recommended not to use any devices or aids, like calculators,computers, or formula collections which they are not allowed to use during exams. Apart fromthe three interventions: everyday examples, the joint construction of definitions, and motivating Page 26.401.3application examples, the lectures are given in traditional fashion. The examination itself iscentrally designed and administered to all first-year students. The course literature consists of aSwedish book, Analys i en variable, by Persson and B¨oiers and Calculus: A complete course byAdams and Essex.Aim of the studyThe overarching aim of the study is to scaffold engineering students
Above the st Gathering Storm: Energizing and Employing America for a Brighter Economic Future. Washington, D.C., National Academies Press (2005).3. Duderstadt, J. J., Engineering for a Changing World: A Roadmap to the Future of Engineering Practice, Research, and Education. Ann Arbor, Michigan, University of Michigan Press, (2007).4. Bloom, Benjamin S. Taxonomy of Educational Objectives (1956). Published by Allyn and Bacon, Boston, MA. Copyright (c) 1984 by Pearson Education. Page 26.226.195. Bloom, B. S
coagulation-flocculation-sedimentation-filtration experiments (A)and sludge volume observations (B) by the students in the laboratory during a laboratory session.For this experiment, the students were asked to prepare the experimental plan, collect the actualenvironmental samples from two different ponds on the campus, followed by experimental setupand execution. The students were asked to collect the samples from the ponds on the campus.But they were not provided any other information on the water quality or turbidity. This wasdetermined as part of the laboratory experiment. The student experiences and opinions from theevaluation survey are presented below. The students were asked to respond to the followingsimple questions and reflect over their
were designed to capture evidence of institutionalchange using the Pathways team as the primary unit of analysis. Exhibit 5: Evaluation Questions 1. Regarding the teams’ early indicators for potential impact: a. Do teams see the value in Pathways activities for achieving their own goals? b. Do teams value being part of a collaborative group, going through this together? What are the perceived advantages of the group, if any? c. Do teams have clarity around why they are participating, what the opportunity is for them, and what they hope to accomplish? d. Do teams have clarity around the program’s activities and theory of change? e. Do teams have clarity around roles
Gains Attributable to Curricular Innovations Although there is growing use of project-based learning in engineering, less has beendone to formally assess the learning gains actually attributable to these types of approach. Ourwork to date has established that (a) the MILL Model is an innovative curricular reform thatprovides students with hands-on skills highly sought by industry, and (b) we have developed a Page 26.252.6psychometrically reliable and valid standardized assessment instrument to measure studentachievement on the competencies spanned by the MILL Model. The current project brings thesetwo together through a formal summative
undergraduate research.InstrumentsThe admissions survey, which was administered to entering freshman and transfer students at thestart of the years 2011, 2012 and 2013, is contained in Appendix A. This instrument wasdesigned to identify students who participated in the institution’s K-12 outreach activities priorto entering colleges. Students who participated in these activities were further asked to evaluatetheir effectiveness and provide basic demographic information. The graduate survey, which wasadministered to graduating students from the STEM fields in the years 2011, 2012 and 2014, iscontained in Appendix B. Students who completed the graduate survey were asked to identifyoutreach activities that they participated in as undergraduate students at
. • STEM-Scholar (Eng) participated in University of Southern Maine’s Thinking Matters Student Exhibition. • STEM- Scholar (Com Sci) participating in an internship within his field of study and is working part-time 10-15 hours a week.References[1] Enrollment Factbook - Office of Institutional Research; University of Southern Maine. (2014, November 4). Retrieved from: http://usm.maine.edu/sites/default/files/oir/Admissions_Fall_2014.pdf[2] Jameson, M. M., & Fusco, B. R. (2014). Math Anxiety, Math Self-Concept, and Math Self- Efficacy in Adult Learners Compared to Traditional Undergraduate Students. Adult Education Quarterly, 0741713614541461.[3] Kramer
