-1711533. 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.References[1] Paulson, D. R., & Faust, J. L. (1988). Active and Cooperative Learning. Los Angeles: California State University, Los Angeles. Retrieved from http://www.calstatela.edu/dept/chem/chem2/Active/index.htm[2] Prince, M. (2004). Does active learning work? A review of the research. Journal of Engineering Education, 93(3), 223-231.[3] Freeman, S., Eddy, S. L., McDonough, M., Smith, M. K., Okoroafor, N., Jordt, H., & Wenderoth, M. P. (2014). Active learning increases student performance in science, engineering, and mathematics
conclusions or recommendationsexpressed in this paper are those of the authors and do not necessarily reflect the views of theNational Science Foundation.References[1] Geometric Optics, PhET, Available at: https://phet.colorado.edu/en/simulation/geometric-optics [Accessed 5 Aug. 2017].[2] B. Alberts, “Prioritizing science education,” Science, vol. 328, pp.249-249, Apr. 2010.[3] I. E. Allen and J. Seaman, Class Difference$: Online Education in the United States. Babson Survey Research Group, 2010. Available: https://files.eric.ed.gov/fulltext/ED529952.pdf. [Accessed December 29, 2017][4] T. de Jong, M. Linn, and Z. Zachariam “Physical and virtual laboratories in science and engineering Education,” Science, vol. 340
, Oxnard College, Santa Barbara City College, and both the ComputerScience and Information Technology departments of CSUCI. One of the first areasdiscussed was that the curricula at the community colleges and the BSIT program havediverged. Reflective of this is the incoming students surprise at how few of theircommunity college courses are transferring as disciplinary credit. The primaryrecommendation from this review of the data is the recommendation that the feedercommunity colleges and CSUCI faculty assess curriculum realignment.All parties are enthusiastic and future meetings are planned to reassess the curriculaalignment in order to assist student progress in transfer and completion. It is noteworthyto look at why this is important and what
renewable resources, theprimary topic area of the REU. Data for the first two years of the program (10 students in 2016 and 9 in2017) are included in the analysis. In addition to the quantitative results from close-ended surveyquestions, the comments made by the students in response to open-ended questions, both in the focusgroup and on their surveys, provide additional insight into their reflections on the impact of the REU andtheir interest in the research topic and research in general.SatisfactionOverall, the students have been happy with the REU experience, and good post-site ratings for the firstyear became even better in the second year. These ratings are presented in Table 1. Students who gaverelatively lower ratings tended to be those who
differentiating factors like race, ethnicity and age can be thought of asthe future scope of this particular study.AcknowledgementThis material is supported by the National Science Foundation under DUE Grant Numbers1501952 and 1501938. Any opinions, findings, conclusions, or recommendations presented arethose of the authors and do not necessarily reflect the views of the National Science Foundation.References[1] Langdon, D., Mckittrick, G., Beede, D., Khan, B. & Doms, M., (2011). Stem: Good jobs now and for the future. Esa issue brief# 03-11. US Department of Commerce.[2] Carnevale, A.P., Smith, N. & Melton, M., (2011). Stem: Science technology engineering mathematics. Georgetown University Center on Education and the Workforce.[3
Qualitative Researchers, 2nd ed. Thousand Oaks: SAGE , 2012.[17] J. Walther, N. W. Sochacka, and N. Kellam, “Quality in Interpretive Engineering Education Research: Reflections on an Example Study,” J. Eng. Educ., vol. 102, no. 4, 2013.[18] L. K. Su, “Quantification of diversity in engineering higher education in the United States,” J. Women Minor. Sci. Eng., vol. 16, no. 2, 2010.[19] E. D. Tate and M. C. Linn, “How does identity shape the experiences of women of color engineering students?,” J. Sci. Educ. Technol., vol. 14, no. 5–6, pp. 483–493, 2005.[20] C. Hill, C. Corbett, and A. St Rose, Why So Few ? Women in science, technology, engineering and mathematics. Washington, DC: American Association of University Women
was supported with funding from the National Science Foundation. Any opinions,findings, and conclusions or recommendations expressed in this material are those of the authorsand do not necessarily reflect the views of the National Science Foundation.References[1] Arendale, D. (1997). SI (SI): Review of research concerning the effectiveness of SI from theUniversity of Missouri-Kansas City and other institutions from across the United States.[2] Dawson, P., van der Meer, J., Skalicky, J., & Cowley, K. (2014). “On the effectiveness of SI: Asystematic review of SI and peer-assisted study sessions literature between 2001 and 2010” Review ofEducational Research, 84 (4), 609–639.[3] Scott Steinbrink, Karinna M. Vernaza, Barry J. Brinkman
was above 4.0/5.0 across all topics in both manufacturingexcellence session and manufacturing quality excellence session [25]. That being said, averagescore for the non-destructive evaluation (NDE) module in Manufacturing Quality Excellencesession was slightly lower (approximately 3.75/5.0) than those for other modules. The lowerscore for NDE could be explained due to the larger amount and more technical nature of thelearning materials as reflected in the participant’s open-ended comments. In overall, the higherthan target (3.5/5.0) course evaluation scores demonstrated that the professional developmentsessions were able to meet course objectives in terms of renewing/enhancing participants’ HVMskills set.5. ConclusionsThe National Science
