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Jack L. Beuth, Carnegie Mellon University; Rohit Kumar, Carnegie Mellon University; Carolyn Penstein Rose, Carnegie Mellon University

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thismodel, it is possible to determine where the most strategic opportunities for supporting learningexist. Figure 1 shows an overview of the architecture used to develop our prototype Page 22.1597.3infrastructure. This architecture is meant to allow context-sensitive support for collaborativelearning and reflection not only to be triggered based on what is happening in the discussion, butfor it to do so with awareness of how it is affecting the state of the conversation through itscontinuous monitoring. Thus, if an intervention is triggered erroneously and ends up having anegative effect on the collaboration, we can detect and correct that. In this

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2011 ASEE Annual Conference & Exposition

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Ying Tang, Rowan University; Sachin Shetty, Tennessee State University; Xiufang Chen, Rowan University

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required by different learning circumstances are increasingly recognized ascritical for successful learners. Such awareness and monitoring processes are often refer to asmetacognition –“ the processes in which the individual carefully considers thoughts in problemsolving situations through the strategies of self-planning, self-monitoring, self-regulating, self-questioning, self-reflecting, and or self-reviewing” [1]. The contention of this research is thatmetacognitive awareness on the part of students can be improved through systematic and directinstructions on strategic thinking. To support that, three important metacognitive interventions,as detailed below, are carefully designed into the interactive game activities.• Road Map training

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2011 ASEE Annual Conference & Exposition

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Sheng-Jen Hsieh, Texas A&M University; Punit Deotale, Texas A&M University

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supported by the National Science Foundation’s Course Curriculum andLaboratory Improvement (CCLI) Program (Award Number 0837634). Any opinions, findings,and conclusions or recommendations expressed in this material are those of the author and do notnecessarily reflect the views of the National Science Foundation.Bibliography1. Online resource available at: http://www.census.gov/foreign-trade/statistics/product/atp/2006/12/atpctry/atpg06.html (last accessed on January 18, 2011)2. Online resource available at: http://www.census.gov/foreign-trade/statistics/product/atp/2008/03/atpctry/atpg06.html (last accessed on January 18, 2011)3. Hsieh, S. and Hsieh, P.Y. “Web-based Modules for Programmable Logic Controller Education

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R. Roemer, University of Utah; Debra J. Mascaro, University of Utah; Eric R. Pardyjak, University of Utah; Stacy Bamberg, University of Utah

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,thermal power sources are emphasized as sustainable energy solutions and highlighted inlecture and laboratory experiences.A team-based design project reflects the sustainable energy theme. During the firstteaching of this course sequence we concentrated on energy storage in compressed air,which is used to propel an air-powered train in an end-of-year design competition. Theproject spirals the design methodology, communication, teamwork, programming,manufacturing and hardware skills acquired during the first year of our new curriculum.For example, students are introduced to the following new manufacturing tools andtechniques: CNC mill, CNC lathe, CNC router, vacuum forming and injection molding.The students continue to use Arduino

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2011 ASEE Annual Conference & Exposition

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Claudio Olmi, University of Houston; Bo Cao, Smart Materials and Structures Laboratory; Han Wang, University of Houston; Xuemin Chen, Texas Southern University; Gangbing Song, University of Houston

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computer and with no specific requirements. Anyone with anInternet connection and access to a web browser can interact with and control a remoteexperiment from anywhere. Users and experiment developers no longer have to worry aboutversion problems or updates, since all the interfaces do not use proprietary technologies.Acknowledgement and DisclaimerThis work is partially supported by the National Science Foundation under Grant Numbers EEC-0935208, EEC-0935008.Any opinions, findings, and conclusions or recommendations expressed in this material are thoseof the author(s) and do not necessarily reflect the views of the National Science Foundation.Bibliography1. Ambrose, S. A., & Amon , C. H. (1997). Systematic design of a first-year mechanical

