manners”. ASEE Prism. American Society for Engineering Education. 2005. vol. 15. no. 4. pp. 45.[10] B. Horn. “A reflection on leadership: A comparative analysis of military and civilian approaches,” 2014, Journal of Military and Strategic Studies, vol 15. No. 3.[11] Y. Xue, R. Larson. “STEM crisis or STEM surplus? Yes and yes”. 2015. Website. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5800410/ (Accessed November 7, 2019)[12] A. Barr, A. “From the battlefield to the schoolyard: The short-term impact of the Post-9/11 G.I. Bill”. The Journal of Human Resources, 2015. vol. 50. no. 3. pp. 580-613.[13] A. W. Radford, A. Bentz, R. Dekker, J. Paslov, J. “After the Post-9/11 G.I. Bill: A profile of military service
subgroups.AcknowledgementsThis material is based upon work supported by the National Science Foundation under grantnumbers DUE #1834425 and DUE #1834417. Any opinions, findings, and conclusions orrecommendations expressed are those of the authors and do not necessarily reflect the views ofthe NSF.References[1] O. Ha and N. Fang, "Spatial Ability in Learning Engineering Mechanics: Critical Review," Journal of Professional Issues in Engineering Education and Practice, vol. 142, no. 2, p. 04015014, 2015.[2] J. G. Cromley, J. L. Booth, T. W. Wills, B. L. Chang, N. Tran, M. Madeja, T. F. Shipley and W. Zahner, "Relation of Spatial Skills to Calculus Proficiency: A Brief Report," Mathematical Thinking and Learning, vol. 19, no. 1, pp. 55-68, 2017.[3] S. A. Sorby
January 6, 2020.[13] S. M. Lord, “Retention and Persistence in Engineering: Data, Issues, and Ideas,” Benton Lecture for Herbert Wertheim College of Engineering, University of Florida, Gainesville, FL, April 18, 2019.[14] S. M. Lord, “Persistence in Engineering: Research and Reflections,” UCI Education Research Initiative Invited Seminar, University of California-Irvine, Irvine, CA, May 23, 2019.[15] M. W. Ohland, “We value what we measure: Exploring data quality and the challenges of working with pre-existing data structures,” Florida International University, School of Universal Computing, Construction, and Engineering Education, Miami, FL, November 13, 2019.[16] M. W. Ohland, “Lessons
resistance. The study also hopes to provide answers of if students are actuallyresisting active learning, as well as the instructors’ perception of this resistance.AcknowledgmentsThis material is based upon work supported by the National Science Foundation under Grant NoDUE-1821488. 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] Dancy, M., Henderson, C., &; Turpen, C. (2016). How faculty learn about and implementresearch-based instructional strategies: The case of Peer Instruction. Physical Review PhysicsEducation Research, 12(1), 010110.[2] Gradinscak, M. (2011). Redesigning engineering
, while I had not made up my mind on going to graduate school before,I now am certain that I want to get a masters.” Increased interest in Graduate schools is also seenin Figure 6, which shows the participant responses to survey questionnaire before and afterparticipation. Figure 6. Student responses to pre- and post-participation survey questions (average of 2017, 2018, and 2019 ratings).3. Lifelong Learning Skills and Acquisition of Interdisciplinary KnowledgeFigures 5 and 6 also show that the program has been able to instill lifelong learning skills in theparticipants and increase their knowledge of other disciplines. Mentor and participant qualitativefeedback reflected the value of participant exposure to the
.[9] R.M. Felder and R. Brent, Teaching and Learning STEM: A Practical Guide. San Francisco,CA: Jossey-Bass, 2016.[10] S.B. Merriam, Qualitative Research and Case Study Applications in Education. Jossey-Bass, 2001.[11] J. Saldana, The Coding Manual for Qualitative Researchers (2nd Edition). Thousand Oaks,CA: Sage Publications, Inc., 2013.AcknowledgementThis material is based upon work supported by the National Science Foundation under Grant No.1347675 (DUE). Any opinions, findings, conclusions, or recommendations expressed in thismaterial are those of the authors and do not necessarily reflect the views of the National ScienceFoundation.