pertaining to female and minority hiring and participation. The unit of analysis is the transcript of each interview or focus group. Researchers will also calculate the extent of match between AM educators’ perceptions and AM standards/certifications as well as use established instruments to measure the extent to which the new professionals report entrepreneurial and intrapreneurial intentions [27-29].Sampling NoteRural NW Florida is highly diverse, with over 30% of residents reporting that they are black,Hispanic, or of multiple races; the enrollments of the participating state colleges reflect theircommunities. Because an intent of this project is to increase participation in AM education andcareers, the research team will reach out to
-Fitzpatrick and G. D. Hoople, “Cultivating an Entrepreneurial Mindset: An Interdisciplinary Approach Using Drones,” Advances in Engineering Education, vol. 7, no. 3, 2019. www.advances.asee.org/wp-content/uploads/vol07/issue03/Papers/AEE-25- Hoople.pdf15 G. D. Hoople, A. Choi-Fitzpatrick, and E. Reddy, “Drones for Good: Interdisciplinary Project Based Learning Between Engineering and Peace Studies,” International Journal of Engineering Education, vol. 35, no. 5, pp. 1378-1391, 2019. https://www.ijee.ie/latestissues/Vol35-5/12_ijee3801.pdf16 E. Reddy, G. D. Hoople, and A. Choi-Fitzpatrick, “Interdisciplinarity in Practice: Reflections on Drones as a Classroom Boundary Object,” Journal of Engineering Studies, vol. 11
lower than expected correction rates,indicating the necessity to enhance undergraduate solid mechanics education. Considering overallperformance by category provides additional evidence with regards to the limited understandingamong students on the multi-scale nature of materials and linkages to observed mechanicalbehavior and properties, Figure 5 (f). The collected student data indicates that although most ofthe students were able to identify the meaning of each keyword and categorize them properly inthe “materials processing” category (77% of students correctly categorized the keywordsbelonging to “materials processing” category), the macro-scale mechanics parameter resultsindicate significant misconceptions as reflected by the observation
even further.AcknowledgementsThis material was supported by the National Science Foundation’s Research Experience forUndergraduate Education (REU) Program (Award no. 1263293). Any opinions, findings, andconclusions or recommendations expressed in this material are those of the author and do notnecessarily reflect the views of the National Science Foundation.Bibliography[1] https://www.nsf.gov/pubs/2013/nsf13542/nsf13542.pdf[2] Brownell, J.E., and Swaner, L.E.. Five High-Impact Practices: Research on Learning, Outcomes, Completion, and Quality; Chapter 4: "Undergraduate Research." Washington, DC: Association of American Colleges and Universities, 2010.[3] Crowe, M., and Brakke, D. "Assessing the Impact of Undergraduate-Research
skills. Students also learn to use Excel/Matlab for data analyses, plotting andstatistical methods.3.9 Ethics, Social and Environmental InjusticesOne of highlights of the project is the inclusion of progressive humanities and qualitative socialsciences. Students in teams are required to watch movies and documentaries that reflect onsocial/environmental injustices, breach of ethics along with gender biases in STEM fields, andsocial prejudices. Students also participate in debates that focus on public policy and arerequired to study the discussions and decisions of the Whitehouse Office of Science andTechnology Policy.3.10 WebsiteA website has been created for the Algae Grows the Future project to promote outreach andmake the project’s resource
improvement.AcknowledgementThis material is supported by the National Science Foundation under DUE Grant Numbers 1501952and 1501938. Any opinions, findings, conclusions, or recommendations presented are those of theauthors and do not necessarily reflect the views of the National Science Foundation.References[1] Wang, J., Fang, A. & Johnson, M., (2008). Enhancing and assessing life long learning skills through capstone projects. ASEE Annual Conference and Exposition, Conference Proceedings. Pittsburgh, PA, 2008-324.[2] Shuman, L.J., Besterfield-Sacre, M. & Mcgourty, J., (2005). The abet "professional skills" — can they be taught? Can they be assessed? Journal of Engineering Education, 94 (1), 41-55.[3] Earnest, J., (2005). Abet
or agreed that they had the chance toupdate the writing instructional materials for their courses during this workshop. This feelingwas reflected in Figure 2(a) which shows the response to the statement “I had the chance toupdate the writing instructional materials for my courses during today’s sessions”. “I learned how to generate dimensions for my rubric” “I had the chance to update the materials for my own course” Engineering Engineering English English (a) Generating rubric dimensions (b) Updating
. Walther, N. W. Sochacka, L. C. Benson, A. E. Bumbaco, N. Kellam, A. L. Pawley, and C. M. L. Phillips, “Qualitative research quality: A collaborative inquiry across multiple methodological perspectives,” Journal of Engineering Education, vol 106, no. 3, pp. 398-430, 2017.[57] J. Walther, N. W. Sochacka, and N. N. Kellam, “Quality in interpretive engineering education research: Reflections on an example study,” Journal of Engineering Education, vol 102, no. 4, pp. 626-659, 2013.