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Sydney Rogers, Alignment Nashville; Sandra Harris, Alignment Nashville and PENCIL Foundation; Ismail Fidan, Tennessee Technological University; David McNeel, Education Consultant

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careers in science and engineering in the spring and summer relative to fall.Thus, interest in studying these subjects in college may correlate with increased understanding ofSTEM careers.The DAET results suggest that girls more easily and accurately described what engineers do inwriting than in their drawings. In the larger core student sample, girls’ written descriptionsshowed positive changes over time, specifically including fewer references to fixing or makingthings. In contrast, the girls’ drawings in spring 2010 tended to more often reflect concepts offixing relative to their fall 2009 drawings. In contrast, the sample of campers demonstrated ashift between spring and summer. Girls drew significantly fewer engineers fixing and

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2011 ASEE Annual Conference & Exposition

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Yongpeng Zhang, Prairie View A&M University; Lin Li, Prairie View A&M University; Xuemin Chen, Texas Southern University

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, #0942778. Any opinions, findings, and 6conclusions or recommendations expressed in this material are those of the authors and do notnecessarily reflect the views of the National Science Foundation.Bibliography [1] http://www.coe.neu.edu/Depts/SET/set/whatisset.html [2] A. Selmer, M. Kraft, R. Moros, C.K. Colton, “Weblabs in Chemical Engineering Education”, Trans IChemE, Part D, Education for Chemical Engineerings, Vol. 2, pp. 38-45, 2007. [3] Sloan Consortium of Institution and Organizations Committed to Quality Online Education, “Staying the Course: Online Education in the United States, 2008”. http://www.sloan-c.org/publications

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Xuemin Chen, Texas Southern University; Lawrence O Kehinde P.E., Texas Southern University; Yuhong Zhang, Texas Southern University; Shahryar Darayan, Texas Southern University; David O. Olowokere, Texas Southern University; Daniel Osakue, Texas Southern University

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iLab, and felt the lab had made themthink about and understand some things they would not have been able to from just lectures ortextbooks. This activity successfully helped us to understand the requirement for the VR-Lab.Acknowledgement and DisclaimerThis work is partially supported by the National Science Foundation under Grant Numbers DUE-0942778, EEC-0935008, and HRD-0928921.Any opinions, findings, and conclusions or recommendations expressed in this material are thoseof the author(s) and do not necessarily reflect the views of the National Science Foundation.Bibliography 1. I. E. Allen and J. Seaman, “Learning on demand: Online education in the United States, 2009”. Technical report, The Sloan Consortium. Retrieved May 1, 2010

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Morgan M Hynes, Tufts University; Ann F. McKenna, Arizona State University, Polytechnic; Chris Rogers, Tufts University; Megan Kiely Mueller, Tufts University; Xaver Neumeyer, Northwestern University; Richard M. Lerner, Tufts University

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,” “O,” and “C” have beenidentified in human development research to constitute the motivational and decision making(executive) skills requisite not only for science, technology, engineering, and math (STEM)attainment but, as well, for succeeding in life more generally, e.g., for protecting against schoolfailure and drop out and for promoting healthy life styles and success in interpersonalrelationships, including peer relationships, student-teacher relationships, family relationships,and civic engagement and community contributions9,12,13. Indeed, the “soft skills” indexed bySOC reflect both practical (planning, coordination) and analytical (problem solving) abilitiesand, in the case of compensation (and the loss-based selections) a component

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2011 ASEE Annual Conference & Exposition

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Lawretta C. Ononye, State University of New York, Canton

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, findings, and conclusions or recommendations expressed herein arethose of the author(s) and do not necessarily reflect the views of the National ScienceFoundation.Bibliography:[1] National Science Board. (2004). Science and engineering indicators: 2004. Arlington, VA: National ScienceFoundation.[2] National Science Foundation. (2007). It’s Elemental: Enhancing Career Success for Women in the ChemicalIndustry: 2007. Arlington, VA: National Science Foundation.[3] http://codes.lp.findlaw.com/uscode/20/28/III/E/1/1067[4] Seymour, E., & Hewitt, N. (1997). Talking About Leaving: Why Undergraduates Leave the Sciences.Boulder,CO: Westview Press.[5] The State of “Learning” in New York: An annual snapshot with comparisons of Select Counties around the

