Paper ID #19852Improving the Requirements Inspection Abilities of Computer Science Stu-dents through Analysis of their Reading and Learning StylesMr. Anurag Goswami, North Dakota State University Anurag Goswami is a Ph. D. Candidate in the department of Computer Science at North Dakota State University. His main research interests include empirical software engineering, human factors in software engineering, and software quality. He is a member of the IEEE Computer Society.Dr. Gursimran Singh Walia, North Dakota State University Gursimran S. Walia is an associate professor of Computer Science at North Dakota State University
and the Eccles et al. Model of Achievement-Related Choices. In Handbook of competence and motivation, eds. A.J. Elliot and C.S. Dweck. New York: The Guilford Press.Echo Ridge (2017). Dyse – Dynamic Spectrum Environment Emulator, http://www.echoridgenet.com/products/dyse.Evans, J. S. B. T. (2003). In two minds: Dual-process accounts of reasoning. Trends in Cognitive Sciences, 7(10), 454-459. doi:10.1016/j.tics.2003.08.012Evans, Jonathan St. B. T. (2009). How many dual-process theories do we need? one, two, or many? (). Oxford: Oxford University Press. doi:10.1093/acprof:oso/9780199230167.003.0002Gee, J. P. (2003). What video games have to teach us about learning and literacy (1st ed.). New York
conducted, we have uncovered, timeand time again, that our students come into our classes with issues that have a direct or indirectbearing on their ability to learn physics. One central question this paper aims to address is: Arethe factors that impede or enhance student learning in physics any different in the millennial age?IntroductionToday’s classrooms are largely populated by millennials. For the past two decades we have seenincreased use of variety of terms used to describe them. The millennial is often considered to bean individual born sometime between approximately 1980 and 2000. We often refer to thissubset of the population as Generation Y or Gen Y. Other names given to this group ofindividuals include Echo Boomers and 24/7’s
Higher Education, TIAA Institute, April 2016. https://www.tiaainstitute.org/public/pdf/taking_the_measure_of_faculty_diversity.pdf. Accessed Feb. 11, 2017.[5] M. J. Finkelstein, V. M. Conley, J. H. Schuster. (2016). The Faculty Factor: Reassessing the American Academy in a Turbulent Era, Johns Hopkins University Press.[6] M. A. Mason, N. H. Wolfinger and M. Goulden. (2013). Do Babies Matter?: Gender and Family in the Ivory Tower. Rutgers University Press.[7] E. A. Cech and M. Blair-Loy. (2014) Consequences of flexibility stigma among academic scientists and engineers. Work Occupations 41(1):86–110.[8] S. Damaske, E. H. Ecklund, A. E. Lincoln & V. J. White. (2014). Male scientists’ competing devotions to work and family
2003.Colbeck, C.L., Campbell, S.E. and Bjorklund, S.A. 2000. Grouping in the dark: What collegestudents learn from group projects. The Journal of Higher Education, 71 (1): 60-83.Felder, R. M., G. N. Felder and E. J. Dietz. 1998. A Longitudinal Study of Engineering StudentPerformance and Retention. V. Comparisons with Traditionally-Taught Students. Journal ofEngineering Education, 87 (4): 469-480.Felder, R. M., and L. K. Silverman. 1988. Learning and teaching styles in engineeringeducation. Engineering education, 78 (7): 674-681.Froyd, J.E. and M.W. Ohland. 2005. Integrated Engineering Curricula. Journal of EngineeringEducation, 94 (1): 147-164.Graham, T., S. Rowlands, S. Jennings, and J. English. 1999. Towards whole-class inter- activeteaching
Press.2. Pryor, J. H. and Reedy, E. J., 2009, “Trends in Business Interest Among U.S. College Students: An Early Exploration of Data Available from the Cooperative Institutional Research Program,” Ewing Marion Kauffman Foundation.3. Yang, A., 2014, Smart People Should Build Things. New York, NY: HarperCollins Publishers.4. Boyd, N. G. and Vozikis, G. S., 1994, “The Influence of Self-Efficacy on the Development of Entrepreneurial Intentions and Actions,” Entrepreneurship Theory and Practice, pp. 63-77.5. McGrath, R. G., 2000, The Entrepreneurial Mindset: Strategies for Continuously Creating Opportunity in an Age of Uncertainty. Boston, MA: Harvard Business School Press.6. Condoor, S. and McQuilling, M., 2009, “Incorporating an