, andBiomimicry, participants were asked to reflect to what extent they felt prepared to teach K-12children maker-centered learning, innovator competencies, and biomimicry. Responses wererecorded on a Likert scale from 1 (no emphasis) to 5 (complete emphasis).For the scale Value of Maker-Centered Learning, Innovator Competencies, and Biomimicry,participants were prompted to identify the extent to which they see value in K-12 studentsengaging with 15 topics related to maker-centered learning, innovator competencies, andbiomimicry. Participant responses were recorded on a Likert scale from 1 (no value) to 5(complete value).For the scale Utility of Maker-Centered Learning, Innovator Competencies, and Biomimicry,participants were prompted to rate the
observers and how to provide collegial and useful feedback. Later in thesemester, after all members of a group have completed their observations, each group meets toprovide feedback to one another. Finally, each participant submits a reflection paper at the endof the semester. Eleven faculty (including three from Hillsborough Community College)participated during year three and thirteen more are set to participate in spring 2019. Participantsare provided a stipend of $500.(d) Training for graduate assistants in laboratory coursesPrior to the start of a fall semester, three to four days of training are provided to graduatestudents who are assisting in laboratory courses. The morning sessions are led by STEERpersonnel who model active learning
Paper ID #25278Board 34: Use of Big Data Analytics in a First Year Engineering ProjectDr. Kevin D. Dahm, Rowan University Kevin Dahm is a Professor of Chemical Engineering at Rowan University. He earned his BS from Worces- ter Polytechnic Institute (92) and his PhD from Massachusetts Institute of Technology (98). He has pub- lished two books, ”Fundamentals of Chemical Engineering Thermodynamics” and ”Interpreting Diffuse Reflectance and Transmittance.” He has also published papers on effective use of simulation in engineer- ing, teaching design and engineering economics, and assessment of student learning.Nidhal Carla
being answered affirmatively. So far, for addressing program elements in #2, students aremost satisfied when being given tours of energy businesses and buildings, and surveys are beingdeveloped to address the question thoroughly.Acknowledgement of SupportThis material is based upon work supported by the National Science Foundation under Grant No.1565068.DisclaimerAny 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.5. References[1] National Science Foundation, "NSF Scholarships in Science, Technology, Engineering, and Mathematics Program | NSF - National Science Foundation," 2018. [Online]. Available
typically represent the dominate groups inengineering programs.Future work will complete this study with the full data set and seek corrective action for thetroubling trend of intervention driving students away. Additionally, more tailored approach to eachmajor type may be necessary in order to prevent negative consequences of intervention.AcknowledgementsThis material is based upon work supported by the National Science Foundation under grant no.DUE-1431578. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the authors and do not necessarily reflect the views of the National ScienceFoundation.References[1] W. S. Swail, K. E. Redd and L. W. Perna, Retaining Minority Students in Higher Education: A
related to those. In spite of these constraints, there are plans to expandboth the number of participating institutions and research access to the dataset.Expansion strategy. New institutional partners will receive funding to provide and update data.As the database becomes larger in size, joining the MIDFIELD partnership becomes even moreattractive. Twenty institutions have signed letters of commitment to join MIDFIELD. Newinstitutions will be targeted to reflect variability in geographic region, institution size asdetermined by the number of engineering graduates per year, and institutional control (public orprivate). Institutions will also be targeted that have a high or low graduation rate for under-represented minorities – plans include
and surface N. 4. Angle factors are available in equation or graphic form in both publications cited in the Reference section. They must be determined from the area and local geometry of all the enclosing “panels” that are “seen” by the person whose comfort is being assessed. Angle Factor Charts and equations are shown in Figure 9. The equations apply to a small horizontal plane, whereas the charts (not shown) reflect the view of a rotated person represented by plane projections. 5. A site visit will be required to measure the window areas and a, b, and c view factor dimensions.bNecessary Assumptions: 1. The indoor glass surface temperature must be calculated or measured
12 38 African-American 7 5 12 Native-American 0 0 0 Other Ethnicity 10 3 13 Table 2. “Applied Value” survey results for fall semester 2014 and spring semester 2015 at four-year colleges.A total of 23,000 student-hours of microcontroller instruction was delivered at the college levelduring the 2014-15 academic year. The number of student-hours of instruction delivered at thefour-year level was double that delivered by community colleges and may reflect a greater abilityto apply the technology
DUE# 1400561 “Midwest PhotonicsEducation Center.”Any opinions, 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. http://www.light2015.org/Home/Event-Programme.html?tab=1. Accessed Jan. 11, 2016.2. http://www.aimphotonics.com/. Accessed Jan. 11, 2016.3. http://www.op-tec.org/index.php. Accessed Jan. 11, 2016.4. http://www.op-tec.org/resources/industry-demand-report. Accessed Jan. 30, 2016.5. http://www.mi-light.org. Accessed Jan. 11, 2016.
