class. After initial contact, volunteers participated in a sample interview, completed theStatics Concept Inventory10, and were classified in quartiles based on their Statics grade. Duringthe sample interview students were asked questions about their personal history in order toprovide sociocultural background information, they were asked to complete a statics ranking task Page 23.963.4in order to assess their Statics concept reasoning, and they were asked two questions fromGreene et al.’s Epistemic and Ontological Cognition Questionnaire5 to get an initial assessmentof their personal epistemology. After the interview, students were asked to
National Council for Science and Technology ScholarshipNo. 293125. 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, nor The United States - Mexico Commission for the Educational andCultural Exchange, neither those of Mexico’s National Council for Science and Technology. Page 23.1211.14References1 Melsa, JL (2007) ‘The winds of change’. ASEE Banquet Keynote Speech.2 Chubin, Daryl E., May, Gary S. and Babco, Eleanor L. (2005) ‘Diversifying the engineering workforce’. Journal of Engineering Education
learning effectiveness, and we will be able to validate it through thequalitative interviews. This study will also evaluate the two questions, R11-rewrite and R12-rewrite that webrought back in from the original IMMS table and added into RIMMS and will update RIMMS asRIMMS++ if they show any significance.References ˚ Cajander, V. Kann, A. Kapoor, R. McDermott, A.-K. Peters, M. Sabin, and [1] S. Frezza, M. Daniels, A. Pears, A. C. Wallace, “Modelling competencies for computing education beyond 2020: a research based approach to defining competencies in the computing disciplines,” in Proceedings Companion of the 23rd Annual ACM Conference on Innovation and Technology in Computer Science Education
handbook of expertise and expert performance, New York, Cambridge University Press, 2006, pp. 21-30.[8] G. Klein and R. R. Hoffman, "Macrocognition, mental models, and cognitive task analysis methodology," in Naturalistic Decision Making and Macrocognition, Hampshire, U.K., Ashgate, 2008, pp. 57-80.[9] R. R. Hoffman and G. Lintern, "Eliciting and representing the knowledge of experts," in Cambridge Handbook of Expertise and Expert Performance, New York, Cambridge University Press, 2006, pp. 203-222.[10] R. R. Hoffman and J. Smith, Toward a general theory of expertise: Prospects and limits, New York: Cambridge University Press, 1991.[11] S. E. Dreyfus and H. L. Dreyfus, "A Five-Stage Model of the Mental Activities Involved in
designThis study is grounded in an interpretivist research philosophy that acknowledges a subjective,socially constructed reality [11]. Consistent with this philosophy, we will use open-endedquestions in an interview setting to understand the participants’ realities through their ownperspectives. Throughout the research process, we will refer to Walther et al.’s qualityframework for interpretive research, which provides guiding questions to ensure quality throughall the stages of research – from “making data” to “handling data” – and across six qualityconstructs: theoretical validation, procedural validation, communicative validation, pragmaticvalidation, ethical validation, and process reliability [12]. Our considerations for each of thesequality
Pedagogy AbstractThe purpose of this work-in-progress (WIP) paper is to report on an ongoing study that used Chiand Wylie (2014)’s Interactive, Constructive, Active, and Passive (ICAP) framework (I > C > A> P) to survey the degree to which LC-DLMs foster cognitive engagement as students learn abouta venturi meter in a fluid mechanics and heat transfer course. Fredricks, Blumenfeld, and Paris(2004) define cognitive engagement as the effort students invest in understanding what they arelearning. Indeed, cognitive engagement is critical for effective teaching and learning inengineering. Although there is research evidence showing that students learn better with hands-onapproaches than traditional