of all of the projects, students were remindedagain and again to think back to these goals, and encouraged to revise the goals as they learned more. Instep 3 (Decide what should be modeled and why), students imagined the model(s) they would create tomatch their physical system. This process didn’t simply ask students to rely upon knowledge they alreadytheoretically had. Rather, it forced them to research in order to learn how they might model the systemthey were analyzing. This research might take them back to foundational knowledge they had alreadybeen exposed to or to new knowledge; although at the beginning the modeling efforts tended to mainlyemphasize the former. The point is that there had to be early imagining of the ultimate model(s
, which consists ofthe types of information that would customarily be found on a job application. The informationprovided by students is used to compile and understand their capabilities and interests, whichincludes major(s), grade point average or GPA, past or current internship and/or coopexperiences, undergraduate research projects, technical skills, leadership experiences, careerinterests, project preferences, etc. As a result of using this process, over a period of many years,we have acquired a significant amount of data and insights into the factors that may contribute tocapstone team success.In parallel with the process of collecting and compiling information on student interests andcapabilities, project descriptions are developed that are
depth across the range ofengineering topics implied by the title of the program.The curriculum must include probability and statistics, including applications appropriate to theprogram name; mathematics through differential and integral calculus; sciences (defined asbiological, chemical, or physical science); and engineering topics (including computing science)necessary to analyze and design complex electrical and electronic devices, software, and systemscontaining hardware and software components.The curriculum for programs containing the modifier “electrical,” “electronic(s),”“communication(s),” or “telecommunication(s)” in the title must include advanced mathematics,such as differential equations, linear algebra, complex variables, and
question and aided inproducing a thick and rich dataset. The first question asked about the project(s) the student wasworking on and the second asked why he or she chose to participate in the extracurricularproject(s). The next four questions asked the students to discuss how their learning, engagement,confidence, and career prospects are affected by the project(s). The seventh question asked themto describe, in detail, the project building process, while the last two questions had them reflecton the value of the experience and the support they received. After each interview, codingcommenced using a constant comparative technique. Heuristic, discrete units of data was codedand categorized, initially through the note-taking process within the
helped the project was projects with enjoyable and Electrostatics and skills with these me better adequate partner(s) helped fun! Magnetostatics projects understand me understand device through practical uses of the importance of projects Electromagnetics communication with my team mate
light in a S-curved shapeinstead of straight lined LED strip light that is shown in Figure 4 (right). Figure 4 The completed circuit constructions with motors (left) and testing the completed motorized vehicle with photocell sensors along the LED light strip track (right)ConclusionDesigning a logic circuit of the self-correcting vehicle project was found to be motivating for thestudents involved by providing student-driven, interdisciplinary, and technology based learningmethod. The project was completed by three honors students in Spring 2017. All three studentsshowed greater confidence in academic success and further interest in continuing similar researchproject. It allowed the students to combine their knowledge
. REFERENCES [1] Beichner, R., J. Saul, R. Allain, D. Deardorff, and D. Abbot, “Introduction to SCALE-UP: Student-Centered Activities for Large Enrollment University Physics,” presented at the Annual meeting for the American Society for Engineering Education, St. Louis, MS, 2000. FIGURE 7 [2] Ingram, B., M. Jesse, S. Fleagle, J. Florman, and S. Van Horne, “Cases NORMALIZED SUCCESS RATES ACCORDING TO
