Foundation (NSF) grant 1836504. Anyopinions, findings and conclusions or recommendations expressed in this material do notnecessarily reflect those of NSF.Bibliography[1] B. Momo, G. D. Hoople, D. A. Chen, J. A. Mejia, and S. M. Lord, “Broadening the engineering canon: How Culturally Responsive Pedagogies can help educate the engineers of the future,” Murmurations Emerg. Equity Educ, vol. 2, pp. 6–21, 2020.[2] J. A. Leydens and J. C. Lucena, Engineering Justice: Transforming Engineering Education and Practice. John Wiley & Sons, 2017.[3] G. D. Hoople, D. A. Chen, S. M. Lord, L. A. Gelles, F. Bilow, and J. A. Mejia, “An Integrated Approach to Energy Education in Engineering,” Sustain. Sci. Pract. Policy, vol. 12, no. 21, p. 9145
under Grant No.1759314 (Binghamton University) and Grant No. 1759259 (Indiana University). Any opinions,findings, and conclusions or recommendations expressed in this material are those of theauthor(s) and do not necessarily reflect the views of the National Science Foundation.References[1] Dotterer, A. M. (2021). Parent involvement, expectancy values, and STEM outcomes among underrepresented adolescents. Social Psychology of Education, 1-15.[2] James, A. G., Rudy, D., & Dotterer, A. (2019). Longitudinal examination of relations between school-and home-based parent involvement and GPA across ethnic groups. Journal of Child and Family Studies, 28(11), 3000-3010.[3] Simpkins, S. D., Davis-Kean, P. E., & Eccles, J. S. (2005
quantitative scores ofare helpful for identifying leadership while individual comments are beneficial for identifyingpotential conflicts. Based on the feedback from CATME, the instructor could apply a variety ofinterventions to prevent further development of conflicts. The inventions include one-on-onevirtual or in-person meetings, group meetings, redistributing of team tasks, and shifting groupactivity to a more agreeable time slot.References[1] S. Akbar, E. Gehringer, and Z. Hu, “Poster: Improving formation of student teams: A clustering approach,” in IEEE/ACM 40th International Conference on Software Engineering: Companion (ICSE-Companion), 2018: IEEE, pp. 147-148.[2] A. Rezvani, R. Barrett, and P. Khosravi, “Investigating the
development efforts, and served in several administrative roles. She has been recognized for her teaching, advising, service, and research and as an Exemplary Faculty Member for Excellence in Diversity, Equity, and Inclusion. ©American Society for Engineering Education, 2023 Evolution of a Student Transition and Success Program Reflections on a 10 Year JourneyAbstractA lot has happened since 2012 – in society, in education, and in one engineering studentdevelopment program, called The Academy of Engineering Success (AcES)! AcES started in2012 at West Virginia University (WVU), a large, mid-Atlantic, R1 institution, and receivedNSF S-STEM funding beginning in 2016 and corporate
Presentations 2. Somewhat disagree receiving/providing feedback on Feedback Likert Scale 3. Somewhat agree presentations 4. Strongly agree guidance from faculty mentor(s) Faculty guidance from capstone instructor Instructor guidance from industry mentor(s) Industry guidance from capstone TAs TA participating in TA-led mixers Mixers This capstone experience has helped me learn what I had hoped to
workshops(e.g., NETI, ASEE section meetings, the ASEE National meeting, CW workshops), and haverecruited six participants in our Action Research Fellows program. By studying the context inwhich instructors adopt and utilize the CW, we will be able to provide recommendations forencouraging use of the CW and of other pedagogical innovations.AcknowledgmentsWe acknowledge the support from National Science Foundation (NSF) through grants DUE1821439, 1821445, 1821638, 1820888, and 1821603. Any opinions, findings, and conclusions orrecommendations expressed are those of the authors and do not necessarily reflect the views ofthe NSF.References[1] S. Freeman, S. L. Eddy, M. McDonough, M. K. Smith, N. Okoroafor, H. Jordt, and M. P. Wenderoth, “Active
. She received undergraduate and graduate degrees in mechanical engineering from Duke and NC State, respectively. Her research interests include engineering education and precision manufacturing. American c Society for Engineering Education, 2021 Use of Personas in Rating Scholarship ApplicationsIntroductionThis evidence-based practice paper introduces a method for creating subjective, holistic rubricsbased on the human-centered design concept of personas. It can be difficult to align assessmentmetrics with subjective artifacts, especially when the goal of the artifact itself is subjective. Thefaculty team who collaborated on an NSF S-STEM project faced
important. You are required to use data sets to find correlationsbetween independent and dependent variables and trends including identifying outliers.” Anotheraerospace engineer described how “We use a lot of relationship analysis - sequential, regression,year over year(s) and yes, there are a lot of cross-relationships.” We were surprised by thesestatements that described an ability to analyze data, given that the bulk of the College Algebracourse involves learning how to use and manipulate these formal expressions, learning skills likefactoring, simplifying, solving, and interpreting parameters. We also found that these trends forengineers followed trends we saw in our larger sample where we interviewed professionals fromacross STEM fields.This
