theory. A case study is the study of a specific phenomenon bounded to a system thatcan be analyzed individually to understand the phenomenon under specific circumstances [14,15]. The process of competencies transfer in industrial engineering students was our case ofstudy. According to Merriam [14], some of the characteristics of a case study are: a. Particularistic: referring to the particular situation of the process of professional internships done by industrial engineering students from the [blinded for review] b. Descriptive: the final product of the study is a rich and dense description of the internship phenomenon c. Heuristic: gives rise to new meanings of the process of transfer of competencies in [blinded for review]´s
Society, 2015.[4] B. Swartz, S. B. Velegol, and J. A. Laman, “Three Approaches to Flipping CE Courses : Faculty Perspectives and Suggestions,” 120th ASEE Annu. Conf. Expo., 2013.[5] A. Lee, H. Zhu, and J. A. Middleton, “Effectiveness of flipped classroom for mechanics of materials,” ASEE’s 123rd Annu. Conf. Expo., no. May, 2016.[6] A. B. Hoxie, T. Shepard, and R. Feyen, “The Flipped Classroom : A Means to Reduce Cheating?,” 122nd ASEE Annu. Conf. Expo., no. Paper ID #11445, p. 16, 2015.[7] J. Laman, M. L. Brannon, and I. Mena, “Classroom Flip in a Senior-Level Engineering Course and Comparison to Previous Version,” in American Society for Engineering Education, 2012.[8] G. S. Mason, T. R. Shuman, and K
Paper ID #24975Integrating Inclusive Pedagogy and Experiential Learning to Support Stu-dent Empowerment, Activism, and Institutional Change: A Case Study withTransgender STEM StudentsKristin Boudreau, Worcester Polytechnic Institute Kristin Boudreau is Paris Fletcher Distinguished Professor of Humanities at Worcester Polytechnic In- stitute, where she also serves as Head of the Department of Humanities and Arts. Her training is in nineteenth-century literature, but for the past 8 years she has taught engineering ethics, first-year en- gineering courses, and humanities for engineers. She has also worked with students and
what was going on and successfully completing the tasks. Also in Classroom A thelead teacher was not the only one leading the class; aids would also pitch in with instructions andguidance. Classroom B was presented information at a much faster pace. Students in the focusgroups noted the instructor talked fast, so students in that room were getting lost more frequentlyand relied heavily on the classroom aids to help them one on one. Classroom B had one extra pairof students so all aids couldn’t help everyone at the same time. We also noticed that Classroom Bwas louder than Classroom A as so many different side conversations were going on. Bothclassrooms were able to complete the given tasks, only one group struggled to finish their finalproject
engage her child in CT during integrated CT+engineering activities. The researchquestions addressed in this study are: What roles does a homeschool parent play that lead to their child’s engagement in computational thinking during (a) an integrated literacy, STEM, and CT curriculum at home, and (b) interaction with an engineering and computational thinking exhibit in a science center? MethodsResearch Design This is a qualitative study that utilized a single-case-study approach to investigate theroles that a homeschool parent plays in promoting CT in her six-year-old child. We employed acase study approach because a case study is an empirical inquiry which can provide
courses by comparing their effectiveness to regular State College courses in (a) student academic success and (b) student success in follow-up courses (e.g., relative success of students in Calculus after taking the prerequisite Pre-Calculus course.o Introduction to Programming offered at State Colleges. Because this course also has a high DFW (i.e., failure and withdrawal) rate, it serves as a barrier to students whose intent is to major in computer science. The objective of this project curriculum refinement component is to improve the conceptual framework of this course so it is optimally effective for State College students in terms of course achievement outcomes and retention in a STEM education degree track. The course
-Jones, Eds. Philadelphia: John Benjamins Publishing Company, 2000, pp. 17–29.[11] S. Wineburg, “Historical Problem Solving : A Study of the Cognitive Processes Used in the Evaluation of Documentary and Pictorial Evidence,” Journal of Educational Psychology, vol. 83, no. 1, pp. 73–87, 1991.[12] S. Wineburg, “Reading Abraham Lincoln: An expert/expert study in the interpretation of historical texts,” Cognitive Science, vol. 22, no. 3, pp. 319–322, 1998.[13] J. Lave, “Situating Learning in Communities of Practice,” in Perspectives on Socially Shared Cognition, vol. 2, L. B. Resnick, J. M. Levine, and S. D. Teasley, Eds. Washington, D.C.: American Psychological Association, 1991, pp. 63–82.[14] J. Lave and E. Wenger, Situated