think up as many possible ways tohandle it as I can until I can’t come up with any more ideas” to what is shown in Table 1. Table 1 – Questions of the EM-PSI Item Engineering Modified PSI (EM-PSI) Subscale 1 When I face a complex problem, I first define exactly what the problem goal(s) is. AAS 2 When a solution method to a problem was unsuccessful, I do not examine why it did not work. AAS 3 If my first effort to solve a problem was unsuccessful, I become unsure about my ability to PC
consequences of the scenario to a broader scope than thespecific situation. They look at how situations like this affect not only the people at that specifictime, but also after the fact and how it affects the community as a whole.C. Compartmentalizing (5): S ubjects agree that there is an issue related to diversity/inclusion,but it is irrelevant to the decision at hand. Often saying things like “In general, this isinappropriate. In this situation…”E. Equivocating (1): Subject is focused on having a back-and-forth with themselves, oftenbouncing between two (or more) alternate perspectives. Usually in a “can’t decide” scenario, butcan become prevalent through the questioning process.S. Solution-Focused (2): Students tend to craft their own
exchange about the challenges of working on diverse studentteams and about how to resolve these challenges, faculty can go a long way to helping Page 14.1312.7engineering students develop the skills, knowledge, and awareness they will need upongraduation.References1. Gurin, P., Dey, E. L., Hurtado, S., & Gurin, G. (2002). Diversity and higher education: Theory and impact on educational outcomes. Harvard Educational Review, 72(3), 330-366.2. Hong, L., & Page, S. E. (2004). Groups of diverse problem solvers can outperform groups of high-ability problem solvers. PNAS, 101(46), 16385-16389.3. Kaplan, M., Cook, C. E., Steiger, J
. One busy intersection on campus is the crossing of Fifth Ave. in front of the bookstore. Dangers at this intersection include heavy traffic and busses which run against the general traffic flow (see diagram below). The University would like to design a cost effective method for students to cross Fifth Ave. which would reduce the possibility of accidents at this intersection. You have been assigned to design a solution to this problem for presentation to the University Traffic Committee. In the process of designing your solution you have been asked to respond to the set of questions on the following pages. The interviewer has more paper if you need it. 1. What is the problem as you see it? 2. List potential solution(s) for this
(1), 33 Lesniak, R. J., & Hodes, C. L. (2000). Social relationships: learner perceptions of interactions indistance learning, The Journal of General Education, 49(1), 34-43.4 Gray, G. L., Evans, D., Cornwell, P., Contanzo, F., and Self B., (2003). Toward aNationwide Dynamics Concept Inventory Assessment Test, Proceedings of the2003 American Society for Engineering Education Annual Conference, Vol Sessions 1168, Nashville,TN: ASEE.5 Timoshenko, S. P., (1983) History of Strengths of Materials, New York: DoverPublications, pp 67-70.6 About the Ecole Polytechnique (2008) Retrieved July 28 2008from: http://www.polytechnique.edu/page.php?MID=177 More Than 75 Years of Quality Assurance in Technical Education, Retrieved 28 July2008 from
Page 14.83.10appropriate comprehensive map, this method does provide a much clearer insight into thefundamental understanding students gain based upon their enrollment in assorted courses.References[1] National Research Council (U.S.). Committee on Learning Research and Educational Practice., J. Bransford, J. W. Pellegrino, S. Donovan, and NetLibrary Inc., "How people learn bridging research and practice," Washington, D.C.: National Academy Press, 1999, pp. x, 78 p.[2] J. R. Anderson and C. Lebiere, The atomic components of thought. Mahwah, N.J.: Lawrence Erlbaum Associates, 1998.[3] J. D. Novak, Learning, creating, and using knowledge: Concept maps as facilitative tools in schools and corporations