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2011 ASEE Annual Conference & Exposition

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Katie Grantham, Missouri University of Science & Technology; Ryan Arlitt, Missouri University of Science and Technology

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. Usabilityaspects that received lower mean scores may reflect lower levels of satisfaction with thataspect of the usability. Based on these mean scores for each response, the survey suggeststhe following order of importance for usability improvements: provide feedback, providehelp and guidance within the application, improve navigation, improve error recovery,and improve accessibility. Page 22.652.18 Table 6.1. RED Usability Survey Results StandardRank Question Mode Mean Deviation

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Thomas A. Litzinger, Pennsylvania State University, University Park; Sarah E. Zappe, Pennsylvania State University, University Park; Maura J. Borrego, Virginia Tech; Jefferey E. Froyd, Texas A&M University; Wendy Newstetter, Georgia Institute of Technology; Karen L. Tonso, Wayne State University; Peggy Noel Van Meter, Pennsylvania State University

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Foundation under GrantDUE-0939823. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation.References1 Pimmel, Russ and Sheryl Sorby, “Writing Proposals to Meet NSF’s Expectations,” Workshop at 2008 ASEE Annual Meeting, Pittsburgh, PA, June 22, 2008.2 Olds, Bar: Evolution, Approaches, and Future Collaborations, Journal of Engineering Education, Vol. 94,No. 1, pp. 13-25 (2005)3 National Research Council, Committee on Scientific Principles for Education Research, Scientific Research in Education, Richard Shevelson and Lisa Towne, Editors, National Academy Press, Washington, DC (2002)4 National Research Council

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Kirsten A. Davis, Boise State University; Sondra M Miller, Boise State University; Ross A. Perkins, Boise State University

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change and willinclude metrics such as the Change Scale14, the Reaction-to-Change Inventory15, and theIrrational Belief Scale16. The Change Scale indicates that “individual differences in attitudestoward change may reflect differences in the capacity to adjust to change situations”14. TheReaction-to-Change Inventory measures an individual’s perceptions about change15. TheIrrational Belief Scale measures an individual’s irrational ideas about change and theirinterpretations of how the change will occur16. These questions will enable us to evaluate thewillingness a faculty member exhibits to use a new innovation. There will be additional sets ofquestions allowing individuals to self-evaluate their knowledge about pedagogy, engineeringeducation

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2011 ASEE Annual Conference & Exposition

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Zhigang Shen, University of Nebraska-Lincoln; Yimin Zhu, Florida International University

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participating classes.Research Question: The proposed environment may lead to conceptual change from a static,structure-oriented perspective of complex spatial and temporal phenomena to a more dynamicand function/behavior-oriented perspective. It is always a question as to how effectively theproposed environment can realize comparable results with traditional case-based learning orproblem based learning. Such results should be reflected by observable facts, including: 1) anenriched understanding of complex phenomena and 2) an improved capability to explaincomplex phenomena and solve complex problems. This research will focus on the followinghypotheses.Hypothesis 1-A: Since students using the proposed environment, an experimental group, willexperience

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2011 ASEE Annual Conference & Exposition

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Lisa Schneider, Cornell University; Maria Terrell, Cornell University

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and ability to apply concepts to new problem situations is by no means unique toour institution. Many schools face it, and some new understanding of why this is happening, andsome evaluation of whether a particular intervention improves things, will have wideimplications nationally.In 2006 the Dean of the Engineering College at our institution formed a Curriculum Task Force.The task force was charged with developing recommendations for changes in the college’s corecurriculum that would reflect and implement the Undergraduate Studies Objectives of thecollege:  Enhance the undergraduate educational environment and experience.  Enhance the engineering undergraduate curriculum and implement procedures for assessment and change