and instructor expecta.tions. 2. Representation and interpretation of time functions. 3. Logarithmic relationships. 4. Plots for Characterization of physical phenomena. 5. Resistance: Static and Dynamic. 6. Kirchoff's voltage law, Kirchoff's current law, Ohm 1 s law. 7. Elementary resistive network analysis. 8. Power and energy. 9. Review. 10. Hour Examination. 11. The binary number system. Conversion between bases, 2 s complements. 1 12. Logic networks with gates. Logical functions. 13. Analysis of combinational logic networks via truth tables. 14. From logic diagrams to printed circuit layout. 15
understandably different, no one coursewill be satisfactory and hence a number of course proposalshave been suggested and implemented at many institutions (1,2] • In contrast to other groups of engineers, who may be in-terested only in the application of microprocessors, elec-trical engineers are expected to know all aspects of micro-processors, namely, hardware, software and applications.They should understand the theory as well as the practice ofmicroprocessor engineering. At least one course should beincluded in existing electrical engineering curricula tocover the above topics. This poses a difficult problem forelectrical engineering departments. They must develop asuitable place in electrical engineering curricula where thecourse(s
containing only conventionalnumerical calculation type questions.Introduction Learning is a constructive process in which new knowledge builds upon priorknowledge.1, 2 It is for this reason that there is increased interest in inductive instructionalmethods like inquiry-based learning, problem-based learning, and just-in-time teaching to namea few. A common feature of these inductive methods is that questions or problems form thecontext for learning.3 Thus, formative assessments based on questions/problems can play afundamentally important role in student learning. The degree to which homework/activity questions impact student learning can beevaluated by considering them relative to Bloom s taxonom . In order of increasing
ca a c a a afrequency. Proceedings of the 2011 North Midwest Section ConferenceT a d db = s/N, as mentioned earlier. As can be seen,a higher sampling frequency lowers the resolution of the frequency domain representation of thesignal, but a higher sample size increases the resolution. When applied to musical notes, thislinear distribution of discrete frequencies is important because musical notes do not distributethemselves at equal intervals. Musical notes are typically denoted A, B, C, D, E, F, or G. Thisrepresents one octave of notes and there are several octaves within human hearing range. Theoctave a note is in is generally
.[3] "Standards-Based Grading Overview," Active Grade, 2012.[4] S. Ambrose, M. Bridges, M. DiPietro, M. Lovett and M. Norman, HHow Learning Works: 7 Research Based Principles for Smart Teaching, San Franscisco: Wiley, 2010.[5] M. Townsley, "What is the Difference between Standards-Based Grading (or Reporting) and Competency-Based Education," Competency Works, 11 November 2014. [Online]. Available: https://www.competencyworks.org/analysis/what-is-the-difference-between- standards-based-grading/. [Accessed 30 12 2019].[6] L. Davis, "Standards-Based Grading: What to Know in 2019," Schoology Exchange, 13 2 2019. [Online]. Available: https://www.schoology.com/blog/standards-based-grading. [Accessed 15 12 2019
degree of humanness and proactivity in our chatbotdesign, in addition to its ethical dimensions. Currently, course information is uploaded to thechatbot in a semi-automated manner, implementing a fully automated process can be moreproductive and easier for educators and admin users. To improve our chatbot, a new feature willbe added allowing students to provide their feedback on chatbot responses based on relevancy.This will allow us to measure how much student inquiries were successfully resolved.References[1] D. C. Brooks and J. Pomerantz, “ECAR Study of Undergraduate Students and Information Technology, 2017,” p. 41, 2017.[2] S. Adams Becker, M. Cummins, A. Davis, A. Freeman, C. Hall Giesinger, and V. Ananthanarayanan, NMC Horizon
Computing, MIT Press, Cambridge. 9. Varma, R., 2002, “Women in Information Technology: A Case Study of Undergraduate Students in a Minority-Serving Institution”, Bulletin of Science, Technology & Society, Vol. 22, pp. 274-282. 10. Beyer, S., Rynes, K., Haller, S., 2004, “Deterrents to Women Taking Computer Science Courses”, IEEE Society and Technology, Vol. 23, pp. 21-28. 11. Irani, L., 2004, “Understanding Gender and Confidence in CS Course Culture: An Alternative to Big O Notation”, ACM SIGCSE Bulletin, Vol. 36, pp. 195-199. 12. Varma, R., 2007, “Women in Computing: The Role of Geek Culture”, Science as Culture, Vol. 16, pp. 359-376. 13. Varma, R., 2007, “Decoding the Female Exodus from Computing
