].Faculty undoubtedly play a critical role in the classroom and beyond in improving motivationand the student learning experience [14]. More specifically, through their teaching practices in theclassroom, faculty can help students meet (or not) their three innate psychological needs(autonomy, competence and relatedness) and thus promote (or hinder) students’ intrinsicmotivation for learning. To date, no research has (a) investigated what Engineering faculty knowabout Self-Determination Theory and it’s relationship to student learning, (b) explored whetherfaculty awareness and knowledge of Self-Determination Theory (SDT) [6] has any beneficialimpact on classroom learning environment and student learning, and (c) investigated whetherstudent-level
provided access to the online forumintervention and required to post weekly for the purposes of help seeking and discussion onproblem-solving assignments. Taken as a whole, the mixed dataset presented a rich picture of thehelp seeking processes that students used in the course.Our approach toward analyzing data and presenting project findings in the form of a usage modelrelated to undergraduate help seeking in distance courses was motivated by the (a) need tointegrate mixed data (i.e., quantitative and qualitative data) describing student help seekingbehaviors, needs, attitudes, and goals within a holistic set of easy-to-use findings and (b) desireto expand the base of knowledge related to the application of UCD tools for student-focusedcurricular
Research Experience For Teachers Programs and Their Effects on Student Interest and Academic Performance: A Preliminary Report of an Ongoing Collaborative Study by Eight Programs.”, MRS Proceedings, 684, GG3.6 doi:10.1557/PROC-684-GG3.6, 2001.[7] A. M. Farrell, “What Teachers Can Learn From Industry Internships.” Educational Leadership, pp. 38-39, March 1992.[8] S. Silverstein, J. Dubner, J. Miller, S. Glied, and J. Loike, “Teachers’ Participation in Research Programs Improves Their Students’ Achievement in Science,” Science, vol. 326, pp. 440-442, 2009.[9] B. D. Bowen, A. Kallmeyer, and H. Erickson, “Research Experiences for Teachers: Engineering in Precision Agriculture and Sustainability for Solitary STEM
Paper ID #39764Board 213: An Expanded Integrated Achievement and Mentoring (iAM)Program to Promote Access to STEM ProfessionsDr. Jessica Santangelo, Hofstra UniversityDr. Lynn A. Albers, Hofstra University Dr. Lynn Albers is an Assistant Professor in Mechanical Engineering of the Fred DeMatteis School of Engineering and Applied Science at Hofstra University. Her previous academic contribution was as one of the founding five faculty/staff at Campbell University.Prof. Margaret A Hunter, Hofstra University Margaret Hunter,Ph.D., is an Associate Professor and Associate Chair of Engineering at Hofstra Univer- sity in the Fred
skills.References[1] J. Lave and E. Wenger, Situated learning: Legitimate peripheral participation. Cambridge, UK: Cambridge University Press, 1991.[2] Santangelo, J., Elijah, R., Filippi, L., Mammo, B., Mundorff, E., & Weingartner, K. (2022). An Integrated Achievement and Mentoring (iAM) Model to Promote STEM Student Retention and Success. Education Sciences, 12(12), Article 12. https://doi.org/10.3390/educsci12120843[3] Santangelo, J. R., Albers, L. A., Hunter, M. A., Weingartner, K., Elijah, R., Lefurgy, S. T., Agarwal, R., & Filippi, L. (2023, June). Board 213: An Expanded Integrated Achievement and Mentoring (iAM) Program to Promote Access to STEM Professions. Paper presented at 2023 American Society for Engineering
0 A A- B+ B B- C+ C C- D+ D D- F Course GradeFigure 1: Percentage of each course grade earned by students who participated in thePLTL groups and those who did not participate in the PLTL groups for Math 116 in theFall 2010 semester. 25 PLTL Groups No PLTL Groups 20 15 Percentage 10 5 0 A A- B+ B
Paper ID #31006A Random Forest Model for Personalized Learning in a Narrative GameDr. Ying Tang, Rowan University Ying Tang received the B.S. and M.S. degrees from the Northeastern University, P. R. China, in 1996 and 1998, respectively, and Ph.D degree from New Jersey Institute of Technology, Newark, NJ, in 2001. She is currently a Professor of Electrical and Computer Engineering (ECE) at Rowan University, Glass- boro, NJ. Her research interests include virtual reality and augmented reality, artificial intelligence, and modeling and scheduling of computer-integrated systems. Dr. Tang is very active in adapting and devel