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2011 ASEE Annual Conference & Exposition

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Gwen Lee-Thomas, Ph.D., Old Dominion University; Autar Kaw, University of South Florida; Ali Yalcin, University of South Florida

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Inventory (LCI) developed by [8]. The LCI is divided intotwo parts and includes 28 questions in part one that allows the respondent to rate their preferencefor learning patterns. These learning patterns are reflected in the literature regarding obtaining,retaining, and retrieving learned information. The response options are presented on a 5-pointLikert scale of: “Never Ever = 1,” “Almost Never = 2,” Page 22.1626.4 “Sometimes = 3,” “Almost Always = 4,” and “Always = 5.”Part II of the LCI includes three (3) open-ended questions that allow respondents to write—intheir own words—their thoughts regarding their

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Mukasa E. Ssemakula, Wayne State University; Celestine Chukwuemeka Aguwa, Wayne State University; Darin Ellis, Wayne State University; Kyoung-Yun Kim, Wayne State University; Gene Liao, Wayne State University; Shlomo S. Sawilowsky, Wayne State University

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Foundation CCLIProgram under grant number DUE-0817391. Any opinions, findings, and/or recommendations inthe paper are those of the authors and do not necessarily reflect the views of the sponsors.6 References [1] SME Education Foundation. 2011. http://www.smeef.org/about/index.html [2] DeMeter, Edward C., Jorgensen, Jens E. and Rullan, Augustine. 1996. "The Learning Factory of The Manufacturing Engineering Education Program." Proceedings, SME International Conference on Manufacturing Education for the 21st Century, San Diego, CA. [3] Lamancusa, John S.; Jorgensen, Jens E.; Zayas-Castro, Jose L.; and Ratner. Julie. 1995. "The Learning Factory - A New Approach to Integrating Design and Manufacturing into Engineering

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Shane F. Cotter, Union College

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category where our categorization largely follows the original paper4 although we haveupdated the categories to reflect the questions given on the newest version 5.0 of the DT-SSCItest. Category # Questions Mathematical Background (B) 5 Linearity and Time Invariance (LTI) 4 Convolution (C) 3 Transform Representations (T) 5 Filtering (F) 2 Sampling (S) 2 Pole Zero Plots

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Lisa Benson, Clemson University; Sarah Jane Grigg, Clemson University; David R. Bowman, Clemson University; Michelle Cook, Clemson University; Roy P. Pargas, Clemson University / U.S .Air Force Academy

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reflect on their problem-solving strategies post-hoc. All students intwo sections of the course used MuseInk® to complete work in class on tablet computers, and aselected subset of students were invited to complete post-hoc audio commentaries within 24hours of completing the problems. Students were purposefully selected to represent a diversecross-section of gender, race and academic preparation. The Ink for this subset of students wascoded by three members of the research team. Inter-rater reliability was assessed continuouslythroughout the project by comparing codes for all three coders and calculating the frequency andpercentages of inter-rater agreement for every code used.Results and DiscussionTo date, worked solutions and audio commentary

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Matthew W. Roberts, University of Wisconsin, Platteville; Philip J. Parker, University of Wisconsin, Platteville; Michael K. Thompson, University of Wisconsin, Platteville; Barb A. Barnet, Univeristy of Wisconsin - Platteville

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reflect the views of the National ScienceFoundation.References1. Smith, Karl A and Imbrie, P K. Teamwork and Project Management. Boston : McGraw Hill, 2004.2. Ohland, Matthew W., et al. Developing a Peer Evaluation Instrument that is Simple, Reliable, and Valid.Proceedings of the 2005 ASEE Annual Conference. 2005. CD ROM.3. American Society of Civil Engineers. Home. Report Card for America's Infrastructure. [Online] 2009.http://www.infrastructurereportcard.org/.4. National Research Council. How People Learn: Brain, Mind, Experience, and School. Washington DC :National Academy Press, 2000. Page 22.488.8

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2011 ASEE Annual Conference & Exposition

