instructors to enhance the quality of language and literacy socialization in their midst and toaccommodate and support newcomers—from all language backgrounds—within these discoursecommunities more satisfactorily and seamlessly as well (pp. 186-187)”. Indeed, the implicationsof these findings for changes in support programs, institutional policies, and pedagogicalpractices can offer the field a more thorough perspective into the intricate and dynamic nature ofacademic discourse socialization and how institutions of higher education can better serveinternational graduate students.References[1] C.P. Casanave, Writing Games: Multicultural Case Studies of Academic Literacy Practices in Higher Education, Mahwah, NJ: Erlbaum, 2002.[2] S.A. Myers, S
Paper ID #22466Promoting Academic and Career Success for Raleigh Future Scholars at NCState UniversityProf. Leda Lunardi, North Carolina State University Leda Lunardi received the BS and MS from University of S˜ao Paulo (USP), S˜ao Paulo, Brazil, and Ph.D. degree from Cornell University. Currently she is a professor in the Electrical and Computer Engineering Department at North Carolina State University in Raleigh. Her teaching and research interests include electronics, optoelectronics, and engineering undergraduate student retention and graduation improve- ment. Her research has been mainly sponsored by the National
; Wijnberg, N. M. (2017). The interplay between intuition and rationality in strategic decision making: A paradox perspective. Organization Studies, 38(2), 225-261.14. Cosier, R. A., & Aplin, J. C. (1982). Intuition and decision making: Some empirical evidence. Psychological Reports, 51(1), 275-281. doi:10.2466/pr0.1982.51.1.27515. Crismond, D. P., & Adams, R. S. (2012). The informed design teaching and learning matrix. Journal of Engineering Education, 101(4), 738-797.16. Dane, E., & Pratt, M. G. (2007). Exploring intuition and its role in managerial decision making. The Academy of Management Review, 32(1), 33-54. doi:10.2307/2015927917. Dhami, M. K., & Thomson, M. E. (2012). On the relevance of
Paper ID #19719Implementation of a Master’s in Translational Medicine (MTM) Program atThe City College of New York (Work in Progress)Mr. Jeffrey Stock Garanich Ph.D., The City College of New York Jeffrey S. Garanich, Ph.D. is Director of the Master’s in Translational Medicine (MTM) Program at the City College of New York (CCNY). In this role, his primary responsibilities include leading recruiting efforts to expand the Program’s student base, engaging medical technology industry partners, and manag- ing administration of a curriculum that trains students from diverse educational backgrounds in the core competencies
subsequently received travel funding to present their work at the ArizonaStudent Energy Conference in Flagstaff, AZ, September 15-16, 2016. Others presented at theCrystalline Silicon Solar Cells and Modules: Materials and Processes held in Vail, CO. References1. Smalley, R. E. (2005). Future global energy prosperity: The Terawatt Challenge. MRS Bulletin, 30, 412-417. Available at http://cohesion.rice.edu/NaturalSciences/Smalley/emplibrary/120204%20MRS%20Boston.p df2. Pickett, G., Bowden, S. Husman, J., Ross, K. Shell, D. F., and Nelson, K. G. (2013, June). Student-led solar cell fabrication pilot line: Engaging the next generation of PV engineers. In IEEE 39th Photovoltaic Specialists Conference
of the FTP, time orientation of the FTP, etc. with less focus on the context.When context-specific items such as those related to perceived instrumentality are removed, amore accurate characterization of students’ FTP type may be realized from quantitative data.An additional outcome of the work is a novel research method for the study of how FTP isconnected to SRL for engineering students. In particular, during the second interview, a card sortmethod was used to elicit a list of the student’s goals, the order of these goals, goals related toSRL, and other aspects of FTP. Students and/or the interviewer(s) wrote on index cards all thegoals that the student mentioned. The student was then instructed to organize the goals into apath
Librarianship, 36, 6, 539–542.11. J.J. Farrell, R.S. Moog, J.N. Spencer. 1999. A guided-inquiry general chemistry course. Journal of Chemical Education, 76, 4, 570.12. S.E. Lewis, J.E. Lewis. 2005. Departing from lectures: An evaluation of a peer-led guided inquiry alternative. Journal of Chemical Education, 82, 1, 135.13. H.H. Hu, T.D. Shepherd. 2013. Using POGIL to help students learn to program. ACM Transactions on Computing Education, 13, 3, 13:1-13:23.14. H.H. Hu, B. Avery. 2015. CS Principles with POGIL activities as a learning community. Journal of Computing Sciences in Colleges, 31, 2, 79-86.15. S. Kumar, C. Wallace. 2014. Instruction in software project communication through guided inquiry and reflection. In Proceedings of the