. 107 - 112.[14] Wood, D. J. and Gray, B. (1991). “Toward a Comprehensive Theory of Collaboration”. Journal of Applied Behavioral Science 27 (2), pp. 139-162.[15] Russel, J.A., Weiss, A. and Mendelsohn, G.A. (1998). “Affect Grid: A Single-Item Scale of Pleasure and Arousal”, Journal of Personality and Social Psychology 57 (3), pp. 493- 502.[16] Koch, C., Neges, M., König, M. and Abramovici, M. (2014). ‘Natural Markers for Augmented Reality-Based Indoor Navigation and Facility Management‘. Automation in Construction 48, pp. 18-30.[17] https://anymotion.com/wissensgrundlagen/augmented-reality-marker[18] Lehmann-Willenbrock, N., Allen, J. A. and Kauffeld, S. (2013). „A Sequential Analysis of Procedural Meeting Communication: How Teams
of it in a coherentfashion.Figure 7: Coincident lines (Line A and Line B) on different planes in an isometric view.Figure 8: Student sketched chamfered corner where collinear vertical line represents two edgeson different planes (indexed 4c and 4d in data).Figure 9 shows a part with curved surfaces which the student found difficult to sketch. Incontrast, Figure 10 shows a very similar part that the student sketched without difficulty.Figure 9: Curved surface part that proved difficult for student to render orthographically.Figure 10: Similar curve surface part that the student sketched easily.In summary, the student learned to sketch isometric views of parts without the support of 3Dprinted parts. The isometric views were clear, and visually
the impactof bonus depreciation and questions whether bonus depreciation makes after-tax analysis lessnecessary.Table4.BeforeandAfterTaxCashFlows (d) (e) (a) (c) 21% After-Tax Before-Tax (b) Taxable Income Income Taxes Cash Flow † Year Cash Flow Depreciation (a) − (b) −0.21(c) (a) + (d) 0 −$25,000 −$25,000 * $5250 −$19,750 1 8,000
conclude that help systems should strive todetect as many one-off errors as possible and provide hints for those (the list may be huge), andthat students struggling for more than some period of time should have a way to get quick help.We intend to make use of these finding to improve our own teaching and content, and to begindeveloping an automated help system for coding homework problems.References[1] Beaubouef, T. & Mason, J. Why the high attrition rate for computer science students: somethoughts and observations. ACM SIGCSE Bulletin, ACM, 2005, 37, 103-106.[2] McCauley, R.; Fitzgerald, S.; Lewandowski, G.; Murphy, L.; Simon, B.; Thomas, L. &Zander, C. Debugging: a review of the literature from an educational perspective. ComputerScience
system setup is shown in Figure 5. Figure 5 (a) demonstrates front view of thehardware setup and consists of CLICK PLC, power supplies and relays. The inside view,provided in Figure 5 (b), shows all the solenoids controlling teach pendant keys and wiringapproach with implementation of the terminal blocks. The description of all the PLC outputconnections with all the teach pendant keys via actuators on middle plate is shown in Table 2.Figure 5: (a) The outer layer of remote robot which consists of CLICK PLC, Din Rail and itscover, 2 Power Supplies, 3 Relays and a sheet of glass to provide the protection, (b) The innerlayer of the remote robot which shows all the actuators attached and wired up to the terminalblocks on the left which is connected
balanced to prevent overrepresentation ofstudents from a single high school or program to reflect the demographics of New York City.Students typically had a grade point average of 87-93 out of 100. Scholarships were providedbased on family income after the student was accepted.Survey LogisticsAn entry (presurvey) and exit (postsurvey) questionnaire pair for 2018 was designed to evaluatestudent development through the use of Likert scale, checkbox, and open-ended questions,approved by the Cooper Union Institutional Review Board. The questions and selectableresponses to the presurvey are recorded in Appendix B, while those to the postsurvey arerecorded in Appendix C. Participants were students in the summer STEM program, with studentand parent
] Criteria for Accrediting Engineering Programs. Accreditation Board for Engineering and Technology (ABET), November 24, 2018.[3] B. Harding and P. McPherson, “What do employers want in terms of employee knowledge of technical standards and the process of standardization?,” in Proceedings of the 2010 ASEE Annual Conference & Exposition, Louisville, KY, USA, 2010, pp. 15.1364.1 – 15.1364.10. [4] D. Purcell, “Report on a survey of schools of engineering in the United States concerning standards education,” The Center for Global Standards Analysis, Spring 2004.[5] H. de Vries and T. Egyedi, “Education about standardization: Recent findings,” International Journal of IT Standards and Standardization Research, vol. 5, no. 2, pp. 11
The Effects of a First Year Engineering Class Using the SCALE-Up Method on Student Retention and Subsequent Student Pass Rates David Ewing The University of Texas at Arlington 416 Yates Street, Arlington, TX, 76019, USA E-mail: david.ewing@uta.edu Abstract method, originally developed at NC State [1] and utilized in Due to the increased demand for engineers, the many universities [2], relies on creating a highly active andUniversity of Texas at Arlington (UTA) created a new, first