. Theirimpact on student learning was also partially reflected in student responses to other open-endedquestions. For instance, students were able to provide important justifications when prompted todiscuss energy sources with an advocate of a particular approach, such as “You have to factor inthe cost, the power it supplies, and the effectiveness over X amount of years.” “The best way toselect an energy source is to focus on being environmentally friendly first. Then find the mostcost effective that will produce enough energy for your needs.” Students also commented on themost important things they learned through the game such as “The most important thing that Ilearned was to be environmentally friendly rather than being the most cost and energy
Page 23.842.2issues. The experimental skills in circuits and electronics of many graduate students are stilldeveloping and not all of the graduate students in the GTA pool are interested in the subjectmatter. This lack of experience and interest is much more difficult to overcome, yet is quicklysensed by the undergraduates taking the course who will reflect this in their comments on thequality of instruction at the end of the semester. Thus, the selection of the instructor for thelectures has been a critical factor to the successful introduction of guided self-learning inexperimental techniques using LiaB.Development of online circuits laboratory course for on-campus studentsMotivation: While a physical lecture was also incorporated in the
. National ScienceFoundation (Award DUE-1042030). Any opinions, findings, conclusions, and/orrecommendations are those of the investigators and do not necessarily reflect the views of theNational Science Foundation.References [1] Kilgore, D., Atman, C. J., Yasuhara, K., Barker, T. J., & Morozov, A. (2007). “Considering Context: A Study of First‐Year Engineering Students,” Journal of Engineering Education, 96(4), 321-334. [2] Olds, B. M., & Miller, R. L. (2004). “The Effect of a First‐Year Integrated Engineering Curriculum on Graduation Rates and Student Satisfaction: A Longitudinal Study,” Journal of Engineering Education, 93(1), 23-35. [3] Pendergrass, N. A., Kowalczyk, R. E., Dowd, J. P., Laoulache, R. N., Nelles, W., Golen, J
processing, biometrics, pattern recognition and filter design.Dr. Kevin D. Dahm, Rowan University Kevin Dahm is a Professor of Chemical Engineering at Rowan University. He received his B.S. from WPI in 1992 and his Ph.D. from MIT in 1998. He co-authored the book ”Interpreting Diffuse Reflectance and Transmittance,” published in 2007, with his father Donald Dahm. His second book, ”Fundamentals of Chemical Engineering Thermodynamics,” a collaboration with Donald Visco of the University of Akron, is expected to be released by January 10, 2014. Kevin has received the 2002 PIC-III Award, the 2003 Joseph J. Martin Award, the 2004 Raymond W. Fahien Award and the 2005 Corcoran Award from ASEE.Dr. Richard J. Kozick, Bucknell
of the e-book and the proposed learning environment.The J-DSP Simulation EnvironmentJ-DSP, a web-based DSP education software, is a block-based environment where simulationsare established by choosing blocks through a drag-n-drop process and connecting them toestablish signal flow. Any change in the simulation parameters are automatically reflected in thefollowing blocks. An example simulation established in the J-DSP interface along withvisualization of the output is shown in Figure 1. A set of DSP laboratories have been developedin J-DSP that cover several DSP concepts including the z-transform, digital filter design, spectralanalysis, multirate signal processing, and statistical signal processing along with a rich set ofvisualization
Page 25.569.2 recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.Components of TAILS Lab ExperimentsTAILS will deliver the tale of each AI algorithm or concept through a story with nine parts,including a description of the concept, relevant applications, sample test data, design description,exercises that guide the student in implementation, a test driver, suggested experiments, sourcecode that implements the algorithm, and complexity analysis. This choice of components ispatterned after the organization found in the files of software support that accompany Winston'sapproach4 and standard software engineering practice. Previous work5 identified
well the course objectives wereachieved on a scale of 1 to 5 with 5 being Strongly Agree and 1 being Strongly Disagree. Table 1reflects student feedback regarding access to new, effective curriculum modules and labs thatmore accurately reflect the needs of industry. Overall feedback was extremely positive.Measurable Outcomes Overall RateStudents will learn how to model basic digital circuits in hardware description 4.73languages.Students will learn how to use VHDL to model common digital hardware 4.64circuits - combinational and sequential circuitsStudents will learn how to use to use VHDL CAD Tools (editors, debug designs 4.25and perform logic simulation
increase in the learninggain. We are encouraged by the positive and enthusiastic feedback from the students on the newmodule. In the future, the entire set will be offered and more details will be reported separately.AcknowledgementsThis material is based upon work supported by the National Science Foundation under Grant No.DUE-TUES-0941035. Any opinions, findings, and conclusions or recommendations expressed inthis material are those of the authors and do not necessarily reflect the views of the NationalScience Foundation.References[1] Gurocak, H., “Mechatronics course with a two-tiered project approach,” 2007 ASEE Annual Conference and Exposition.[2] Giurgiutiu, V. and Mouzon, B., “Functional Modules for Teaching Mechatronics to