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Donald Plumlee, Boise State University

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attitude that reflects a “Need for Cognition” or awillingness to put forth cognitive effort. It is typically assumed that a project-based curriculumin engineering education promotes these characteristics and encourages higher level-learning. Infact, for project-based learning to be widely adopted, there must be a willingness within thestudent body to modify their traditional role within the curriculum.Anecdotal evidence suggests that attitudes towards higher level learning vary among engineeringstudents. Many engineering students appear to be more comfortable in rigid structured learningenvironments, while some students seem to prefer more creative expression. Improving eachstudent’s comfort with the “Ill-Structured” problems faced in professional

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2011 ASEE Annual Conference & Exposition

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Yi Guo, Stevens Institute of Technology; Shubo Zhang, Stevens Institute of Technology; Hong Man, Stevens Institute of Technology; Arthur B. Ritter, Stevens Institute of Technology

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engineering courses, and pilot testing.AcknowledgmentPartial support for this work was provided by the National Science Foundation's Course,Curriculum, and Laboratory Improvement (CCLI) program under Award No. 0837584. Anyopinions, findings, and conclusions or recommendations expressed in this material are thoseof the authors and do not necessarily reflect the views of the National Science Foundation.Bibliography1. What is "Sayaka", the next generation capsule endoscope? http://www.rfamerica.com/sayaka/index.html, August 2010.2. Colonoscopy. http://en.wikipedia.org/wiki/Colonoscopy, August 2010.3. The SmartPill Wireless Motility Capsule. http://www.smartpillcorp.com/index.cfm? pagepath = Products /The_SmartPill_Capsule&id=17814

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Authors

John J. Duffy, University of Massachusetts, Lowell; Linda Barrington, University of Massachusetts, Lowell; Manuel A Heredia, University of Massachusetts, Lowell

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-0920574). Thanks to all thefaculty members in engineering and other colleges who have tried service-learning in theircourses as part of this program. Any opinions, findings, and conclusions or recommendationsexpressed in this material are those of the author(s) and do not necessarily reflect the views ofthe National Science Foundation.ReferencesABA. (2011). Model code of ethics. Retrieved 2011 9-January from http://www.asce.org/Content.aspx?id=8484ASCE. (2011). Policy statement. Retrieved 2011 19-January from http://www.asce.org/Content.aspx?id=8484Bringle, R., & Hatcher, J. (1995). A service-learning curriculum for faculty. Michigan Journal of CommunityService Learning , 2, 112-122.DeAngelo, L., Hurtado, S., Pryor, J. H., Kelly, K. R., &

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Matthew W. Ohland, Purdue University, West Lafayette; Richard A. Layton, Rose-Hulman Institute of Technology; Daniel Michael Ferguson, Purdue University, West Lafayette; Misty L. Loughry, Georgia Southern University; David J. Woehr, University of Tennessee; Hal R. Pomeranz, Deer Run Associates

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in hierarchical fashion: research informs faculty practice, facultydetermine the students’ experience, which, if well managed based on research findings, shouldequip students to work in teams. People. People are the groups that will use the proposed system: students, faculty, andresearchers. The hierarchy of people reflects the hierarchy of goals: the work of the research Page 22.1303.3team supports the work of faculty, which in turn supports the work of students and their teams. GOALS OUTCOMES PEOPLE STRATEGIES

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John Krupczak, Hope College; Kate A Disney, Mission College

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under development.DiscussionInitial tests of the portable laboratories show encouraging results. The students completing theprojects demonstrated an increase in content knowledge in areas related to the project materials.Content knowledge increases are significant. The content knowledge average rose from a poorto a fair level of comprehension. The students themselves rate the projects as interesting andeducationally useful. The students are learning and enjoying the process.AcknowledgementThis work was supported by the National Science Foundation under award: DUE-xxx. Anyopinions, findings, and conclusions or recommendations expressed in this material are those ofthe authors and do not necessarily reflect the views of the National Science

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2011 ASEE Annual Conference & Exposition

