A. Enshassi and A. Hassouna, Assessment by employers of
environment, but thought activities in other disciplines possessedmany similar design features. Table 1 illustrates Goel and Pirolli’s twelve features of adesign task with a condensed description of each feature. The letters A- L are used todenote each characteristic, as is the style in Goel and Pirolli’s presentation of the features.Table 1. Goel and Pirolli’s Features of a Design Task Feature Description A. Distribution of Incomplete specification of start and goal state complete information unspecfication of transition between start and goal state. Two types of constraints: 1- Non-negotiable: nomological B. Nature of constraints (natural laws) and 2- Negotiable
changingthe values of individual variables by one unit will allow educators to determine the resultingvalue in intervention efforts. The most valuable variables for developing intervention programswill be those that are directly controllable and have the greatest impact on increasing theestimated probability of a STEM outcome.Bibliography[1] National Science Foundation, Division of Science Resources Statistics, Graduate Students and Postdoctorates inScience and Engineering: Fall 2002, NSF 05-310, Project Officers: Julia D. Oliver and Emilda B. Rivers (Arlington,VA 2004). (available from NSF website http://www.nsf.gov/statistics/nsf04318/ )[2] Commission on Professionals in Science and Technology (CPST), data derived from the American Associationof
, learning-oriented, support-oriented,challenge-oriented, and disruptive. The coding book is included in Attachment B. Table 2 showsa short episode from one of the teams. As seen in this table, both the students who engaged in theaction (action by) and the student towards whom the action was directed (action towards) wererecorded during coding.Table 2. Sample CodingStudent Code Discourse Action Discourse ActionName By Move TowardsA2: Alex I think one of our priorities should be distance A2 IDE from the building when you lower it down. Like having a little hang up away from the
course project. Peer-teachers helpedstudents in groups of four to five to design and present final course projects on energysustainability that modeled a similar project designed as a K-12 outreach activity.Students in the various project groups developed posters, short movies, and presentations.Some conducted interviews with people on campus.The delivery of the ENGR 101 course at our research campus differed from traditionalengineering course offerings in two ways: (a) peer teachers led the recitation activitiesand (b) weekly homework assignments were essays rather than problem solvingassignments. It is not uncommon that many students view engineering practice as simply
, and CEIA, and published in the Journal of Engineering Education, the Journal of Language and Social Psychology, the Journal of Applied Social Psychology, the European Journal of Social Psychology, and the European Review of Social Psychology.Christine B. Masters, Pennsylvania State University Christine B. Masters is an Assistant Professor of Engineering Science and Mechanics at The Pennsylvania State University. She earned a PhD from Penn State in 1992. In addition to raising four children with her husband of 20 years, she has been teaching introductory mechanics courses for more than 10 years, training the department graduate teaching assistants for 7 years, coordinating the
, the value of the vignette is to show that multiple foci could beaddressed concurrently in a change initiative.Str ategies for Cur r icular ChangeA change strategy is an overall plan for how the change will occur. Curricular change strategiesseem to come in two varieties: (i) prototype first, and (ii) full-scale deployment. In the prototypefirst strategy, change agents develop the new curriculum and then offer it to a fraction of thestudents for whom it is ultimately envisioned. There are two sub-varieties of the prototype firststrategy: (a) show that it makes an improvement, and (b) work out the kinks.The purpose of the first sub-variety is to demonstrate that that prototype makes a difference withrespect to the stated goals in order to
educationalexperience than track B or it does not. If it does, the success of the track should be monitoredthrough specific learning outcomes. If it does not, then there is really only one track andstudents’ choices are essentially meaningless. Page 13.1362.6While student learning outcomes are a useful set of requirements by which to define success ofan educational program, they are not easy to measure. Two examples of student learningoutcomes are: 1. Ability to function on multidisciplinary teams (ABET d); 2. Understanding of Professional and Ethical Responsibilities (ABET f)How does one measure these outcomes to determine if the engineering