gatheringinformation typically considered “experience”. Such experience is typically associated with thehigher level cognitive tasks, synthesis and evaluation, as defined by Bloom and Krathwohl(1984). When used with many practitioners, the technique can yield a database of diverseexperiences that can be incorporated into course instruction and assignments. Some examples ofdata for which the critical incident technique is well suited to obtain include the following:• The criteria designers use to evaluate competing design options.• The most important factors that designers consider in making a decision about which material(s) to use.In contrast, eliciting knowledge about low- to mid-level cognitive tasks such as comprehension,application, or analysis (Bloom
] Tytler, R (2007). Re-imagining science education: Engaging students in science for Australia’s future. Australian Education Review, 51.[4] CNBC (2016). Millennials are driving the board games revival. Retrieved from https://www.cnbc.com/2016/12/22/millennials-the-board-games-revival-catan- pandemic.html[5] Eisenack, K. (2013). A climate change board game for interdisciplinary communication and education. Simulation & Gaming, 44(2-3), 328-348.[6] Fukuchi, S. G., Offutt, L. A., Sacks, J., & Mann, B. D. (2000). Teaching a multidisciplinary approach to cancer treatment during surgical clerkship via an interactive board game. The American journal of surgery, 179(4), 337-340.[7] Huang, A., & Levinson, D
National Science Foundation.References[1] D., Clive L., A., M. Agogino, O., Eris, D., D. Frey, and L., J. Leifer. "Engineering designthinking, teaching, and learning." Journal of engineering education 94, no. 1 (2005): 103-120[2] C., David P., and R., S. Adams. "The informed design teaching and learning matrix." Journalof Engineering Education 101, no. 4 (2012): 738-797.[3] Y. Y., Seah, and A. J., Magana. "Exploring students’ experimentation strategies inengineering design using an educational CAD tool." Journal of Science Education andTechnology 28, no. 3 (2019): 195-208.[4] M. H., Goldstein., Ş., Purzer, C., Vieira Mejia, M., Zielinski, and K. Anna Douglas."Assessing idea fluency through the student design process." In 2015 IEEE Frontiers
, greater equitycould perhaps be achieved by making used surplus university laptops available for checkout, or bydiverting some of the funds used to update and maintain fixed computer labs to create a pool oflaptops that can be checked out to students in need.References [1] Digilent, “Analog Discovery 2: 100ms/s USB Oscilloscope, Logic Analyzer and Variable Power Supply,” 2019. [Online]. Available: https://store.digilentinc.com/ [2] Raspberry Pi Foundation, “Raspberry pi,” https://www.raspberrypi.org/, 2019. [3] Mathworks, “MATLAB Online,” https://www.mathworks.com/products/matlab-online.html/, 2019. [4] ——, “MATLAB Mobile Overview,” https://www.mathworks.com/products/matlab-mobile.html/, 2019. [5] E. P. St. John, S. Hu, and J. Weber, “State
undergraduateengineering programs? Do first-generation students’ funds of knowledge shift or change as theyassimilate to their undergraduate engineering programs? We believe that future work in this areawill significantly improve retention for first-generation students within engineering and open waysfor them to feel like they fit in engineering.Table 3. First Round of Data Extraction for Primary SourcesTitle/Author(s) Source Purpose of Study Type of Study Setting/ Data Collected Summary of Findings PopulationAntonellis (2013). ProQuest This research was intended as Qualitative
and teaching styles in engineering education, Engineering Page 24.1363.12Education, 78, 674-681, 1988, Author's Preface.4. Tall, D. (1991), Intuition and rigor: the role of visualization in the calculus. In Zimmerman& Cunningham (Eds.), Visualization in Mathematics, M.A.A., Notes No. 19, 105-119.5. Heath, M., Malony, A., Rover, D. (1995), The visual display of parallel performance data,Computer, 28, 21-28.6. Wood, S. (1996), A new approach to interactive tutorial software for engineering education,IEEE Transactions on Education, 39, 399-408.7. Novick, L. R., Hurley, S. M., Francis, M. (1999), Evidence for abstract, schematicknowledge of three