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Pratibha Varma-Nelson, Indiana University Purdue University Indianapolis; Stephen Hundley, Indiana University Purdue University Indianapolis; Terri Tarr, Indiana University Purdue University Indianapolis

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the university.The teaching portfolio was noted as an appropriate vehicle to document, reflect, and organizeteaching-related activities of faculty. Items in such a portfolio would include: teaching Page 22.1498.8philosophy that is informed by the scholarship of the field; student accomplishments; studentevaluations; documentation of new things tried in the classroom; peer observation programdocumentation; and a description of service on policy committees regarding teaching andlearning.Recommendations and Implications for Policy, Practice, and Future ResearchThere are several recommendations and implications for policy, practice, and future

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Ashley Ater Kranov, Washington State University; Mo Zhang, Washington State University; Steven W. Beyerlein, University of Idaho, Moscow; Jay McCormack, University of Idaho; Patrick D. Pedrow, Washington State University; Edwin R. Schmeckpeper, Norwich University

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professional engineering environment.This is critical, given the nature of the instrument, as we posit that high scores on the EPS Rubricwill suggest high performance in engineering professional skills in the workplace.Table 9. Questions to Examine Validity Evidence (adapted from Moskal & Leyden25) Content Construct Criterion • Do the scoring rubric’s • Are all of the • How do the scoring rubric’s criteria criteria address any important facets of reflect competencies that suggest extraneous content? the intended construct success on related or future • Do the scoring rubric’s evaluated through the performances

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2011 ASEE Annual Conference & Exposition

Authors

Kathleen L. Kitto, Western Washington University; Debra S. Jusak, Western Washington University

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materials in the data set are: steels (8), cast irons (2), stainless steels (6), aluminums (5),coppers (3), titanium (1), nickels (4), magnesiums (2), special/precious alloys (5), thermoplasticsand thermosets (15), ceramics/glasses (6), and composites (6), for a current total of 63 with moreadded as properties are documented. Currently, 110 conceptually grouped materials to choosefrom are planned. The visual students should display the information graphically while activelearners will want to “try it out” by choosing different materials to compare or to see howplotting one material property versus another will change the way they examine the data. Verballearners will be able to describe the results of their explorations. Reflective learners will

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2011 ASEE Annual Conference & Exposition

Authors

Jianyu Dong, California State University, Los Angeles; Huiping Guo, California State University, Los Angeles

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problems and get them prepared for the design ofnew network components or system. Since our work is still on the early stage, the paper onlypresents very preliminary assessment results at this point. In the future, more comprehensiveassessment data will be collected and analyzed, and the findings will be used to further improvethe course redesign.AcknowledgmentThis material is based upon work supported by the National Science Foundation under Grant No.0941839. Any opinions, findings and conclusions or recommendations expressed in this materialare those of the author(s) and do not necessarily reflect the views of the National ScienceFoundation (NSF).References[1] The network simulator NS-2, http://www.isi.edu/nsnam/ns/[2] Opnet Network Simulator

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2011 ASEE Annual Conference & Exposition

Authors

Geoffrey L. Herman, University of Illinois, Urbana-Champaign; Michael C. Loui, University of Illinois, Urbana-Champaign

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grants DUE-0618589.The opinions, findings, and conclusions do not necessarily reflect the views of the NationalScience Foundation or the University of Illinois at Urbana-Champaign.References[1] Almstrum, V. L., Henderson, P. B., Harvey, V., Heeren, C., Marion, W., Riedesel, C., Soh, L.-K. & Tew, A. E. (2006). Concept inventories in computer science for the topic discrete mathematics. ITiCSE '06: Proceedings of the 11th Annual SIGCSE Conference on Innovation and Technology in Computer Science Education, ACM press, 163-167.[2] Allen, K. (2006). The Statistics Concept Inventory: Development and analysis of a cognitive assessment instrument in statistics. Doctoral Dissertation, The University of Oklahoma.[3] Allen, M. J. & Yen, W