of learning by instructors. b. encourage interaction between students and the faculty c. encourage reciprocity and cooperation between students d. prepare students for a different type of leaning by the look of the room when they first enter.The first item in this list is the key goal of this room design, a room that was designed from theground up with active and cooperative learning approaches in mind. The next two are directlyfrom the Chickering and Gamson’s “Good Practices in Undergraduate Education” and are relatedto the first. It was hoped that the room would allow this greater engagement by students witheach other, with the instructor and with the material
, Page 13.842.10South Padre Island, Texas, March 28-30, 2007.4. Ames, C. and Ames, R., Research on Motivation in Education, Chapter 1: Wiener, B., Vol 1. Orlando:Academic Press, 1984.5. Malone, T., Towards a Theory of Instrinsically Motivating Instruction. Cognitive Science, 4, 333-369, 1981.6. Norman, D., Twelve Issues for Cognitive Science. Cognitive Science, 4, 1-32, 1980.7. Bransford, J. D., Brown, A. L., and Cocking, R. R. (Eds.), “How People Learn: Brain, Mind, Experience, andSchool, National Research Council, National Academy Press, Washington, D.C., 1999.8. Brophy, S., and Bransford, J., “Design Methods for Instructional Modules in Bioengineering”, Proceedings ofthe 2001 American Society for Engineering Education, 2001.9. Fuentes, A.A
AC 2008-2601: EFFECTIVENESS AND PROFESSIONAL PORTFOLIOS: ACONTENT ANALYSIS OF STUDENTS’ PORTFOLIO ANNOTATIONSJennifer Turns, University of WashingtonKejun Xu, University of WashingtonMatt Eliot, University of Washington Page 13.471.1© American Society for Engineering Education, 2008 Effectiveness and professional portfolios: A content analysis of students’ portfolio annotationsAbstractThe engineering education community is exploring activities that can support the learning fromexperience. One such activity involves having students construct professional portfoliosconsisting of: 1) a professional statement in which the student makes claims about
following category list of gains wereidentified: (a) thinking and working like a scientist, (b) “becoming a scientist,” (c)personal/professional gains, (d) clarification/confirmation of career plans, (e) enhancedcareer/graduate school preparation, and (f) other gains and skills. The findings showed a highlevel of agreement between students (92%) and faculty (90%) that the undergraduate researchexperience was highly beneficial2. Although the work of Seymour and colleagues revealedfindings pertaining to attitudes toward graduate school and research, as well as confidence levelsand other gains in skills, the number of engineering student participants was limited to a smallnumber.Most recently, one of the more extensive studies on assessing the
ofmanagement, and learn the values and mission of the organization1, 18. Van Maanen and Schein2described the socialization process by three domains of (a) learning what to do, (b) learning howto do it, and (c) learning why it is done this way.From the perspective of the learner in a social context, social cognitive theory views learning asa complex process, which is affectively and socially constituted19. This is consistent with recenttheories of learning, which incorporate cognitive, emotional, and social factors into a moreintegrated system of interdependent factors19, 20. For example, Yang20 proposed a theory ofknowledge comprising interactions between technical knowledge (what to do), practicalknowledge (how to do it), and affectual knowledge
instructions thatencouraged students to discuss the implications of the problem and develop approaches toaddress it, rather than immediately develop solutions. After all, practicing engineers mustapproach problems holistically, working as a team to assess data sources, address contextualissues, and communicate with stakeholders before deciding on solutions. “The scenario assignment is not intended to measure a student’s scientific knowledge. Rather, it is a realisticopen-ended task that draws on a student’s critical thinking skills as well as problem formulationand management expertise.”17 See Appendix B for instructions and sample scenarios.The Student DiscussionBefore each of the 45-minute curricular debriefs, a CTLT facilitator informed students