the National Science Foundation under Grant No.EEC-1359414. The authors would also like to thank the support from Texas A&M University-Kingsville.References:[1] Prince, M. J., Felder, R. M., & Brent, R. (2007). Does faculty research improve undergraduateteaching? An analysis of existing and potential synergies. Journal of Engineering Education,96(4), 283-294.[2] Hunter, A. B., Laursen, S. L., & Seymour, E. (2007). Becoming a scientist: The role ofundergraduate research in students' cognitive, personal, and professional development. Scienceeducation, 91(1), 36-74.[3] Seymour, E., Hunter, A. B., Laursen, S. L., & DeAntoni, T. (2004). Establishing the benefitsof research experiences for undergraduates in the sciences: First
Offers Encouragement, Support to Women in STEM." Group Offers Encouragement, Support to Women in STEM | UC Merced. University of California Merced, 2 Feb. 2016. Web. 23 Jan. 2017.5. "Female Stem Groups Summary." (n.d.): n. pag. 10 Mar. 2016. Web. 23 Jan. 2017.6. "Harvey Mudd Launches BRAID Initiative to Increase Diversity in Computer Science | Harvey Mudd College News." Harvey Mudd College. N.p., 24 Sept. 2014. Web. 23 Jan. 2017.7. National Science Board, National Science Foundation, National Center for Science and Engineering Statistics. "S&E Indicators 2016 | NSF - National Science Foundation." S&E Indicators 2016 | NSF - National Science Foundation. National Science Foundation, Jan
Manufacturing since 2010 and International Journal of Computational Materials Science and Surface Engineering since 2007.Dr. S. Hossein Mousavinezhad, Idaho State University is the principal investigator of the National Science Foundation’s research grant, National Wireless Re- search Collaboration Symposium 2014; he has published a book (with Dr. Hu of University of North Dakota) on mobile computing in 2013. Professor Mousavinezhad is an active member of IEEE and ASEE having chaired sessions in national and regional conferences. He has been an ABET Program Evaluator for Electrical Engineering and Computer Engineering as well as Engineering Education. He is Founding General Chair of the IEEE International Electro Information
).Learner’sperceptionsofacybersecuritycompetitionasitrelates toknowledge,skills,andabilities(KSA’s).PaperpresentedattheNICE(NationalInitiativefor CybersecurityEducation)Conference,SanDiego,CA.Justice,C.,&Do,L.(2012).ITexperientiallearning:TheLivingLab.PaperpresentedattheFrontiersin EducationConference(FIE),2012.Kelly,S.(2014).Dnsmasq.Retrievedfromhttp://www.thekelleys.org.uk/dnsmasq/doc.htmlTheNationalInitiativeforCybersecurityEducation(NICE).(2015).Retrievedfrom http://csrc.nist.gov/nice/framework/Newhouse,B.K.,Scribner,B.,&Witte,G.(2016).NICECybersecurityWorkforceFramework(NCWF). DraftNISTSpecialPublication800-181.Pearce,M.,Zeadally,S.,&Hunt,R.(2013).Virtualization:Issues,securitythreats,andsolutions.ACM ComputingSurveys(CSUR),45(2
follow-on course Intermediate Dynamics (but might be included at the end of a semestercourse that includes three-dimensional kinetics). Here, we discuss results from the Pulley IBLAand the Rolling Cylinder IBLA.Table 2. IBLAs and their targeted principles. IBLA Targeted principle(s)Pulley Particle Newton’s Second LawImpact Pendulum Particle Work and Energy; Impulse and MomentumSpools Relationships between (a) net force and linear acceleration; (b) net moment and angular acceleration; (c) linear and angular accelerationsRolling Cylinders Effect of mass distribution on rolling; Rigid body work and energy.Gyroscope Three-dimensional
-2 -1.5 -1 -0.5 0 0.5 1 1.5 2 Time (s) -5 x 10 Fig. 6. MATLAB simulation of a square pulse (Amplitude=2V, Pulse width= 0.1 µs). 2.5 2 Voltage (V) 1.5 1 0.5 0 -2 -1.5 -1 -0.5 0 0.5 1 1.5 2 Time (s) -5
relation to others’ expectations.Acknowledgment:This work was supported through funding by the National Science Foundation (NSF EEC 1752897). Anyopinions, 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. Lewis, H. B. (1971). Shame and guilt in neurosis. International Universities Press: New York. 2. Tangney, J. P., & Dearing, R. L. (2002). Shame and guilt. Guilford Press: New York. 3. Scheff, T. J. (2003). Shame in self and society. Symbolic interaction, 26(2), 239