AC 2012-3735: A MODULAR APPROACH FOR TEACHING A FIRST UN-DERGRADUATE COURSE IN NANOELECTRONICSDr. Syed Iqbal Omar P.E., Texas A&M University, Kingsville Syed Iqbal Omar is a professor of electrical engineering and computer science at Texas A&M University, Kingsville. The areas of his current research interests are computational nanotechnology and spintronics.Prof. Reza Nekovei, Texas A&M University, Kingsville Reza Nekovei is a professor of electrical engineering and computer science at Texas A&M Univer- sity, Kingsville. He has many years of experience in developing graduate and undergraduate programs. Nekovei is currently co-PI for two NSF projects related to teaching by design research and develop
,andsustainability.WearedevelopingafacultythatembracestheredefinedengineeringcanonandtheprofessionalspinethroughfacultyempowermentworkshopsandbyhiringfacultywiththedesiretocontributetotheREDgoals.Wearealsoestablishingpartnershipstodevelopacultureofchangewithintheschoolanddevelopingprofessionalskillsincludinggreaterconnectionsbetweentechnicalknowledgeandprofessionalpracticethroughanindustry-developed“IndustryScholarsProgram.Finally,weareusinganew“GeneralEngineering”departmentasanincubatorofREDcurriculumstaffedwithclusterhiresaroundtheREDproposalthemes.References[1] Bamford, D. & Forrester, P., “Managing planned and emergent change within an operationsmanagement environment,” International Journal of Operations & Production Management,23(5), 546–564 2003.[2] Przestrzelski, B., Roberts, C., and Perry, L.,“The Industry Scholars Program: An OrganicProgram Grown by Industry Professionals for Undergraduates,” Proceedings of the ASEEAnnual Conference and Exposition, Salt Lake City, Utah, June 24-27, 2018.[3] Fosfuria, A. & Røndeb, T., “Leveraging resistance to change and the skunk works model ofinnovation, Journal of Economic
efforts are notalways driven by experiences of the practitioners in the field. In this study, this lens is beingused to address the proposed research questions and achieve the following outcomes: A. Literature review synthesizing and highlighting the current state of research and practice around broadening the participation of African Americans; B. Innovation Cycle of Broadening Participation, a conceptual model that depicts the current relationship between research and practice in this context and outlines a national agenda for coordinating the efforts of stakeholders committed to broadening participation of African Americans in engineering and computer science.To this end, we began a three-year, NSF-funded project in
Paper ID #29299Educating the Workforce in Cyber & Smart Manufacturing for Industry 4.0Dr. Mathew Kuttolamadom, Texas A&M University Dr. Mathew Kuttolamadom is an associate professor in the Department of Engineering Technology & In- dustrial Distribution and the Department of Materials Science & Engineering at Texas A&M University. He received his Ph.D. in Materials Science & Engineering from Clemson University’s Int’l Center for Au- tomotive Research. His professional experience is in the automotive industry including at the Ford Motor Company. At TAMU, he teaches Mechanics, Manufacturing and
), and co‐op/internship experience Figure 2. Figure 2: Seniors with greater makerspace involvement tend to produce higher quality ideas. Makerspace involvement Acknowledgements to the grant Carberry, A. R., H. S. Lee and M. W. Ohland (2010). "Measuring engineering design self‐efficacy." Journal of Engineering Education 99(1): 71‐79. Levy, B. D. (2017). Equivalent design problems, an experimental study, Georgia Institute of Technology. Linsey, J., J. Murphy, A. B. Markman, K. Wood and T. Kurtoglu (2006). Representing analogies: Increasing the probability of innovation. ASME 2006 International Design Engineering Technical Conferences and
students partner with teachers across university sites to: (a) inspire and enable K-12th grade STEM teachers within commuting distance of a participating university to engage in authentic agrivoltaics engineering research, and (b) spread agrivoltaics research experiences to schools serving students from populations historically minoritized in engineering. Given our district partners, this primarily includes students with limited economic means, and students from Latin@ and Indigenous communities.First, during a six-week RET summer program, teachers are co-located in a universityresearch lab where they (a) learn PV content knowledge, including understanding whatis currently known about agrivoltaics systems around the