Based Learning and Authentic Assessment in Digital Pedagogy: Embracing the Role of Collaborative Communities”. The Electronic Journal of e- Learning, 13(2), 68-83.Costa, A., & Kallick, B. (2008). Learning and Leading with Habits of Mind: 16 Essential Characteristics for Success. Alexandria: Association for Supervision & Curriculum Development.Harper, K., Baker, G. R., & Grzybowski, D. M. (2013). First Steps in Strengthening the Connections Between Mathematics and Engineering. PEER. Atlanta: American Society for Engineering Education.Holmegaard, H. T., Madsen, L. M., & Ulriksen, L. (2016). Where is the engineering I applied for? A longitudinal study of students’ transition into higher
careers in BME or other related fields. With a foundationin both the technical and social aspects of engineering, our hope is that the engineers graduatingfrom our integrated engineering program will approach biomedical engineering with aconsideration for the necessary engineering principles as well as the end user of the product,service or diagnostic they develop. We strive to give our students a “Changemakers” mindset topositively impact communities, companies, and society when they graduate.References1. Yoder B. Engineering by the Numbers. Am Soc Eng Educ. 2017;11–47.2. Linsenmeier RA, Harris TR, Olds SA. The VaNTH Bioengineering Curriculum Project. Proc Second Jt EMBS/BMES Conf. 2002;2644–5.3. Linsenmeier RA. What makes a biomedical
to Jacobson’s committee’sdeliberations. There is no clear recollection of how the group moved from here to the first set ofa-k learning, or “program” outcomes as it was originally called [32]. Criterion 3. Program Outcomes and Assessment Engineering programs must demonstrate that their graduates have: (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 (d) an ability to function on multi-disciplinary teams (e) an ability to identify, formulate, and solve engineering problems (f) an
Ebrahimzadeh a, Nick Safai b Department of Engineering, Des Moines Area Community College, Ankeny, IA 50023, USA b Engineering Department, Salt Lake Community College, Salt Lake City, UT 84123 USAAbstractMost freshmen engineering majors have very little or no background in programming. In the firstyear of college, they learn the basics of programming, so they can apply their computing skills forfuture engineering courses. Different schools use different programming languages, such asMATLAB, Visual Basic, C++, and Python for their engineering curriculum. However, Python isthe only one that is open source. Additionally, the language versatility, online community of users,and powerful analysis packages such as Numpy and Scipy have made this free
Paper ID #25480Board 20: Engagement in Practice: First Year Students as ”Engineer for aDay” for Middle School StudentsDr. Cynthia Helen Carlson PE, PhD, Merrimack College Dr. Carlson worked as a water resources engineer for 10 years prior to earning her doctorate, contributing to improved water management in communities within the United States, Middle East, and Singapore. She has been a licensed Professional Engineer (PE) since 2002. Dr. Carlson’s research interests are broadly characterized as ’how civil engineering impacts public health’, and include storm water man- agement, modeling environment/engineering/social
and none Analysis engineering standards,” in 2015 ASEE Annu. Conf. Expo., 2015.. https://doi.org/10.18260/p.24218. [7] G. E. Okudan and B. Osif, “Effect of guided research Effective Design experience on product design performance: A pilot study,” J. Project Eng. Educ., vol. 94, no. 2, pp. 255–262, 2005. Grades [8] B. Otis and L. Whang, “Effect of library instruction on Effective Citation undergraduate electrical engineering design projects,” in 2007 Analysis ASEE Annu. Conf. Expo., 2007. https://peer.asee.org/2620. [9] M. Phillips, S. Lucchesi, J. Sams, and P. J. van Susante, Effective
Research Experiences for Teachers (RET) site? Three perspectives on Big Data and Data Science Stephanie B. Philipp, Olfa Nasraoui, and Jason Immekus University of Louisville College of Education and Human Development & J.B. Speed School of Engineering Louisville, KY 40292 stephanie.philipp@louisville.edu olfa.nasraoui@gmail.edu jason.immekus@louisville.eduAbstractThis paper will share initial findings from the first year of a Research Experience for Teacherssite, supporting nine secondary STEM teachers from diverse schools in six-week
systems selected are (Figure 1): garbage compactor [11], and b)punching press. These are relatively commonplace and simple systems that students will be ableto relate to their operation, and more important to be able to have good discussion aboutcapabilities, specifications, options, and provides opportunity for potential improvements of thesystems. (a) garbage compactor (b) punching press Figure 1. Systems used for development of materials on fluid power.The corresponding hydraulic systems to be used as the base for the materials and furtherdevelopment are the ones shown below in Figure 2. In these systems, the important takeaway isthat they have the basic components and there is some type of