lead to learning (formally or informally) and the development of newperspectives and ideas. Wenger’s ideas around communities of practice [27] which integratesocial learning theory and social constructivism, stem from this viewpoint. Wenger describescommunities of practice as a group of individuals, with a shared domain or area of interest, whoengage in collective learning to achieve a common goal [29]. This practice occurs withinhistorical and social contexts, and learning occurs within the community through socialconstructivism [27]. The Zone of Proximal Development, the distance between what a learnercan accomplish independently and what s/he can accomplish with help from peers [30], isutilized to push community members forward in their
practices in which stakeholder concernschanged actual engineering decisions and practices as exemplary CSR activities, rather thanthose that simply redistributed some of the economics earnings of industry to a broader array ofpeople. In so doing, we drew inspiration of Auld et al.’s distinction between “old” and “new”CSR, in which “old” CSR encompasses philanthropy (such as volunteering and charitabledonations like scholarships) and “new” CSR refers to activities that change core businesspractices to create social, economic, and environmental value for stakeholders as well ascompanies [4]. The question asking students to evaluate CSR practices as being excellent, okay,or not CSR therefore included a range of activities on the old to new scale, from
to 1950’s [1] researchers started to explore this technology. Simplyspeaking, computer vision deals with the technology that mimics the capabilitiesof a human (normal) vision system. Naturally, a normal human being is equippedwith sensors for five different sensing capabilities (vision, smell, taste, touch, andhear). These capabilities are controlled by the central nervous system (brain)allowing a human being to demonstrate intelligent behavior. By default, thevision system of a human being is three dimensional and it uses two eyes thatwork as sensors (detectors) to capture images. Earlier computer vision systemused only one camera along with the associated computational platform andsoftware and therefore, it dealt largely with two
semester of 2017, a local inventor (2nd author of this paper) needed some CADmodeling support. We adapted our curriculum and made it a priority to help meet this need. Wewere rewarded for it - students loved these service projects. The S-L project served as a link fromengineering theory to everyday objects people can touch and see. Along the process they learnedwhat they needed to learn - the CAD tools. It was a win-win situation. In the following sections,we will document these activities and share some ABET outcome assessment results.The Wrap Rack ProjectOur university’s motto is "To Seek to Learn is to Seek to Serve."1 Service-Learning (S-L) haslong been recognized as an effective way of achieving multiple student learning outcomes
a creative way tosolve a given problem without the conventional step by step laboratory procedure. Thischallenging experience provides students a taste (flavor) of real life engineering environmentand thus better prepares them for professional activities, while increasing their learning andcreativity.REFERENCES[1]. Abd.Rahman, Norliza & Kofli, Noorhisham & Takriff, Mohd & Abdullah, Siti. (2011). Comparative Study between Open Ended Laboratory and Traditional Laboratory. IEEE Global Engineering Education Conference, EDUCON 2011. 40 - 44. 10.1109/EDUCON.2011.5773110.[2]. Dr. Bridget M. Smyser, Kavin McCue. (2012). From Demonstration to Open-Ended Labs, Revitalizing a Measurement s and Analysis Course. ASEE Conference
the study reported inthis paper. In the future, we will use factor scores derived from factor analysis to evaluate themediation relationships between the variables in our study, and we will employ learning andmotivation theories to further explore these relationships.References[1] L. Tian, T. Yu, and E. S. Huebner, "Achievement goal orientations and adolescents’ subjective well-being in school: the mediating roles of academic social comparison directions," Teaching for understanding at university: Deep approaches and distinctive ways of thinking., vol. 8, p. 37, 2017.[2] M. V. Covington, "Goal theory, motivation, and school achievement: An integrative review," Annual review of psychology, vol. 51, no. 1, pp. 171-200