-BIM teaching Page 24.459.10method.AcknowledgmentThis material is based upon work supported by the National Science Foundation under Grant No.DUE-1140941. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author and do not necessarily reflect the views of the National ScienceFoundation.References1. Kelly,W. E. (2008). “General education for civil engineers: Sustainable development.” Journal of Professional Issues in Engineering Education and Practices, 134(1), pp. 73-83.2. Kim, J.-L. (2012). “Use of BIM for effective visualization teaching approach in construction education,” Journal of
, andconclusions or recommendations expressed in this material are those of the authors and do notnecessarily reflect the views of the National Science Foundation.References1. United Nations. United Nations Millennium Development Goals [Internet]. Millennium Goals. 2013 [cited 2013 Oct 2]. Available from: http://www.un.org/millenniumgoals/2. National Academy of Engineering. News from the National Academies [Internet]. National Academies. 2008 [cited 2013 Oct 7]. Available from: http://www8.nationalacademies.org/onpinews/newsitem.3. Duderstadt JJ. Engineering for a Changing World: A Roadmap to the Future of Engineering Practice, Research
supported by the National Science Foundation EngineeringEducation Program under Grants #1264769 and #1264901. Any opinions, findings, conclusions,or recommendations expressed here are those of the authors and do not necessarily reflect theviews of the National Science Foundation. Page 24.284.7 5References1 National Science Board (2007). A National Action Plan for Addressing the Critical Needs of the U.S. Science,Technology, Engineering, and Mathematics Education System, Arlington, VA, National Science Foundation,http://www.nsf.gov/nsb/documents/2007
do not necessarily reflect the views of the National Science Foundation.References1. “Lighting the Path to a Competitive, Secure Future, A White Paper by the National Photonics Initiative, May 23,2013”,http://www.lightourfuture.org/files/8213/6943/4583/Lighting_the_Path_to_a_Competitive_Secure_Future_052413.pdf, accessed on Oct. 15, 20132. “Industry Demand for Two-Year College Graduates in Optics and Photonics Technology, A 2012 Industry Surveyof Current and Future Demand for Two-Year Degreed Photonics Technicians”,http://www.op-tec.org/2012survey.php, accessed on Oct. 15, 20133. National Science Foundation Advanced Technological Education program,http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=5464, accessed on Jan. 2, 20144. “Optics and
, Page 23.232.6 H2 and others) in the public and in private gathering places. This mobile handheld device then can relay the information detected to smart phones or tablets or laptops in any place at any time. Applications of this useful mobile device include coal mine explosion prevention, detections of natural gas and other industrial and explosive chemical leaks, and detection of harmful gases in the public gathering places such as subway stations, shopping malls, and airports. Figure 8 shows a prototype of the handheld device. a) Prototype of HCDD b) Case Design Figure 8. Mobile Handheld Chemical Detection DeviceAs can be seen, the scope of all the design projects reflected
members.AcknowledgementsThis material is based upon work supported by the National Science Foundation, EngineeringEducation and Centers (EEC) division, IEECI program, under Grant No. EEC-1037729. Anyopinions, findings, and conclusions or recommendations expressed in this material are those ofthe authors and do not necessarily reflect the views of the National Science Foundation. Theauthors gratefully acknowledge the support of Dr. Marcia Belcheir, Coordinator of InstitutionalAssessment and Associate Director of Institutional Analysis, Assessment and Reporting forsummarizing administrative and data management support with the self-report survey discussedin this paper.References1. Ford, G.S., T.M. Koutsky, and L.J. Spiwak. (2007). "A Valley of Death in the Innovation
0.665 Factor 2 (projects and case studies) 2 0.676The data analysis sorted the 11 ABET outcome items into two groups. It was found that items 1 Page 25.1339.6through 5, 7, and 11 were grouped together into factor 1, and items 6 and 8 through 10 weresorted together into factor 2. On reflection, the authors decided to term these factors “technicaldevelopment” and “professional development.”The outcomes grouped under technical development mostly refer to the “number crunching”skills in engineering, specifically outcomes 1 through 3, 5, and 11. The other two, items 4 and 7,can be thought of as soft skills that
experiment server while still maintaininga secure level of communication. With this interface, no add-ons or plug-ins will need to beinstalled on any computer, and anyone with a web browser and internet access will be able to usethe interface to control an experiment remotely.AcknowledgmentsThis work is partially supported by the National Science Foundation under Grant Numbers EEC-0935208, EEC-0935008, and DUE-0942778.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.Bibliography[1] Ambrose, S. A., & Amon , C. H. (1997). Systematic design of a first-year mechanical engineering course at Carnegie Mellon