processing and documentation processing. There aretwo types of data processing procedures for qualitative and quantitative data. Depending on thequality of the data and documentation, varying levels of the processing standards are applied.For example, UK Data Archive allocates Standard A*, A, B, and C for quantitative studies 15.Standard A* is applied to data sets that are destined for the archive’s browsing tool. Studiesdeposited by government departments and major research centers are processed with Standard A.Standards B and C are allocated to the studies from academic sources, and studies with materialsin poor condition, respectively.For qualitative data, the same four-level standards are applied with different details. Standard A*is allocated
guidance of the Clemson University Institutional Review Boardstaff. Page 26.878.8 References1. Guo, J., The worst possible way to push kids into studying science, math and engineering. TheWashington Post 2014.2. Spencer, B.; Llewellyn, D.; Usselman, M. In Recruiting engineering students into K-12 teaching,2010 ASEE Annual Conference and Exposition, June 20, 2010 - June 23, 2010, Louisville, KY, Unitedstates, 2010; American Society for Engineering Education: Louisville, KY, United states.3. Panitz, B. ASEE PRISM 1996, 6, (2), 22-22.4. Restructuring Engineering Education: A Focus on Change; National Science Foundation: 1995;pp 1
-Mendívil, E. (2014). How can Augmented Reality favor the learning of Calculus? In H. R. Arabnia, A. Bahrami, L. Deligiannidis, & G. Jandieri (Eds.), Proceedings of the International Conference on Frontiers in Education: Computer Science and Computer Engineering (pp. 443–447). Las Vegas, Nevada, USA: CSREA Press. 3. Carvalho de Alencar, C. V., & Lemos, B. M. (2014). Possibilities of Augmented Reality use in mathematics aiming at a meaningful learning. Creative Education, 5(9), 690–700. 4. Dunleavy, M., Dede, C., & Mitchell, R. (2009). Affordances and limitations of immersive participatory Augmented Reality simulations for teaching and learning. Journal of Science Education and Technology, 18(1), 7
RECEIVING SPECIFIC LETTER GRADES 30% 25%Percent of Class receiving a Specific Letter Grade 20% 15% 10% 5% 0% A BA B CB C DC D E Letter Grade at end of Course Sp 04 F 05 Sp 07 F 09 F10 F11 Figure 1. Grade Frequencies (as Percent of Class) in Selected Semesters4. Fall ’09 (F 09): The format was changed so that time value
valuable. They saw it as an assignment that just needed to becompleted without much thought. Well, in all honesty, our team charter, we didn't take it very seriously. We thought the whole concept, in general, was common sense. So we verbally said we'll write down some stuff we think our teachers wanted to see. I mean, basically we will be reasonable, we will do our work. As a whole that's what we wrote on our team charter. I don't think on our team charter was terribly valuable as a general in [CompE I] as a whole. (Student B) The team charter we wrote down at the beginning and none of us really knew what to put
, – Rubric B processing, sustainability • Presentation Final – (environmental, societal, Rubric C economical, & technical factors) -Ecological audits -Deliver information in written format Final Evaluation (FE) All that was in PE plus the following: -Material testing -Statistical analysis -Design a material test
additional concepts. Page 26.871.8FindingsThe concepts and related problem statement for each dyad was drawn from the engineering orindustrial design course in which they were enrolled, including a wide variety of conceptual andproduct framings (Table 3). Dyad A (Junior, Industrial Design) was focused on creating kitchenproducts for millennials, addressing new kitchen practices surrounding this generation’sinteraction with the foods of the future. Dyad B (Sophomore, Mechanical Engineering) wastasked with “design[ing] a device that meets a basic need in a developing region, whileimproving or creating self-sustaining economic activity.” Dyad C
andethnic minority) engineering students. Table 1 shows the number of students who haveparticipated in the STEP program in CEAS at UC. The gender and demographic distribution ofthe total number of students is as follows: (a) Gender distribution: 147 (69%) men and 71 (31%)female students; and (b) Ethnicity distribution: 108 (70%) ethnic minority, 95 (27%) whiteCaucasians, 8 (2%) Asian American, and 7 (2%) in “other” category. As of the beginning of2014 Spring Semester, a total of 148 students remain in the STEP program and theirdemographics is shown in Table 2 and the total number is broken down as follows: (a) Genderdistribution: 99 (67%) men and 49 (33%) female students; and (b) Ethnicity distribution: 72(49%) ethnic minority, 60 (41%) white
. Reliability Engineering and System Safety, 96(6), 679-686. doi:10.1016/j.ress.2010.12.010.7. Walther, J., Kellam, N., Gattie, D., & Schramski, J. (2011). Engineering education as a complex system. European Journal of Engineering Education, 36(6), 521-535. doi:10.1080/03043797.2011.6220388. Steinlicht, C., & Garry, B. (2013). Systems Learning Within the Context of Subject Learning. American Society for Engineering Education, 2013 120th ASEE Annual Conference & Exposition, Atlanta. Retrieved December 20, 2014, from http://www.asee.org/public/conferences/20/papers9. Frank, M. (2012). Engineering systems thinking: Cognitive competencies of successful systems engineers. Procedia Computer Science, 8, 273-278. doi:10.1016