solve low 9. Schrlau, M.G., R.J. Stevens, and S. Schley, Flippingperformance and retention issues in the first year. Specifically Core Courses in the Undergraduate Mechanicalin courses intended to introduce first year students to contentFirst Year Engineering Experience (FYEE) Conference August 6-8, 2017, Daytona Beach, FL M1A-3 Session M1A Engineering Curriculum: Heat Transfer. Advances in Engineering Education
Education, 95, 1, 2006, pp. 39-47.[2] Knight, D, W, Carlson, L, E, & Sullivan, J, F, “Improving Engineering Student Retention through Hands-On, Team Based, First-Year Design Projects”, 31st International Conference on Research in Engineering Education, June 22 – 24, 2007.[3] Felder, R, M, Felder, G, N, & Dietz, E, J, “A Longitudinal Study of Engineering Student Performance and Retention. V. Comparisons with Traditionally-Taught Students”, Journal of Engineering Education, 87, 4, 1998, pp. 469-480.[4] Sorby, S, A, & Baartmans, B, J, “The Development and Assessment of a Course for Enhancing the 3-D Spatial Visualization Skills of First Year Engineering Students”, Journal of Engineering
used for stability and positioning a protractor. The stand also included a piece of 1.5 m string with a marking at 1.0 m to A B indicate where students should hold the light meter. FIGURE 1 A. COORDINATE SYSTEM FOR ANALYSIS. ASSUME THE CENTER OF THEBULB IS AT THE ORIGIN AND THE BULB IS ALIGNED ALONG THE Z-AXIS [3]. B. DIAGRAM OF SPHERICAL CAP SURFACE AREA. THE ARROWS SHOW THEDIRECTION OF 𝐸! MEASUREMENTS FOR THE FIRST THREE 𝜃′S. THE SMALLER DASHED LINES SHOW THE 𝑆𝐴! 'S ASSOCIATED WITH 𝜃! AND 𝜃
the laststudent to select will inevitable be forced on a team, whichcan be a problem in certain situations.Future DirectionsAs a “Work in Progress” data has not been collected toassess the effectiveness of the method presented. Teamswere created using the method presented here along withother team formation methods across several sections of acommon first year engineering course. By the time of theconference these data will be available. REFERENCES[1] S. H. Bhavnani and M. D. Aldrich, "Teamwork across Disciplinary Borders: A Bridge between College and the Work Place," Journal of Engineering Education, vol. 89, no. 1, pp. 13- 16, 2000.[2] Engineering Accreditation Commision, "Criteria for accredition
Skills: The McMaster Problem Solving Program”, Journal of Engineering Education, April 1997, pp. 79-91 [4] Felder, R, M, Silverman, L, K, “Learning and Teaching Styles in Engineering Education”, Engr. Education, 78(7), pp. 674-681, 1988 [5] Freeman, S, Eddy, S, L, McDonough, M, Smith, M, K, Okoroafor, N, et al, “Active
studentachievement and attitude.References[1] Lowell, J., Utah, B., Verleger, M., & Beach, D. (2013). The Flipped Classroom : A Survey of the Research The Flipped Classrom : A Survey of the Research. Proccedings of the Annual Conference of the American Society for Engineering Education, 6219[2] Laman, J. A. (2012). AC 2012-4028 : CLASSROOM FLIP IN A SENIOR-LEVEL ENGINEER- ING COURSE AND COMPARISON TO PREVIOUS VERSION Classroom Flip in a Senior-Level Engineering Course and Comparison to Previous Version Abstract identified by students as needing further review and ex.[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
to 1st graders. We are excited tocontinue this work.iCommittee on Public Understanding of Engineering Messages, 2008. Changing the Conversations: Messages for Improving thePublic Understanding of Engineering. National Academy of Engineering. The National Academy Press. Washington, DC. Master, A., Cheryan, S., & Meltzoff, A. N. (2016). Computing whether she belongs: Stereotypes undermine girls’ interest andiisense of belonging in computer science. Journal of Educational Psychology, 108(3), 424. S., Master, A., & Meltzoff, A. N. (2015). Cultural stereotypes as gatekeepers: increasing girls’ interest in computeriii Cheryan,science and engineering by diversifying stereotypes. Frontiers in psychology, 6, 49.iv https
