-minute datawould not be included in the answers input into the system. However, as can be seen in this case,after comparing video-tapes to answers input, it does appear that essentially all relevant studentdesign process data has been included in the student answers, such as assumptions, heuristics,etc.As with the alpha-test, the students that completed the work in the pilot study supplied a richdescription of their design process thinking about the problems presented. An example of astudent team response to the first interactive question (see Appendix B) was: “First, we defined the problem using the present state/desired state heuristic. See figure 1 on page one for this work. Next we formulated assumptions, that an equal
feasibleconcepts for the software application to be developed. Each team would then submit a writtenproposal to their client for approval. The proposals were evaluated using the “Client: ProposalEvaluation Rubric.” Appendix B provides an example use of this rubric, containing the feedbackprovided to one of the programming teams. This rubric was used formatively, with teams notpermitted to go forth into the code development phase until they satisfactorily addressed alldesign-oriented shortcomings via submission of a revised proposal, which was also evaluated viaapplication of the Proposal Evaluation Rubric.For purposes of implementing a critical design review process, teams presented their applicationsin a science fair exhibition-type format, illustrated
. The meeting times for the two courses overlapped for 75 minutes a week enabling theFigure 1: (a-b) Collaborative sessions between undergraduate students and preservice teachers held atthe campus with Sphero robots (a) and LEGO WeDo Kits (b). (c) Example of an animal-inspired robotbuilt by students using LEGO WeDo kit. (d-f) Collaborative sessions between fifth/sixth graders,preservice teachers, and engineering students at an after-school technology club using spheros (d),LEGO WeDo kits (e), and coding/robot building activities (f). (g-k) Examples of animal-inspired robotsbuilt by students: Bat (g), Duck (h), Tiger (i), Turtle (j), and Penguin (k).engineering and education students to work collaboratively during several class sessions
from each sub-area ofelectrical engineering to represent conceptual knowledge that (a) all students should knowwithout review, and (b) represent fundamental concepts that are taught to all students in theprogram. Thus the inventory measures how well student understand the concepts underlyingelectrical engineering.To determine how ratings on different sections of the peer evaluation compared with each otherand with scores on the other measures of engineering design correlation coefficients werecalculated. The level of significance was set to p < 0.05. Due to the relatively small sample sizethe data was also analyzed for correlations with p < 0.1. While such correlations are reported,they are identified in the paper and not considered
the Future of Online Education: Understanding its Historical Evolution,Implications, and Assumptions, Online Journal of Distance Learning Administration, 10(2).[2] Marsh II, G. Ed.D, McFadden, A. PhD, Jo Price, B. Ed.D (1999). An Overview of Online Educational DeliveryApplications, Online Journal of Distance Learning Administration, 2(3).[3] Smathers, G. (1946-1967), Libraries History: Resurgence and Growth, (December 2007)http://www.uflib.ufl.edu/msl/LibHist1946-1967.html[4] Morse, L. (2007). Distance Education Tools for Engineering, International Conf. on Eng. Education (ICEE). Page 13.973.14
Paper ID #12769Making Value for Faculty: Learning Communities in Engineering FacultyDevelopmentDr. Stephanie Pulford, University of Washington Center for Engineering Learning & Teaching (CELT) Dr. Stephanie Pulford is an instructional consultant within University of Washington’s Center for Engi- neering Teaching & Learning, where she coordinates the Engineering Writing & Communication Devel- opment Program. Dr. Pulford’s professional background in engineering includes a Ph.D. in Mechanical Engineering, an M.S. in Engineering Mechanics, and a B.S. in Aerospace Engineering as well as industry experience as an
reduction in the designer’s information awareness throughout the design process: As design requires integration of information in various formats from different sources at the right stage of design, consideration of all related information creates a mental load on the designer resulting in the potential omission of information, compromising the design outcome. b. A reduction in the design team’s collective awareness throughout the design process: when a number of designers are tasked to complete a design, information transfer among designers might also impact collective awareness in a team and hence the design outcome (e.g., a member not transferring the required information to others on time, or not