for other activities.The second major objective of the TExT is to provide learning activities to be used in the class-room along with detailed lesson plans describing how to conduct these activities. To the maxi-mum extent possible, this includes providing the resources necessary for conducting the in-classactivity. In cases where the resources cannot be provided, the lesson plan includes a list of all theitems the instructor will need in class along with an indication of those that must be obtainedfrom a source external to the TExT. The key points of this objective are to ensure (a) that eachactivity is well designed as a student learning experience, (b) that implementation of each activ-ity is straightforward and time-efficient and (c) that
being met through student learning and validated through the businessimpacts of training.The research method used ensured that the problems identified could be met through measurableobjectives and provided a framework for evaluating the following questions: a) did theknowledge transfer, b) did the knowledge impact behaviors, and c) did the behaviors impactproductivity and productivity of the product service offerings? This framework includedinstructor and student evaluations of the PLM course. This evidence based approach is a critical Page 13.236.5business component of most industrial training programs.Instructor Led Online Lectures and
mathematics for 3 years. She has worked on diverse projects about learning, including research about discourse, reading, statistics, algebra, and now Statics. Her primary research focus remains improving the quality of mathematics teaching. She can be contacted at kjh262@psu.edu.Christine B. Masters, Pennsylvania State University Christine B. Masters is an Assistant Professor of Engineering Science and Mechanics at The Pennsylvania State University. She earned a PhD from Penn State in 1992. In addition to raising four children with her husband of 20 years, she has been teaching introductory mechanics courses for more than 10 years, training the department graduate teaching assistants for
recording journal of search processes, a guiding toolto understand the architecture of the information gateway (See Appendix B). In an individualconference with a librarian, students received feedback on their overall search process. Thisprocess and its merits were presented in details previously.8TAC of ABET Criteria 2e requires that graduates should demonstrate an ability to functioneffectively on teams. Students are asked to elect roles based on their strengths: ̇ A file manager to organize the virtual files (e.g. minutes, notes, articles, summaries), including the evolving PowerPoint; ̇ A communicator/task manager to contact faculty with issues and problems and to keep the group coordinated and on task; ̇ An editor to focus on producing
engineering students. European Journal of Engineering Education, 25(2), 145-155.4. Seymour, E., & Hewitt, N. M. (1997). Talking about leaving: why undergraduates leave the sciences. Boulder, CO: Westview Press.5. Moller-Wong, C., & Eide, A. (1997). An engineering student retention study. Journal of Engineering Education, 86(1), 7-15.6. Shuman, L. J., Delaney, C., Wolfe, H., & Scalise, A. (1999). Engineering attrition: student characteristics and educational initiatives [Electronic version]. Proceedings of the American Society for Engineering Education Annual Conference.7. Zhang, G., Anderson, T., Ohland, M., Carter, R., & Thorndyke, B. (2002). Identifying factors influencing engineering student graduation and
requirements so students can see how these concepts link together to satisfy the project’s purpose. This helps students realize that the basic task is achievable. b. Labs introduce and develop common practices which will make projects easier to do or will allow students to earn higher grades. For example, labs teach students how to use and modify test code. This builds the skills needed to achieve basic requirements. c. Homework has students practice core concepts or common practices on their own to prepare for the projects. For example, a homework assignment has students learn a new command and write test code for it. This builds
. The FE, for example, tends toconcentrate on engineering subject-area and knowledge acquisition. Less attention is devoted tothe engineering skills students may or may not have developed. Some have argued that FE scoresare appropriate for assessing certain of ABET's EC2000 Criterion 3.a-k outcomes, specifically"Criterion 3: (a) an ability to apply knowledge of mathematics, science, and engineering; (b) anability to design and conduct experiments, as well as to analyze and interpret data; (c) an abilityto design a system, component, or process to meet desired needs; (e) an ability to identify,formulate, and solve engineering problems; (f) an understanding of professional and ethicalresponsibility, and (k) an ability to use the techniques