Productivity Paradox of Information Technology', Communications of the ACM, 36 (1993), 66-77.6 Colin Potts, 'Software-Engineering Research Revisited', Software, IEEE, 10 (1993), 19-28.7 Walt Scacchi, 'Managing Software Engineering Projects: A Social Analysis', Software Engineering, IEEE Transactions on (1984), 49-59.8 Walt Scacchi, and D Hurley, 'Understanding Software Productivity', Software Engineering and Knowledge Engineering: Trends for the Next Decade, 4 (1995), 273-316.9 Viljan Mahnic, 'A Capstone Course on Agile Software Development Using Scrum', Education, IEEE Transactions on, 55 (2012), 99-106.10 B Lakhanpal, 'Understanding the Factors Influencing the Performance of Software Development Groups
., Drnevich, V., Irfanoglu, A., and Bullock, D. (2012). Summary of developments in the civil engineeringcapstone course at Purdue University. Journal of Professional Issues in Engineering Education & Practice, 12(1), pp95-98.Dougherty, J., and Parfitt, M. (2013). Student and practitioner collaboration in an online knowledge community:Best practices from a capstone course implementation. Journal of Architectural Engineering, 19(1), pp 12-20.Ford, G. and Ball, A., (2011). The evolution of engineering and engineering technology educational programs in theUnited States. Conference proceedings of the American Society of Engineering Educators. Vancouver, BC,Canada .Ford, G., Kinard, C., and Sims, B. (2012). Measuring educational program effectiveness
will need to move beyond the 3D modeling aspects andintegrate to a greater extent the information laden aspect of BIM. While currently the BIMcourse covers all topics related to the information laden aspect of the model, this will need to bedriven home in a more forceful manner to the students through smaller projects where studentsare expected to build a model which will contain information that can be used not just during thedesign and drawing generation phase of the project but can move into the construction phase andbeyond, making complex architectural projects easier to manage through the entire cycle ofdesign, construction and facilities management.References[1] B. Johnson, "Design Ideation: The Conceptual Sketch in the Digital Age
mellifluously,” New YorkTimes, April 22, 2012.[2] Fox, Armando; Canny, John, “Autograding and online ed technology,”https://docs.google.com/document/d/11e7HzGGRAvAhTce6L7P33fyQUo67wO_Qbec6cGynrKo/edit#heading=h.vo90ekim8uj0, accessed Feb. 2, 2015[3] Beitzel, B. D.; Gonyea, N. E., “The rubric interview: a technique for improving the reliabilityof scoring written products,” Proc. 2014 Virginia Tech Conference on Higher EducationPedagogy, p. 242.[4] Edwards, S.H; Perez-Quiñones, M.A., “Web-CAT: automatically grading programmingassignments.” In Proceedings of the 13th annual conference on Innovation and technology incomputer science education (ITiCSE '08). ACM, New York, NY, USA, 328-328, 2008.DOI=10.1145/1384271.1384371 http
ishighly recommended. Appendix B shows the topics covered in a ten-week course. Appendix Cpresents all student ratings with two-sigma outlier data shown in red. Figure 7 Conclusions from Student Surveys (See Appendix A for Details). Page 26.684.15 NOTE: (C7 and C8 Are Based on Post-Presentation Responses Only) Summary of Student Feedback and Resolve A positive student recommendation was noted26 by the associate dean of the engineeringcollege in his preparation for a successful ABET visit during the spring 2014 quarter. Studentsgiving positive feedback, I believe, have been motivated towards valuing conscience awarenessin the
Paper ID #11113Discussions of Engineering Education Learning Advances among WorkingEngineering FacultyProf. Byron G. Garry, South Dakota State University BYRON GARRY is an Associate Professor and Undergraduate Program Coordinator in the Department of Construction & Operations Management in the College of Engineering at South Dakota State University. He has been a member of ASEE since 1998. As SDSU ASEE Campus Rep., his goal is to help fellow College of Engineering faculty to be reflective teachers.Dr. Suzette R Burckhard, South Dakota State University Dr. Burckhard earned a BS in Engineering Physics, a BS in Civil
protocol studies in design andother disciplines and related research in cognitive psychology. Design Studies, 19(4), 389-430.7. Dorst, K. (2004). On the Problem of Design Problems – Problem Solving and Design Expertise. Journal ofDesign Research, 4(2).8. Welch, M. (1999). Analyzing the Tacit Strategies of Novice Designers. Research in Science & TechnologicalEducation, 17(1), 19-34.9. MacDonald, D., & Gustafson, B. (2004). The role of design drawing among children en- gaged in a parachutebuilding activity. Journal of Technology Education 16(1), 55-71.10. McCormick, R., Murphy, P., & Hennessy, S. (1994). Problem-Solving Processes in Technology Education: APilot Study. International Journal of Technology and Design Education, 4(1), 5