departments, and could potentially increasestudent retention. The results of advancing students in math and improving their critical thinkingskills in student retention and graduation rate in engineering is currently being investigated.AcknowledgementsThis research is supported by a grant received from the National Science Foundation (Grant #DUE-1504730). The opinions expressed are those of the authors and do not necessarily representthose of the NSF. The authors would like to thank Drs. Amy Kuhn and Robin Hensel for theirassistance and recommendations in the project.ReferencesCoolbaugh, A., Veeramachaneeni, S., Morris, M., & Santiago, L. (2017). Promoting Critical Thinking Skills in Non-Calculus Ready First Year Engineering Students. San
Microcontroller. The speed to simulate the required torqueforces in the chip was estimated at between 50 and 90 rad/s. Some test results for chips areshown in Fig. 5, indicating the change in threshold torque with channel geometry. A Gantt chartschedule for the 8-month project is shown in Fig. 6.Conclusion and Discussion. This project proved to be an instructive case study for senior designon several accounts: 1) it developed and tested a useful medical sensor with importantapplications, 2) it utilized a microfluidic chip as a sensor, rather than the more typicalapplications of microfluidics for sample processing and analysis, 3) it demonstrated that there isa place for completely non-electrical sensors, and 4) its easy prototyping allowed students
by choosing a different path of study. Phase II of the project begins in Fall 2017with data collection on self-regulated decision making, major fit, and self-regulated learning inorder to map real-world behaviors (major changes) to self-regulated decision-making theory20.AcknowledgementThis material is based upon work supported by the National Science Foundation (NSF) underGrant No. 1554491. 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.References1. Pascarella ET, Terenzini PT. Predicting voluntary freshman year persistence/withdrawal behavior in a residential university: A path analytic validation of Tinto’s model. J
studentmisconceptions associated with the TBL from the transport class will hopefully be repaired.However, where misconceptions persist or new ones are revealed through posttest assessmentswe will modify videos, simulations and in-class activities as necessary and re-test the approachin subsequent course offerings. AcknowledgementsThis project is funded by NSF IUSE 1432674. The authors would like to thank Nehal Abu-Lailfor allowing us to implement this demonstration in her class. References1. A. Jacobi, J. Martin, J. Mitchell, and T. Newell. A concept inventory for heat transfer. in Frontiers in Education, 2003. FIE 2003 33rd Annual. 2003, IEEE.2. S. Kolari and C. Savander-Ranne, Visualisation promotes apprehension and comprehension
visual interfaces and information richness. The proposed app-based tool will facilitate students’ learning by engaging them with rich information resources and virtual hands- on activities. Acknowledgement This material is based upon work supported by the National Science Foundation under Grant No. EEC 1343749. References1. Crawford, M. 10 Ways Nanotechnology Impacts Our Lives. The American Society of Mechanical Engineers (2016).2. Roco, M. The long view of nanotechnology development: the National Nanotechnology Initiative at 10 years. J. Nanoparticle Res. 427–445 (2011).3. Jeschke, S. Collaborative Working Environment for Virtual and Remote Experiments in Nanoscience and Nanotechnologies. in Interactive Mobile and
number of students in Spring 2016 class. The Spring 2015 class had total of 20 studentswhere 2 students did not continue the class after the first Midterm. Spring 2016 class had 18students and 2 students did not continue after the first midterm. Furthermore, the same amount ofcourse material was covered in both the classes.ResultsSpring 2015 and Spring 2016 grading criteria is shown in Table 1. For comparison, Spring2016’s midterms total points are converted to the equivalent of Spring 2015 total midterm pointsof 50%. Figure 1 shows the total points students received in both the semesters at the end of allthe Midterms. Average Midterm exam score and standard deviation of Spring 2015 was 32 (totalscore of 50) and 7.06 respectively. Midterm exam
anode electrode. IMFC is the current produced by theMFC reactor. The meanings of all parameters shown in Equations (4) - (8) can be found in ourprevious ASEE paper [3]. The model contains 4 differential equations, 9 equations, and 25parameters. dS = -qa xa - qm xm + D( S0 - S ) (4) dt dxa = - µ a xa - K d ,a xa - a a Dxa (5) dt dxm = - µm xm - K d ,m xm - a m Dxm (6) dt