engineering education.BackgroundCBAM was developed in the 1970’s and 1980’s by researchers at the University of Texas atAustin. Over this timeframe, three main components were created; Levels of Use (howindividuals interact with the innovation), Stages of Concern (the feelings of individuals), andInnovation Configurations (how the innovation is adapted to a particular setting). When used inconjunction, these components aid in assessing and guiding the adoption of innovations in aneducational setting7. Explaining the full complexity of CBAM is beyond the scope of this paperbut this body of research can be further explored in the included references 3,6,8,9
Capacity of the United States Engineering Research Enterprise, Washington, D.C.: National Academies Press.[4] Clough, G. W., 2004, The Engineer of 2020: Visions of Engineering in a New Century, Washington, D.C.: National Academy of Engineering.[5] Sheppard, S. D., Macatangay, K., Colby, A., and Sullivan, W. M., 2009, Educating Engineers: Designing the Future of the Field, Stanford, CA: The Carnegie Foundation for the Advancement of Teaching.[6] Johnson, D. W., Johnson, R. T., and Holubec, E. J., 1990, Circles of Learning: Cooperation in the Classroom, Edina, MN: Interaction Book Company.[7] Dym, C. L., Agogino, A. M., Eris, O., Frey, D. D., and Leifer, L. J., 2005, "Engineering Design
to share their voices and experiences and those who assisted with access theseparticipants. The authors also wish to thank Blanca Miller, Jessica Chestnut, Daniel Briggs, andAaron Lando for their contributions to the project.References[1] S. Cho, K.W. Crenshaw, and L. McCall, “Toward a field of intersectionality studies: Theory, applications, and praxis,” Signs, vol. 38 no. 4, pp. 785-810, 2013.[2] A.-M. Nunez, “Employing Multilevel Intersectionality in Educational Research: Latino Identities, Contexts, and College Access,” Educational Researcher, vol. 43, no. 2, pp. 85–92, 2014[3] S. M. Lord, M. M. Camacho, R. A. Layton, R. A. Long, M. W. Ohland, and M. H. Wasburn, “Who’s Persisting in Engineering? A
. Three engineering-education collaborators were interviewed in dyads tounderstand conceptualizations of futures, values, systems, and strategic thinking in relation totheir joint research project(s). All three dyads provided specific examples of different ways ofthinking from their shared research efforts. Preliminary findings suggest that a ‘ways of thinking’framework could provide a useful guideline for engineering and education faculty planning tocollaborate for interdisciplinary research as well as the overall EER community.OverviewThe world today faces complex problems ranging from climate change to health issues.Numerous calls by prominent organizations have been made in light of these global,sociotechnical problems to transform
. These comments allexplain the function of the code without simply restating the code. For example, comment n usesthe word “loops”, an indication that it could be a literal restatement of code, but the commentcontinues to explain that the source code is “comparing to find the highest comparison and itsindex”, which provides additional insight into the source code functionality that is not simply arestatement. Figure 5: Case Study C: Every-line. Source code for Lab Sample WL6_S5_G6.The literal comments are a, c, i and s. a and c are a plain English restatement, and i bordersbetween literal and conceptual as the comment has two parts. First, they state that they are‘looping’ which is literal and then they state ‘adds all
. Educ., vol. 98, no. 3, pp. 283–294, Jul. 2009, doi: 10.1002/j.2168-9830.2009.tb01025.x.[3] S. Rosen et al., “Relating Level of Inquiry in Laboratory Instructions to Student Learning Outcomes,” p. 15.[4] S. Nikolic, “Training laboratory: Using online resources to enhance the laboratory learning experience,” in 2014 IEEE International Conference on Teaching, Assessment and Learning for Engineering (TALE), 2014, pp. 51–54, doi: 10.1109/TALE.2014.7062584.[5] L. D. Feisel and A. J. Rosa, “The Role of the Laboratory in Undergraduate Engineering Education,” J. Eng. Educ., vol. 94, no. 1, pp. 121–130, Jan. 2005, doi: 10.1002/j.2168-9830.2005.tb00833.x.[6] S. Nikolic, C. Ritz, P. J. Vial, M. Ros, and D. Stirling, “Decoding