Paper ID #13876Not engineering to help but learning to (un)learn: Integrating research andteaching on epistemologies of technology design at the marginsDr. Prashant Rajan, Iowa State University Prashant Rajan is an Adjunct Assistant Professor in the Department of English and the Communication Studies Program at Iowa State University. He has a B. Eng. in polymer engineering from Pune University, an M.S. in materials science and engineering from the University of Cinainnati, and a Ph.D.in Organiza- tional Communication with Ph. D. minors in research methods and critical-cultural theories from Purdue University. He is
throughout the community. The design report provided to EWB was submitted to the local government and EWB-USA, as well as various other sponsors for funding purposes. The team has also been invited to join EWB-PPC on their implementation trip to Ecuador next year to help construct the system. B. La Paz Community – Panama The second team took on the project of installing a water system in the community of La Paz in Panama. This project was an extension to the previous projects for the Kuna Nega community. The Kuna Nega community is supplied water by a pressure main running from Panama City. Every week, this pressure main is shut off for up to 36 hours, and the community is supplied water solely by an existing 10,000 gallon storage
what I was doing, I know how to do this, I have taking calculus before, I just got nervous and I ended up getting a B+ in that class, which is huge [G1].This student addressed that her level of competence prior to arriving to college was at a 4.0,signifying that her motivation was not to perform better, but rather to avoid under-performing.Prior research has also shown that that students who assume the mastery avoidance goal haveachieved success in the past, which clearly illustrated in this student’s narrative41. Uncertaintyfor this participant was a threatening factor towards her goal, as she stated, “you don't know whatthe future holds for you or the job, you don't know if you’re going to like . . . you
: Balanced designs for deeper learning in an online computer science course for middle school students. 2014, Stanford University.[6] Lahtinen, E., K. Ala-Mutka, and H.-M. Järvinen. A study of the difficulties of novice programmers. in ACM SIGCSE Bulletin. 2005. ACM.[7] Streveler, R.A., et al., Learning conceptual knowledge in the engineering sciences: Overview and future research directions. Journal of Engineering Education, 2008. 97(3): p. 279-294.[8] Barney, B., Introduction to parallel computing. Lawrence Livermore National Laboratory, 2010. 6(13): p. 10.[9] Nevison, C.H., Parallel Computing for Undergraduates. National Science Foundation and Colgate
phases.Future ImplicationsThis study shows results from a part for our research project. The instrument is being applied infive partner institutions to identify possible differences in perceptions in different types ofuniversities. We are aiming to identify relationships between the dimensions of culture and a)student choice of major, and b) student success within a major. In addition, we are conducting alongitudinal study to understand whether students’ perceptions about their academic programschange over time and under which circumstances, leading, to an actionable theory of engineering Page 26.369.12culture that can support pedagogies of inclusive
students appear in our dataset at a higher rate than their prevalence in theengineering population.Students served, parsed by academic major. Student demographics by major are shown in Table1, and it is clear that a few majors are over-represented in our dataset as compared to engineeringundergraduate population as a whole. We list the majors as Major A, B, C,… to protect theidentity of the faculty and staff within those majors. In particular, Major A students appear in ourdataset about 30% more than their prevalence in the overall population, and Major E students ata rate nearly double their representation in the overall population. It is not clear why Major Astudents would be over-represented in our dataset. However, Major E tends to attract
role of emotion in student learning, and synergistic learning. A recent research project uncovers the narratives of exemplar engineering faculty that have successfully transitioned to student-centered teaching strategies. She co-designed the environmental engineering synthesis and design studios and the design spine for the mechanical engineering program at UGA. She is engaged in mentoring early career faculty at her univer- sity and within the PEER National Collaborative. In 2013 she was selected to be a National Academy of Engineering Frontiers of Engineering Education Faculty Member.Karen Sweeney Gerow, University of Georgia Karen Sweeney Gerow is pursuing her PhD in the Lamar Dodd School of Art at the University