sociotechnical mindsets that our students can instill inengineering practice.References 1. Huff, J. L. (2014). Psychological journeys of engineering identity from school to the workplace: How students become engineers among other forms of self. Retrieved from ProQuest, UMI Dissertations Publishing (3669254). 2. Huff, J. L., Smith, J. A., Jesiek, B. K., Zoltowski, C. B., Graziano, W. G., & Oakes, W. C. (2014). From methods to methodology: Reflection on keeping the philosophical commitments of interpretative phenomenological analysis. Proceedings of the 2014 ASEE/IEEE Frontiers in Education Conference. October 2014, Madrid. 3. Huff, J. L., Jesiek, B. K., Zoltowski, C. B., Ramane, K. D., Graziano, W. G
from Worces- ter Polytechnic Institute (92) and his PhD from Massachusetts Institute of Technology (98). He has pub- lished two books, ”Fundamentals of Chemical Engineering Thermodynamics” and ”Interpreting Diffuse Reflectance and Transmittance.” He has also published papers on effective use of simulation in engineer- ing, teaching design and engineering economics, and assessment of student learning.Dr. Liang Hong, Tennessee State University Dr. Liang Hong received the B.S. and the M.S. degrees in Electrical Engineering from Southeast Univer- sity, Nanjing, China in 1994 and 1997, respectively, and the Ph.D. degree in Electrical Engineering from University of Missouri, Columbia, Missouri in 2002. Since August 2003
. Adams, R. S.; Turns, J.; Atman, C. J., Educating effective engineering designers: The role of reflective practice. Design Studies 2003, 24 (3), 275-294.21. Bursic, K. M.; Atman, C. J., Information gathering: A critical step for quality in the design process. Quality Management Journal 1997, 4 (4), 60-75.22. Christiaans, H.; Dorst, K. H., Cognitive models in industrial design engineering: A protocol study. Design Theory and Methodology 1992, 42, 131-140.23. Crismond, D. P.; Adams, R. S., The informed design teaching and learning matrix. Journal of Engineering Education 2012, 101 (4), 738-797.24. Atman, C. J.; Bursic, K. M., Teaching engineering design: Can reading a textbook make a difference? Research in Engineering Design 1996
compensate for missing information and using it toconstruct the problem space5.Forster et al. have examined how different preparations, variations in goal setting, and alternativetask instructions impact performance6. By framing given design tasks in either a novel or afamiliar manner or by priming participants with reflection on novel or familiar events prior tocompleting a task, it was found that participants with less direct experience associated with agiven problem were more open to being primed in a particular manner. Chen et al. investigatedhow different facilitation effects correlate with the creative performance across differentcultures7. They tested Chinese college students and US college students by providing explicitinstructions to half
drawn are of particular interest, sincethese affect persistence studies in all disciplines.AcknowledgementsThis material is based upon work supported by the National Science Foundation (NSF) underGrant 1129383 in the Research on Engineering Education (REE) program. The opinionsexpressed in this article are those of the authors and do not necessarily reflect the views of NSF.References1 Lord, S. M., R. A. Layton, and M. W. Ohland, “Trajectories of Electrical Engineering and Computer Engineering Students by Race and Gender,” IEEE Transactions on Education, 54(4), 610-618 (2011).2 Orr, M. K., S. M. Lord, R. A. Layton, and M. W. Ohland, “Student Demographics and Outcomes in Mechanical Engineering in the U.S.,” International Journal of