= 1, 2, 3,….,N, where N isthe parameter form calculated byN 2m 1. Finding N is required in order to compute theperiodogram and Fisher test. In addition, we take our deterministic random phase θ in the interval[-π,π]. The problem of detecting the periodical components in a time series (described in (2)) isequivalent to the problem of detecting peaks in a periodogram in2,9.We focus in detecting aperiodicity from (2) in frequency domain and the periodogram that is coordinated at Fourier in9.In spectral analysis, therefore, we take ∆t as sampling time, and we convert it in to frequency bycalculating Nyquist frequency f which is going to observe in frequency domain as double sideband with the interval S f , f from1-2 which can be defined
show typical Mossbauer spectra of iron film prepared by spin coating and sol-gel method respectively. The Mossbauer spectrum of samples prepared by spin coating can befitted with two Lorenzian doublets. This indicates presence of two different forms of iron. Theisomer shift,0.53 m/s relative to iron foil spectrum, and quadrupole splitting, 0.8 mm/s, of line Bagree with octahedrally co-ordinated Fe3+. However, line A shows very little isomer shift, 0.04mm/s relative to iron foil spectrum, and quadrupole splitting of 1.3 mm/s. The isomer shift ofline A is compatible with Fe0 but presence of quadrupole splitting indicates non-symettricelectron density at the site of iron nuclei. But the intensity of line A is significantly lowcompared to line B
, & ones skills, resources and abilities allocating resources prior to learning Information Management – processing information efficiently Procedural – knowledge about how Monitoring – assessment of one s to implement a learning procedure learning or strategy use Debugging – correcting performance errors Conditional – knowledge about
the authors, and the Commission cannot be heldresponsible for any use which may be made of the information contained therein.7. References[1] S. Swarat, P. H. Oliver, L. Tran, J. G. Childers, B. Tiwari, and J. L. Babcock, “How Disciplinary Differences Shape Student Learning Outcome Assessment,” AERA Open, vol. 3, no. 1, p. 233285841769011, 2017.[2] G. W. G. Bendermacher, M. G. A. oude Egbrink, I. H. A. P. Wolfhagen, and D. H. J. M. Dolmans, “Unravelling quality culture in higher education: a realist review,” High. Educ., vol. 73, no. 1, pp. 39–60, 2017.[3] B. J. Harper and L. R. Lattuca, “Tightening Curricular Connections: CQI and Effective Curriculum Planning,” Res. High. Educ., vol. 51, pp. 505–527, 2010.[4
required totake. Additionally, at these institutions, graduate students have served as instructors of record.They will be invited to participate in the study as well. We also plan to collect data from thestudents of these first-year programs using an exploratory survey. The questions on the survey willseek to gather information about students’ initial interest in engineering prior to enrolling in theirrespective institutions, their general perception of the first year courses they have just completed,what their intended majors are, what types of activities they engaged in during their first yearcourse and if/how these activities fueled or increased their desire to continue to pursue theirengineering degrees.References[1] S. L. Christenson, A. L
Science Foundation (NSF) GraduateResearch Fellowship. Any opinions, findings, and conclusions or recommendations expressed inthis material are those of the author(s) and do not necessarily reflect the views of the NSF.References:[1] P. J. Denning, “Viewpoint Remaining Trouble Spots with Computational Thinking,” pp. 33–39, 2016.[2] U. Ilic, H. I. Haseski, and U. Tugtekin, “Publication Trends Over 10 Years of ComputationalThinking Research,” Contemp. Educ. Technol., vol. 9, no. 2, pp. 131–153, 2018.[3] C. Concepts, A Framework for K-12 Science Education. 2012.[4] J. M. Wing, “Computational Thinking : What and Why ?,” no. November, pp. 1–6, 2010.[5] T. T. Yuen and K. A. Robbins, “A Qualitative Study of Students’ Computational ThinkingSkills in a
student who participated is currently pursuing a research project underthe supervision of Dr. Freeborn and Dr. Gosa to investigate surface electromyography tocharacterize swallowing behavior.References[1] American Speech-Language-Hearing Association, “Scope of practice in speech-language pathology,” Communication Disorders Quarterly, 2007. [Online]. Available: www.asha.org./policy.[2] M. O’Keefe, T. Burgess, S. McAllister, and I. Stupans, “Twelve tips for supporting student learning in multidisciplinary clinical placements,” Medical Teacher, vol. 34, no. 11, pp. 883–7, 2012. doi:10.3109/0142159X.2012.700431[3] D. M. Shafran, L. Richardson, M. Bonta, “A novel interprofessional shadowing initiative for senior medical