and firstrelates the sum of IPRO Day exhibit and presentation scores [table A] to other outcomemeasures. Then in tables B and C respectively we relate the IPRO Day exhibit andpresentation rankings specifically to other learning outcome measures. Finally in table D Page 13.578.5we take a subset of the teams, where the learning objective test is included in thesemester grade, and specifically correlate those team rankings with total IPRO Day teamrankings and with IPRO Day presentation and exhibit rankings.Table A: Various Outcome MeasureRankings Correlated* with Total IPRO Day Score Rankings Fall Spring
participanthas up to three hours to complete the task. The statement details constraints and encourages theparticipant to request information. The participant has access to a resource box withmiscellaneous tools (i.e., a calculator, post-it notes, pencils, pens, colored pencils, rulers, etc.).They have additional access to the facilitator and information binder (the participant must ask forspecific information) and an internet-connected computer. Refer to figure 1 for the design taskstatement. Figure 1: Study Design Task Statement B. Description of the DataEach design session lasts up to three hours. There is a scheduled ten-minute break and anapproximately 25-minute follow-up interview. Each session is video
Paper ID #33160The Impact of Scaffolding Prompts on Students’ Cognitive InteractionsDuring Collaborative Problem Solving of Ill-structured Engineering TasksMiss Taylor Tucker, University of Illinois at Urbana-Champaign Taylor Tucker graduated from the University of Illinois at Urbana-Champaign with a Bachelor’s degree in engineering mechanics. She is now pursuing a master’s degree at UIUC through the Digital Environments for Learning, Teaching, and Agency program in the department of Curriculum and Instruction. She is interested in design thinking as it applies to engineering settings and lends her technical background to
Paper ID #28645Incorporation of virtual learning environments for online STEM activitiesStefan Kleinke, Embry-Riddle Aeronautical University, Worldwide Campus Stefan Kleinke is a full-time faculty member of the College of Aeronautics at Embry-Riddle Aeronautical University, Worldwide. He currently instructs subject areas that range from aerodynamics and aircraft performance to unmanned system’s operational aspects such as sensing, navigation, and task-oriented optimization. As a former military flight instructor and examiner, he also gained expertise in student pilot and pilot instructor training and its standardization
geomorfología de Chile”, Revista Eureka sobre Enseñanza y Divulgación de las Ciencias, vol. 16, nº 2, p. 2202, feb. 2019.[4] T. Crews and J. B. Butterfield, “Data for Flipped Classroom Design: Using Student Feedback to Identify the Best Components from Online and Face-to-Face Classes”, HES, vol. 4, no 3, pp. 38-48, may 2014, doi: 10.5539/hes.v4n3p38.[5] J. Bergmann and A. Sams, “Flip Your Students’ Learning,” Educational Leadership, vol 70, nº 6, pp.16-20, mar. 2013.[6] Electronic Education Report, “Pearson Partners on Flipped Learning”, jul. 2013. Access: mar. 04, 2021. [Online]. Available: https://www.electroniceducationreport.com/content/pearson-partners-flipped-learning[7] I. M. Solano Fernández, Podcast
below to illustrate the kinds ofresponses. Identifying details have been removed or changed to protect participants. The textappears just as they entered it: no grammatical or spelling corrections have been made. Therewere two relevant questions: a) The organization/project you are now working with (type of business, type of section where you work, main project you are working on). b) Tell us what you have been doing in your job in the last month.Applied Ocean Science (“other” group)a) I work in a large engineering consultancy. I work in the coastal and ocean group of the Page 13.857.11Infrastructure group. The main project I am
," Qualitative Social Work, vol. 1, pp. 261-283, 2002.[4] M. Tafur and S. Purzer, "The Role of Outlier Analysis in Reducing Purposeful Sampling Bias: A Sequential Mixed-Method Approach," in 2015 ASEE Annual Conference, Seattle, Washington, 2015.[5] M. Tafur Arciniegas, "Understanding how adults approach technological challenges: A sequential mixed methods research," 2015.[6] L. M. Bowen, "Resisting Age Bias in Digital Literacy Research," College Composition and Communication, vol. 62, pp. 586-607, 2011.[7] K. Mogg, B. P. Bradley, and N. Hallowell, "Attentional Bias to Threat: Roles of Trait Anxiety, Stressful Events, and Awareness," The Quarterly Journal of Experimental Psychology Section A, vol. 47, pp
Processing for Information Retrieval: The Time is Ripe (again). Association for Computing Machinery, Inc. New York:NY.9 Zipf, H.P. 1949. Human Behaviour and the Principle of Least Effort. Addison-Wesley, Cambridge:MA.10 Li, W. Random Texts Exhibit Zipf's-Law-Like Word Frequency Distribution. IEEE Transactions on Information Theory. 38.6 (1992): 1842-5.11 Bloom, L. Cognition and the Development of Language. Language. 50.2 (1974): 398-412.12 Saffran, Jenny R., et al. Incidental Language Learning: Listening (and Learning) Out of the Corner of Your Ear. Psychological Science. 8.2 (1997): 101-5.13 The Linguistics Encyclopedia. Ed. Kirsten Malmkjær. 2nd ed. 2002. Routledge, New York.14 González B., J., Pazos R., Gelbukh, A., Sidorov