engineering education. Kitana is an active member of the American Institute of Chemical Engineers (AIChE) at WSU, and serves as their Graduate Student Chair for the 2018-19 academic year.David B. Thiessen, Washington State University David B.Thiessen received his Ph.D. in Chemical Engineering from the University of Colorado in 1992 and has been at Washington State University since 1994. His research interests include fluid physics, acoustics, and engineering education.Prof. Bernard J. Van Wie, Washington State University Prof. Bernard J. Van Wie received his B.S., M.S. and Ph.D., and did his postdoctoral work at the University of Oklahoma where he also taught as a visiting lecturer. He has been on the Washington State
, we briefly review how design methodologies can be categorized by three dis-tinct conceptions of logic. In so doing we also intend to portray some of the common narratives onrationality of engineering and design.2.1 Classical logicThe first category of design methodologies are those committed to three axioms of classical logic,namely, a. the law of identity which states everything is identical to itself, b. the law of contradiction (or non-contradiction) which states that contra- dictions are not acceptable, c. and the law of excluded middle which states if a proposition is not true its negation must be true.In the following we first review two major developments in this domain
Paper ID #26372Mandatory but not Required: Examining Change in the Year Two Imple-mentation of a Novel Engineering Mathematics CourseDr. Janet Y. Tsai, University of Colorado, Boulder Janet Y. Tsai is a researcher and instructor in the College of Engineering and Applied Science at the University of Colorado Boulder. Her research focuses on ways to encourage more students, especially women and those from nontraditional demographic groups, to pursue interests in the eld of engineering. Janet assists in recruitment and retention efforts locally, nationally, and internationally, hoping to broaden the image of engineering
in and Earning a STEM Degree: An Analysis of Students Attending a Hispanic Serving Institution," American Educational Research Journal, vol. 46, pp. 924-942, 2009.[4] S. Hurtado, C. B. Newman, M. C. Tran, and M. J. Chang, "Improving the rate of success for underrepresented racial minorities in STEM fields: Insights from a national project," New Directions for Institutional Research, vol. 2010, pp. 5-15, 2010.[5] L. Perna, V. Lundy-Wagner, N. D. Drezner, M. Gasman, S. Yoon, E. Bose, et al., "The Contribution of HBCUS to the Preparation of African American Women for Stem Careers: A Case Study," Research in Higher Education, vol. 50, pp. 1-23, February 01 2009.[6] A. Byars-Winston, Y. Estrada, C. Howard, D. Davis, and J. Zalapa
action research brings together multiple disciplines and stakeholders whocollaboratively aim to simultaneously investigate and ameliorate real-world problems, to act incommunity and institutional settings, and actively monitor whether that action is achievingdesired goals, is sustainable, and is not producing new problems. Pohl and Hadron [16] definetransdisciplinary research as research that “deals with problem fields … in such a way that it can:(a) grasp the complexity... of problems, (b) take into account the diversity … of life-world …and scientific perceptions of problems, (c) link abstract and case-specific knowledge, and (d)develop knowledge and practices that promote what is perceived to be the common good” [pp.431-32]. Perrin [17] notes
disciplines at a large southwestern university. The project,funded by the Kern Family Foundation, began in fall of 2018 with the aim of institutionalizingthe entrepreneurial mindset (EM), improving and expanding evidence-based pedagogicalstrategies in capstone courses, and creating a faculty Community of Practice to share resourcesand best classroom practices.Sixteen capstone faculty from multiple engineering disciplines participated in three workshopsand three coaching sessions in the fall semester. The workshops promoted the EM andevidence-based pedagogical best practice and covered topics including: (a) ‘cultivatingcuriosity’ for opportunity recognition, (b) writing measurable student learning objectives, (c)‘making connections’ in the design
in engineering: Investigating variation across high schools comparing who could go versus who does go int,” in ASEE Annual Conference and Exposition, 2018.[13] J. Eccles, “Expectancies, values, and academic behaviors,” in Achievement and Achievement Motives, J. T. Spence, Ed. 1983, pp. 75–146.[14] A. Wigfield and J. S. Eccles, “Expectancy-value theory of achievement motivation,” Contemp. Educ. Psychol., vol. 25, pp. 68–81, 2000.[15] M. B. Miles, A. M. Huberman, and J. Saldana, “Chapter 4: Fundamentals of qualitative data analysis,” in Qualitative Data Analysis, 2013, pp. 69–103.[16] S. J. Tracy, “Qualitative quality: Eight ‘big-tent’ criteria for excellent qualitative research,” Qual. Inq., vol. 16, no. 10, pp