Work-in-Progress: Research Plan for Introducing Problem Solving Skills through Activities to an Introductory Computer Science Course Stephany Coffman-Wolph, Kimberlyn Gray, and Marcia Pool Department of Computer Science, The University of Texas at Austin 2317 Speedway, Austin, TX, 78712, USA E-mail: sscw@cs.utexas.edu Department of Chemical Engineering, West Virginia University Institute of Technology 512 S Kanawha St, Beckley, WV, 25801, USA E-mail: Kimberlyn.Gray@mail.wvu.edu Department of Bioengineering, University of Illinois at
environment and provide industrial and educational outreach to neighboringcolleges. Allowing students access to state of the art technology gives them an advantage inproduct development and manufacturing. This boosts interest in academic and personalentrepreneurial projects while at the same time offers exposure to multiple fields of study. Page 12.1186.2The CPIC currently houses two fully-functional RP machines. One is Z-Corp.’s Spectrum Z510color system which uses a gypsum-based powder and liquid binder. This machine is the focalpoint for current experimentation. The center offers students hands-on experience withtechnology that is becoming as
, and microcomputers to the building, testing, operation and maintenance of electrical/electronic(s) systems. (ABET 8.a) The application of physics or chemistry to electrical/electronic(s) circuits in a rigorous Outcome 13 mathematical environment at or above the level of algebra and trigonometry. (ABET 8.b) The ability to analyze, design and implement control systems, instrumentation systems, Outcome 14 communication systems, power systems, or hardware and software computer systems. (ABET 8.c) The ability to apply project management techniques to electrical/electronic(s)/computer Outcome 15 systems. (ABET 8.d
, Sweden, Chapman & Hall, 1997.[2] J. St-Pierre, D. P. Wilkinson, S. Knights and M. Bos, “Relationships between watermanagement, contamination and lifetime degradation in PEFC,” Journal of New Materials forElectrochemical Systems, Volume (3), 99-106, 2000.[3] T. J. P. Freire and E. R. Gonzalez, “Effect of membrane characteristics and humidificationconditions on the impedance response of polymer electrolyte fuel cells,” Journal ofElectroanalytical Chemistry, Volume (503), 57-68, 2001.[4] D. Chu and R. Z. Jiang, “Performance of polymer electrolyte membrane fuel cell (PEMFC)stacks part I, evaluation and simulation of an air-breathing PEMFC stack,” Journal of Power
modeling. The paper highlights the experience inhandling the undergraduate students for research participation and presents students’ experienceworking in nuclear engineering program. The undergraduate participation in research providedunique opportunity in recruiting students in the nuclear engineering program for graduateprogram.IntroductionSince the beginning of the nuclear industry, early 1960s, chemical engineering has been asignificant discipline within the U. S. nuclear industry1. Traditionally the chemical engineershave made and now continue to make significant contribution in the areas of fuel fabrication,isotope separation, fuel reprocessing, and waste management. Chemical engineers monitor thechemistry of the coolant and cleanup systems
procedure with variable time step size adjuster. The time step size isvaried between 10-4 second and 10-6 second, such that convergence is achieved. Page 13.1115.6The following numerical values are used in the numerical computationsMx = 90kg, My = 120kg,Kx = 108 N/m, Ky = 108 N/m,Cx = 1900 N-s/m, and Cy = 2200N-s/mThe above damping values are based on a damping ratio of 1% of the critical dampingcalculated from the stiffness data. The mass and stiffness values correspond to that of atypical CNC machine. The stiffness values correspond to those of the lead screwsdriving the two tables. These values may vary somewhat from the nominal values, butfor this
these various use cases unless otherwise disallowed by the assignedprivileges. See main menu options below.The AdministratorThe administrator will assign roles to new user accounts, but can also create customized roles byassigning a customized set of use cases to a user. S/he can also assign the new user to adepartment and course code prefix. A less frequent activity of the administrator is to edit thereference tables which are used to fill the department names, program names, program-department associations, course code department prefix, list of program outcomes, and others.When deploying a new installation of Unisyllabus the administrator will spend some timesetting-up the reference tables but afterwards his/her role is mostly limited to
presentations.BackgroundThis laboratory is designed to be completed in a two-hour laboratory session for thosesuccessfully completing pre-laboratory exercises. While a number of RF simulation packagesmay be used to perform the listed simulations, the real-time tuning capabilities of Microwave Page 14.38.2Office provide for a high degree of interactivity which is a primary component of thisexperiment. Minimal equipment requirements include a RF frequency generator and a spectrumanalyzer; however, the use of a vector network analyzer with s-parameter capabilities providesadditional opportunities to reinforce concepts demonstrated in the design and simulation phasesof this