, N. (2005). Academic mentoring in college: The interactive role of student’s and mentor’s interpersonal dispositions. Research in Higher Education, 46(1), 29-51.Boardman, C., & Bozeman, B. (2007). Role strain in university research centers. The Journal of Higher Education, 78(4), 430-463.Bordes, V., & Arredondo, P. (2005). Mentoring and 1st-year latina/o college students. Journal of Hispanic Higher Education, 4(2), 114-133.Bowen, W. G., & Sosa, J. A. (1989). Prospects for faculty in the arts and sciences. Princeton, NJ: Princeton University Press.Boyer, E. L. (1990). Scholarship reconsidered: Priorities of the professoriate. Princeton, NJ: Carnegie Foundation for the Advancement of
and their association with career interest in STEM,” International Journal of Science Education, Part B, vol. 2, no. 1, pp. 63–79, 2012.[5] Y. S. George, D. S. Neale, V. Van Horne, and S. M. Malcom, “In pursuit of a diverse science, technology, engineering, and mathematics workforce: Recommended research priorities to enhance participation by underrepresented minorities,” American association for the advancement of science, 2001.[6] N. Gonzalez, L. C. Moll, and C. Amanti, Eds., Funds of Knowledge: Theorizing Practices in Households, Communities, and Classrooms. New York: Routledge, 2005. doi: 10.4324/9781410613462.[7] P. Bell, L. Bricker, S. Reeve, H. T. Zimmerman, and C. Tzou, “Discovering and Supporting
systematic review and meta-analysis. Psychological Bulletin, 138(2), 353-387. doi:10.1037/a0026838[9] Goodman, I., & Cunningham, C. (2002). Final Report of the Women's Experiences in College Engineering (WECE) Project (ED507394). Retrieved from https://eric.ed.gov/?id=ED507394[10] Marra, R. M., Rodgers, K. A., Shen, D., & Bogue, B. (2013). Women Engineering Students and Self-Efficacy: A Multi-Year, Multi-Institution Study of Women Engineering Student Self-Efficacy. Journal of Engineering Education, 98(1), 27-38. doi:10.1002/j.2168- 9830.2009.tb01003.x[11] Lent, R. W., Brown, S. D., Schmidt, J., Brenner, B., Lyons, H., & Treistman, D. (2003). Relation of contextual supports and barriers to choice behavior in
Paper ID #5792Live Energy: An Initiative for Teaching Energy and Sustainability Topicswith the most Up-to-date and Relevant ContentDr. Christine Ehlig-Economides, Texas A&M University Dr. Ehlig-Economides has been full professor of petroleum engineering at Texas A&M University in the Albert B. Stevens endowed chair since 2004. Before that she worked for Schlumberger for 20 years in well test design and interpretation, integrated reservoir characterization, modern well construction design, and well stimulation. She has worked in more than 30 countries and authored more than 60 papers. Dr. Ehlig- Economides has
, and developing achievement-related motivations and engagement,” in Handbook of socialization: theory and research, 2007.[14] S. Hidi and K. A. Renninger, “The four-phase model of interest development,” Educational Psychologist, vol. 41, no. 2, pp. 111–127, Jun. 2006.[15] H. Markus and P. Nurius, “Possible selves,” American Psychologist, vol. 41, no. 9, pp. 954–969, 1986.[16] B. Gray, Collaborating: Finding common ground for multiparty problems, 1st ed. San Francisco: Jossey-Bass, 1989.[17] B. Gray and J. M. Purdy, Collaborating for our future: multistakeholder partnerships for solving complex problems, First edition. Oxford ; New York, NY: Oxford University Press, 2018.[18] A. M. Thomson and J. L. Perry, “Collaboration
communicate clearly to the team, group, or broad Communication audience. Discouraging A leader who induces a loss of hope or diminishes ambition in others.Table 2. Leader Role-Model Categories Scientist Scientists in fields such as physics that had notable achievements in their fields of studies. Current Elon Musk (b. 1971, Generation X), Bill Gates (b. 1955, Baby Boomer), Mark Leaders in Zuckerberg (b. 1984, Millennial). Both male and female students across Technology race/ethnicity only identified current technology leaders that are white males. Elon Musk came up consistently in interviews because of his innovation and also serving society by using technology to address societal needs
both the pre- and post- survey. The last two questionsof the survey asked gender identity and age. Gender identity options included (a) man, (b) woman, (c)non-binary, (d) prefer not to answer, and a write in option. Students participating identified as 50% menand 50% women. Average age of the student respondents was 16.8 ± 1.5 years.Definitions of a soft robot In the free response section of the survey, participants were asked “What is asoft robot?”. Overall, students had reasonable ideas about what soft robots were and their uniquefeatures compared to traditional robots. Table 1 shows a summary of pre- and post- survey responses forthis question. While in the post survey, no one answered “I don’t know”, it is important to note that 4