use of the instrument to track growth over time.Revisions to the PCTA are being incorporated to improve its reliability and the scoring rubric for the open-ended items is being reviewed in light of student responses so that it provides a closer match to the types ofresponses expected. Differential item function analyses will explore any potential biases in the instrumentaccording to age, gender, race, and education level. Eventually the results will be compared betweentreatment and control groups to provide evidence toward the efficacy of programs that focus on developingteachers’ CT instructional competencies.References[1] S. Papert, & I. Harel (1991). “Situating constructionism,” Constructionism, 36(2), 1-11.[2] S. Cansu, F Cansu (2019
persistence, goal setting, andresilience. The persistence factors highlighted in this study include students’ motivation andcommitment to their educational goals4.MotivationStudents are motivated to enter and complete engineering programs by a myriad of sources.Parents, teachers, mentors, and even other students provide the kind of guidance and supportneeded to complete an engineering degree program5. Some students require a great deal ofsupport from teachers and mentors, while others persist on limited support or under their ownvolition. In this study, students that are motivated out of “a true sense of choice, a sense offeeling free in doing what [s/he] has chosen to do” are considered dogged6.An important aspect of motivation is found in the
, L. Baker-Ward, E. Dietz, and P. Mohr, (1993) "A Longitudinal Study of Engineering Student Performance and Retention I. Success and Failure in the Introductory Course," Journal of Engineering Education, pp. 15-21, 1993.House, J., (2000). “Academic Background and Self-Beliefs as Predictors of Student Grade Performance in Science, Engineering and Mathematics," International Journal of Instructional Media, vol. 27, pp. 207-220, 2000.Immekus, J., S. Maller, P.K. Imbrie, N. Wu, P. McDermott, (2005). Work In Progress: An Analysis of Students’ Academic Success and Persistence Using Pre-College Factors” Proceedings of the Frontiers in Education Conference, 2005.Jagacinski, C. and LeBold, W., (1981). “A Comparison of Men and Women
teams that differ in gender composition. Proceedings of the ASEE Annual Conference & Exposition, Session 2630.16. Hirsch, P., Anderson, J., Colgate, J.E., Lake, J., Shwom, B. and Yarnoff, C. (2002). Enriching freshman design through collaboration with professional designers. Proceedings of the ASEE Annual Conference & Exposition, Session 1353.17. Design Projects, http://www.ecsel.psu.edu/design-projetcs/, viewed on July 6th, 2004.18. Sheppard, S., Jenison, R. (1997). Freshman engineering design experiences: An organization framework. International Journal of Engineering Education, 13(3), p 190-197.19. Amon, C.H., Finger, S., Siewiorek, D.P., and Smailagic, A. (1995). Integration of design education, research, practice at
Outreachactivities Indicate Dual Benefits, American Society for Engineering Education, 2010[2] Rippon, S., Collofello J., and Hammond R. (2012). That’s What an Engineer Does?: Freshmen Developing aPersonal Identity as an Engineer. American Society for Engineering Education, 2012[3] Poole, S.J., deGrazia, J.L. and Sullivan, J.F. (2001). Assessing K-12 Pre-Engineering Outreach Programs.Journal of Engineering Education, January 2001, 43-48.[4] Louis S. Nadelson and Janet Callahan, A. (2001). Comparison of Two Engineering OutreachPrograms for Adolescents. Journal of STEM Education, Volume 12, Issue 1 & 2, January-March 2011[5] Bachnak, R., Chappa, E., and De La Rosa, K. (2009). Exposing K-12 Students to Science and Engineering,October 18 - 21, 2009, San
correct any serious design problems before the sensorsare fabricated. A key deliverable is the implementation of the design algorithm, usually in aspreadsheet (see Figure 4).Students were guided toward designing load cell transducers configured as circular aluminumrings because aluminum rings of various sizes were readily and inexpensively available from thedepartment machine shop. Some student teams whose members had machine shop experiencechose to design and fabricate transducers of other types, such as a C-shaped transducer whichhad multiple attachment points to allow its range to be adjusted and an S-shaped transducerwhich was similar to some commercial designs (see Figure 5). Figure 4: Load cell transducer design spreadsheet created by