. P. (1990). The principles of design (No. 6). Oxford University Press on Demand.Torrance, E. P. (1966). Torrance tests of creative thinking: Norms-technical manual (Researched.). Princeton, NJ: Personnel Press.Treffinger, D., Isaksen, S., & Dorval, B. (2000). Creative problem solving: An introduction (3rded.). Waco, TX: Prufrock Press.Weisberg, R. W. (1999). Creativity and knowledge: A challenge to theories. In R.J. Sternberg(Ed.), Handbook of creativity (pp. 226-250). Cambridge, UK: Cambridge University Press.AppendixFull List of Reflection Questions Question Type Question Response Type Individual How comfortable do you feel in using the 1-6 (1=very uncomfortable, questions
,Instructor 1 concerns of the campus costs associated B/C ratios, considering community with a new all relevant criteria, lighting system dealing with uncertaintyTrees and Determining if old Weighting cost estimation, time 49 51%Road growth trees should be environmental value money, comparingSafety removed to provide concerns alternative investments, more safety on a park compared to B/C ratios, consideringInstructor 1 road driver safety all relevant criteria
of student learning (See Appendix B for activity sample & Appendix Cfor quiz sample).The categories in our framework used for question development represented different levels ofcognitive activity required to respond to the question, which was also considered to be indicativeof question difficulty.27 The verbatim type questions were generated from ideas and informationexplicitly stated in the activity, and required students to merely recall the correct responses. Forexample, to correctly answer the verbatim question in the concepts in context activity, studentsneeded to select a disaster/failure that occurred as a result of an incomplete phase transformation;this information was explicitly stated in the activity. The comprehension
entrepreneurial mindsetby the time students complete their programs. The instrument will be shared with otherengineering colleges.Biography1. Shartrand, A., Weilerstein, P., Besterfield-Sacre, M., & Olds, B. (2008) Assessing student learning in technology entrepreneurship. The 38th ASEE/ISEE Frontiers in Education Conference. Saratoga Springs, NY.2. Pittaway, L. & Hannon, P. (2009). Assessment practice in enterprise education. International Journal of Entrepreneurial Behavior and Research. 15(1): 71-93.3. Standish-Kuon, T., & Rice, M. P. (2002). Introducing engineering and science students to entrepreneurship: Models and influential factors at six American universities. Journal of Engineering Education. 91(1): 33-39.4. Bilen, S.G
Paper ID #7111From Freshman Engineering Students to Practicing Professionals: Changesin Beliefs about Important Skills over TimeDr. Katherine E Winters, Virginia Tech Katherine Winters earned her PhD in Engineering Education from Virginia Tech studying the career goals and actions of early career engineering graduates. She also has BS and MS degrees in Civil Engineering from BYU.Dr. Holly M Matusovich, Virginia TechMs. Samantha Brunhaver, Stanford University Samantha Brunhaver is a fifth year graduate student at Stanford University. She is currently working on her PhD in Mechanical Engineering with a focus in
first semesterweekly meetings were held for F-VCPs to (a) learn about and discuss issues of student learningand implementation of research-based educational practices in their courses, and (b) plan theimplementation of the research-based educational practices appropriate for each participant. Inthe second semester of each cycle, F-VCP participants met on a semi-regular basis to supporteach other as they carried out their newly planned research-based educational approach in theircourse. Different research-based educational practices were covered and discussed in each F-VCP, at the discretion of the community leaders. Greater detail can be found in Authors (2016). F-VCP participants collaborated and developed their communities of practice
milestones on community college student outcomes. Research in Higher Education, 48(7), 775-801.Dawson, S., & Hubball, H. (2014). Curriculum analytics: application of social network analysis for improving strategic curriculum decision-making in a research- intensive university. Teaching and Learning Inquiry: The ISSOTL Journal, 2(2), 59-74.Hodara, M., & Rodríguez, O. (2013). Tracking Student Progression through the Core Curriculum. New York: Community College Research Center, Columbia University.Krumm, A. E., Waddington, R. J., Teasley, S. D., & Lonn, S. (2014). Using Data from a Learning Management System to Support Academic Advising in Undergraduate Engineering Education. In J. A. Larusson & B
thiscourse has improved your competence in a number of important areas. For each of thefollowing, please indicate how much this course has improved your knowledge or skill.” Program outcomes: (a) an ability to apply knowledge of mathematics, science, and engineering (b) an ability to design and conduct experiments, as well as to analyze and interpret data (c) an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability. (d) an ability to function on multi-disciplinary teams (e) an ability to