Engineering Programs,” ABET, Inc.,November 17, 2007, accessed at http://www.abet.org/Linked%20Documents-UPDATE/Criteria%20and%20PP/E001%2008-09%20EAC%20Criteria%2011-30-07.pdf. 2. Miller, R. L. and Olds, B. M., “A Model Curriculum for a Capstone Course in Multidisciplinary EngineeringDesign,” Journal of Engineering Education, October 1994. 3. Whitman, L.E., Malzahn, D. E., Chaparro, B.S., Russell, M., Langrall, R., and Mohler, B.A., 2005, “AComparison of Group Processes, Performance, and Satisfaction in Face-to-Face Versus Computer-MediatedEngineering Student Design Teams,” Journal of Engineering Education, July 2005. 4. McKenzie, L.J., Trevisan, M.S., Davis, D.C., and Beyerlein, S.W., 2004, “Capstone Design Courses andAssessment: A
AC 2008-1113: USING CALIBRATED PEER REVIEW AS A TEACHING TOOLFOR STRUCTURAL TECHNOLOGY IN ARCHITECTUREAnne Nichols, Texas A&M University Dr. Nichols is an Assistant Professor of Architecture at Texas A&M University. She teaches structural analysis, design, and planning at the undergraduate and graduate level. She is a civil engineer with research interests in the structural mechanics and modeling of masonry and cement materials. Page 13.1331.1© American Society for Engineering Education, 2008 Using Calibrated Peer Review as a Teaching Tool for Structural
AC 2008-1348: APPLYING "CULTURAL CONSENSUS ANALYSIS" TO ASUBGROUP OF ENGINEERING EDUCATORSSusan Lord, University of San Diego Susan M. Lord received a B.S. from Cornell University and the M.S. and Ph.D. from Stanford University. She is currently Professor and Coordinator of Electrical Engineering at the University of San Diego. Her teaching and research interests include electronics, optoelectronics, materials science, first year engineering courses, as well as feminist and liberative pedagogies. Dr. Lord served as General Co-Chair of the 2006 Frontiers in Education Conference. She has been awarded an NSF CAREER and ILI grants. She is currently working on a collaborative NSF-funded Gender in
AC 2008-1347: THE FOUR-DOMAIN DEVELOPMENT DIAGRAM: A TOOL FORDESIGNING DEVELOPMENT-CENTERED TEACHINGLinda Vanasupa, California Polytechnic State UniversityTrevor Harding, California Polytechnic State UniversityWilliam Hughes, California Polytechnic State University Page 13.1231.1© American Society for Engineering Education, 2008 The Four-Domain Development Diagram: A tool for designing development-centered teachingAbstractResearch in education has brought to light the complexity of the learning process, demonstratingthat students' development is influenced by a myriad of cultural and social factors, as well as theenvironment in which learning takes
AC 2008-950: WILL I SUCCEED IN ENGINEERING? USINGEXPECTANCY-VALUE THEORY IN A LONGITUDINAL INVESTIGATION OFSTUDENTS’ BELIEFSHolly Matusovich, Purdue UniversityRuth Streveler, Purdue UniversityHeidi Loshbaugh, Colorado School of MinesRonald Miller, Colorado School of MinesBarbara Olds, Colorado School of Mines Page 13.1403.1© American Society for Engineering Education, 2008 Will I Succeed in Engineering? Using Expectancy-Value Theory in a Longitudinal Investigation of Students’ BeliefsAbstractThis multi-case study qualitatively and inductively examines undergraduate engineeringstudents’ expectancies for success as engineers as well as how these
AC 2008-1034: FROM PIE TO APPLES: THE EVOLUTION OF A SURVEYINSTRUMENT TO EXPLORE ENGINEERING STUDENT PATHWAYSHelen Chen, Stanford UniversityKrista Donaldson, Stanford UniversityOzgur Eris, Franklin W. Olin College of EngineeringDebbie Chachra, Franklin W. Olin College of EngineeringGary Lichtenstein, Stanford UniversitySheri Sheppard, Stanford UniversityGeorge Toye, Stanford University Page 13.633.1© American Society for Engineering Education, 2008 From PIE to APPLES: The Evolution of a Survey Instrument to Explore Engineering Student PathwaysAbstractThe Academic Pathways Study (APS) of the Center for the
AC 2008-1926: ALIGNING STUDENT LEARNING, FACULTY DEVELOPMENTAND ENGINEERING CONTENT: A FRAMEWORK FOR STRATEGICPLANNING OF ENGINEERING INSTRUCTION AND ASSESSMENTArunkumar Pennathur, University of Texas-El Paso Arunkumar Pennthur is Associate Professor of Industrial Engineering at UTEP. He teaches work design, senior design and human factors engineering. His research interests are in virtual collaboration and problem representation in engineering education.Louis Everett, University of Texas-El Paso Louis Everett is Professor and Chair of Mechanical Engineering at University of Texas at El Paso. He teaches Dynamics and Controls. His research interests are in metacognition in engineering education