the author(s) and do not necessarily reflect the views ofthe National Science Foundation.Bibliography[1] Avouris, P. (2004). Supertubes. IEEE Spectrum , 41-45.[2] Buzatu, D. A., Biris, A. S., Biris, A. R., Lupu, D. M., Darsey, J. A., & Mazumder, M. K. (2004). Electronic Properties of Single-Wall Carbon Nanotubes and Their Dependence on Sythetic Methods. IEEE Transactions on Industry Applications , 1215-1219.[3] Meletov, K. P., Krestinin, A. V., Arvanitidis, J., Christofilos, D., & Kourouklis, G. A. (2010). Thermally Induced Softening of the Radial Breathing Modes of Bundled Single-Walled Carbon Nanotubes. Fullerenes, Nanotubes, and Carbon Nanostructures , 538-544.[4] Saito, R., Dresselhaus, G., & Dresselhaus, M. S
university and were given time to explore the science andengineering practices in NGSS and the progression of expected student competency fromkindergarten through graduation. The workshop engaged teachers in hands-on engineeringexperiences, included direct instruction on engineering practices and provided time to reflect onways to incorporate these practices in their science classroom. In addition, each participant wasrequired to complete a final project from a list of options provided. Many of the teachers createdand instructed new engineering lessons for their classrooms, while being observed by universitystaff. Several teachers used university-based lessons as a means of providing engineering lessonsto their students. Upon completion of the
to understanding psychological safety in engineeringdoctoral education. By investigating the impact of psychological safety on students anddeveloping resources to enhance faculty-student relationships, we seek to foster inclusive,psychologically safe research environments that support graduate student success and enhancedresearch innovation.AcknowledgmentsThis work was funded by the the National Science Foundation (Award #2224421) 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] L. L. Baird, “Helping graduate students: A graduate adviser’s view,” New Dir. Stud. Serv., vol. 1995, no. 72, pp
students intheir learning. [5], [7] As outlined in the principles of good feedback practice, by Nicol, goodfeedback can “facilitate the development of self-assessment and reflection in learning” andmotivate the students to “close the gap between current and desired performance.” Onlineassessments can also provide students with a certain amount of flexibility, which can beadvantageous for those with work responsibilities and family care needs. One challenge inimplementing online assessments is academic dishonesty, as students have increasedopportunities for cheating, especially in poorly proctored assessments. However, measures suchas test-taker verification, plagiarism detection software, and supervised monitoring of testingconditions can
resources such as a chamber of commerce or other connectorgroup familiar with local industry, and communication project progress and accomplishmentsregularly.AcknowledgementThis material is based upon work supported by the National Science Foundation under Grant No.1949454. Any opinions, findings, and conclusions or recommendations expressed in this materialare those of the authors and do not necessarily reflect the views of the National ScienceFoundation.References[1] Allen, P.J., Lewis-Warner, K., & Noam, G.G. (2020). Partnerships to transform STEM learning: A case study of a STEM learning ecosystem. Afterschool Matters, 31, 30-41.[2] Pattison, N. P.(2021). Powerful partnership: An exploration of the benefits of school and industry
messages and instructional content, including graphs of data situating team ratings. Thetool asks students to reflect on the messages and patterns that they see in their team, as well as todescribe behaviors they might try next using strategies from motivational interviewing.The National Science Foundation program for Improving Undergraduate STEM Education(IUSE) awarded the authors a grant to support evaluating the effectiveness of this tool, both interms of its ability to detect inequity and exclusion and in terms of its interventions. In this shortpaper and associated poster we summarize some of this work. Specifically, we will present howwe have operationalized “diverse” and “effective” teams, as well as how statistical measures ofthese
] M. J. Scott and G. Ghinea, “On the domain-specificity of mindsets: The relationship between aptitude beliefs and programming practice,” IEEE Transactions on Education, vol. 57, no. 3, pp. 169–174, 2014.[32] D. A. Fields, Y. B. Kafai, L. Morales-Navarro, and J. T. Walker, “Debugging by design: A constructionist approach to high school students’ crafting and coding of electronic textiles as failure artefacts,” British Journal of Educational Technology, vol. 52, no. 3, pp. 1078–1092, 2021. [Online]. Available: https://bera-journals.onlinelibrary.wiley.com/doi/abs/10.1111/bjet.13079[33] D. A. Fields and Y. B. Kafai, “Debugging by design: Students’ reflections on designing buggy e-textile projects,” Proceedings of
student mental health and increasing professional help seeking, especially for studentswho are historically excluded in engineering.Theoretical FrameworkThe IBM is utilized to identify beliefs influencing behavior within a given population [9], whichis grounded in research indicating that intention strongly predicts behavior [10, 11]. In the contextof this project, the IBM asserts that the key driver for help-seeking behavior is the intention to seekhelp (Figure 1). Intention is influenced by three help-seeking mechanisms—attitude, perceivednorm, and personal agency— which are shaped by help-seeking beliefs. Attitude reflects anindividual's overall evaluation (positive or negative) of help-seeking, considering outcome beliefs(anticipated positive