Engineering Education Research: Reflections on an Example Study,” Journal of Engineering Education, vol. 102, no. 4, pp. 626–659, 2013, doi: 10.1002/jee.20029.[10] J. Walther et al., “Qualitative Research Quality: A Collaborative Inquiry Across Multiple Methodological Perspectives,” Journal of Engineering Education, vol. 106, no. 3, pp. 398– 430, 2017, doi: https://doi.org/10.1002/jee.20170.[11] S. Tan, “The Elements of Expertise,” Journal of Physical Education, Recreation & Dance, vol. 68, pp. 30–33, Feb. 1997, doi: 10.1080/07303084.1997.10604892.[12] C. Aaron, E. Miskioglu, K. M. Martin, B. Shannon, and A. Carberry, “Nurses, Managers, and Engineers – Oh My! Disciplinary Perceptions of Intuition and Its Role in
] Chen, H.L., O. Eris, K.M. Donaldson and S.D. Sheppard. "From PIE to APPLES: The Evolution of a Survey Instrument to Explore Engineering Student Pathways" ASEE, Pittsburgh, 2008.[17] Astin, A.W., "Student Involvement: A Developmental Theory for Higher Education" Journal of College Student Development, vol. 40, no. 5, pp. 518-529, 1999.[18] Light, R.J., Making the Most of College: Students Speak Their Minds. Cambridge, MA: Harvard University Press, 2001.[19] Berger, J.B., J.F. Milem and M.B. Paulsen. "The exploration of "habitus" as a multi-dimensional construct" The Association for the Study of Higher Education, Miami, 1998.[20] Chubin, D., K. Donaldson, L. Fleming and B. Olds, "Educating
AC 2008-696: MEETING THE CHALLENGE OF REVIEWING ELEVENENGINEERING PROGRAMSPierre Lafleur, Ecole Polytechnique de Montreal Pierre G. Lafleur is Professor of Chemical Engineering and Director of accademic affairs at Ecole Polytechnique of Montreal, Quebec, Canada. He has obtained his engineering degree from Ecole Polytechnique and his Ph.D. in Chemical Engineering from McGill University in the field of Polymer Engineering. After graduating he worked in industry before joining École Polytechnique in 1985. Professor Lafleur has been extensively involved in undergraduate teaching and graduated 20 master and 15 Ph.D. students. He has published more than a 100 articles in scientific journals
complex game.” Journal of the Operational Research Society, 33:63–71.[13] McClure, J.R., Sonak, B., and Suen, H.K. (1999). “Concept map assessment of classroom learning: Reliability, validity, and logistical practicality.” Journal of Research in Science Teaching, CCC 0022-4308/99/040475-18, 475–492.[14] Novak, J., and Canas, A. (2008). “The Theory Underlying Concept Maps and How to Construct and Use Them.” Technical Report IHMC CmapTools 2006-01 Rev 01-2008.[15] Yin, Y, Vanides, J. Ruiz-Primo, M.A., Ayala, C.C., and Shavelson, R.J. (2005). “Comparison of two concept- mapping techniques: Implications for scoring, interpretation, and use.” Journal of Research in Science Teaching, 42(2):166–184.[16] Walker
, J.W. and G.M. Zhang, A Freshman Engineering Design Course. Journal of Engineering Education, 1993. 82(2): p. 83-91.12. Natishan, M.E., L.C. Schmidt, and P. Mead, Student Focus Group Results on Student Team Performance Issues. Journal of Engineering Education, 2000. 89(3): p. 269-272.13. Eide, A., R. Jenison, L. Northup, and S. Mickelson, Engineering Fundamentals and Problem Solving. Fifth ed, ed. B. Stenquist. 2008, Boston: McGraw-Hill.14. Creswell, J.W., Qualitative Inquiry and Research Design: Choosing Among Five Approaches 2nd. Ed. 2007, Thousand Oaks, CA: Sage Publications. Page 15.869.2115. Lincoln, Y.S. and E.G. Guba
, provided the tuition resourcesnecessary to underwrite new degree programs and initiatives in engineering education. Anengineering workforce shortage of about 8,000 was also anticipated during the coming decade atthe time of our interviews.Overall, it is our assessment that the Danish national response to Bologna can be characterized asfollows: A decision to embrace the Bologna Process through a desire to introduce market competition, greater specialization, and responsiveness within Denmark’s educational institutions, especially at the master’s level. A decision to address both the a) short term recessionary softening of the labor market and the b) long-term competitiveness of the Danish workforce by having 50% of all
Page 15.302.7engineering hires and (b) after a few years on the job. We requested the Delphi participants toanswer these questions, providing as much detail as possible.These six Delphi questions were: 1. What computing competencies are required for new technical hires at your company? 2. What computing proficiencies do you expect your technical employees to develop during their first few years on the job? 3. What new computing skills and processes do you see emerging in the next couple of years in your field? 4. Once fluent, what types of problems do you expect your technical employees (with 3-5 years of experience) to solve using computing tools? 5. Once fluent, what types of projects do you expect your technical