Potential sources of material include your own personal notes where you Present students with made a mistake, or a homework/exam inaccurate work (on a solution that introduces mistakes worth slide or handout) and pointing out have them take a few Make clear something is wrong on your notes on what is wrong, handout, to avoid confusing students Intentional 2-10 then follow up by calling who arrive late or aren't fully paying Mistake(s) minutes on students
one student smaller.Next, gruepr runs its genetic optimization algorithm, displaying its progress to the instructor. Allof the instructor’s chosen teaming options are used in the algorithm’s fitness function. After theoptimization algorithm operates for some time, the set of teams with the quantitatively highestscore is shown to the instructor. The instructor can choose to keep these teams, make minortweaks by swapping one or more pairs of students between teams, or get rid of the teams andrestart the optimization scheme from the beginning. If the instructor chooses to restart theoptimization, they may also choose to adjust the teaming options and/or team size(s) at that time.Since genetic algorithms are, in general, not guaranteed to find
introductory and advanced technical writing courses.Data-driven learningAs the educational marketplace expands, institutions of higher learning are experimenting withhow active learning increases student success. Freeman et al.’s meta-analysis of STEM educationstudies found that active learning significantly increased course grades over didactic methodsand was particularly effective in classes of 50 or less students. In contrast, students were 1.5times more likely to fail a course that lacked active learning strategies [1].The spectrum of active learning ranges from simple activities, such as writing minute papers orpausing for reflection, to more complex activities, such as hands-on technology and inquirylearning. Active learning is being promoted as
findings are that the integration of makingactivities into cornerstone courses provides a great resource to expose students to authenticengineering experiences that can help them be more prepared for their senior years inengineering school and for their future engineering careers.A limitation of this study is that there was only one team in group B. The interventions understudy were initiated in 2015, and a handful of students had registered for them as an elective atthe time. Hence, team B1 was the only team that was available to study whose members hadtaken the design courses under study in their first or second year of study. Still, B1 was thesource of a wealth of qualitative data.Another potential explanation for team B1’s performance is their
methods that best fit the metal(s) of interest in the sample matrix. Method development has also provided participating students the ability to learn the importance and relevance of optimizing analytical methodologies in order to confidently measure trace metals in a sample. Each project required unique sample preparation methods. For example, sample preparation in the "Buried Treasure" project (a collaborative project that involved engineering, art and history disciplines) included development of a digestion method as well as a non- destructive method to preserve archeological glass and ceramic artifacts. 2) Training Instrumentation training was an ongoing program throughout this project
. The contents, opinions, and recommendations expressed are those of the author(s) anddo not represent the views of the National Science Foundation. We would also like to thank ourparticipants for contributing their personal experiences to this research. References[1] O. Amsterdamska, “Demarcating epidemiology,” Sci., Technol., & Human Values, vol. 30, no. 1, pp. 17-51, Jan. 2005.[2] A. C. Barton, V. Johnson, and the students in Ms. Johnson’s Grade 8 science classes, “Truncating agency: Peer review and participatory research,” Res. in Sci. Edu., vol. 32, no. 2, pp. 191-214, Jun. 2002.[3] M. Eisenhart and L. Towne, “Contestation and change in national policy on
contributed to the overall ranking. The graph is essentially a stacked bar chart.An artifact that received all “1”s would be at one side of the chart, and an artifact that receivedall “5”s would be at the other. Ratings of “1” are shown as taller bars than lower ratings, so thatthe stacked bar for a higher-rated artifact is taller than other bars. We provide the rainbow chartas a web service for ranking-based systems. Here is an example of the visualization. Figure 1. Example of visualization of rankingsThe green bars represent a first-place ranking from one’s peers. They are taller than the (yellow)second-place ranking bars, or the bars for any other rank. In this case, the highest-ranked artifactreceived six first-place