. Interestingly, changing major within the school appears more frequent. Furthermore, it is common to witness students migrating within the school in the later years of their studies. Figure 2, shows the distribution of migration over the semesters for both migrations outside the school and within the school. B sem10, A sem1, sem10,sem1, sem9, 3% 2% 3% 0% 3% sem8, 7% sem9, sem2, 16% 17
satisfactory. We also observed that students' learningbehaviors are slightly different in some instances between the on-campus sections and the on-line sections. We believe that some observations call for further investigations, which mayprovide insights for developing more effective learning tools, especially for online learning.Bibliography1. J. T. Bushberg, J. A. Seibert, E. M. Leidholdt, and J. Boone, Essential Physics of Medical Imaging (2nd Ed),Lippincott Williams & Wilkins, 2002.2. A. Louie, J. Izatt, and K. Ferrara, “Biomedical Imaging Graduate Education Programs: Imaging Curricula andImaging Courses”, the Whitaker Foundation Biomedical Engineering Education Summit, 2005,http://www.whitaker.org/academic/wrapup.html.3. C. B. Paschal, “The
. Chem. Educ., vol. 83, no. 5, p. 804, May 2006, doi: 10.1021/ed083p804.[12] M. D. Koretsky, B. J. Brooks, R. M. White, and A. S. Bowen, “Querying the questions: Student responses and reasoning in an active learning class,” J. Eng. Educ., vol. 105, no. 2, pp. 219–244, 2016, doi: 10.1002/jee.20116.[13] M. D. Koretsky, B. J. Brooks, and A. Z. Higgins, “Written justifications to multiple- choice concept questions during active learning in class,” Int. J. Sci. Educ., vol. 38, no. 11, pp. 1747–1765, Jul. 2016, doi: 10.1080/09500693.2016.1214303.[14] S. A. Finkenstaedt-Quinn, M. Petterson, A. Gere, and G. Shultz, “Praxis of Writing-to- Learn: A model for the design and propagation of Writing-to-Learn in STEM,” J. Chem
ScienceFoundation.References[1] A. Godwin, “The Development of a Measure of Engineering Identity,” presented at the 2016 ASEE Annual Conference & Exposition, Jun. 2016. Accessed: Sep. 24, 2021. [Online]. Available: https://peer.asee.org/the-development-of-a-measure-of-engineering-identity[2] B. E. Hughes, W. J. Schell, B. Tallman, R. Beigel, E. Annand, and M. Kwapisz, “Do I Think I’m an Engineer? Understanding the Impact of Engineering Identity on Retention,” presented at the 2019 ASEE Annual Conference & Exposition, Jun. 2019. Accessed: Feb. 10, 2023. [Online]. Available: https://peer.asee.org/do-i-think-i-m-an-engineer-understanding-the-impact-of-engineering-i dentity-on-retention[3] M. M. Camacho and S. M. Lord, The Borderlands of
examined the percentage of students in these groups who ended the first andsecond semester of introductory chemistry with a grade of B- or better. This analysis reflects aspecific goal of RESP, which is to encourage students to persist in STEM with relatively goodgrades while acknowledging that attaining the highest course grades may be out of reach formany of these students during their first year in college. Thus, RESP aims for students to finishthe semester in the top two-thirds of the course, which in most cases reflects grades of B- orbetter.Hypothesis 4: RESP participants will receive proportionately more B- or higher grades than theproportion received by control group students in first-semester chemistry.Hypothesis 5: RESP participants will
physical contexts related to the concepts they learned about. This will informour selection of physical models for the model-based course and provide culturally relevantcontexts for the new course.ReferencesBandura, A. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review, 84, 191-215.Bandura, A. (1986). Social foundations of thought and action: A social cognitive theory. Prentice Hall.Beer, F., Johnston, E. R., & Mazurek, D. (2012). Vector Mechanics for Engineers: Statics (10th edition). McGraw Hill.Chan Hilton, A. B., & Neupauer, R. M.(Eds.). (2012) H2OH Classroom demonstrations for water concepts. American Society of Civil Engineers.Felder, R. M. & Brent, R. (2016
attended fiveREU workshops at University of South Carolina (UofSC) on topics ranging from ethics, posterpresentation preparation, and graduate school application preparation. The students alsoparticipated in the project team’s critical thinking sessions on defining a research problem, doinga literature search, and the research process. The research group traveled to Clemson to visit theCyberphysical Systems Lab and Tier 1 University Transportation Center for ConnectedMultimodal Mobility (C2M2) at CU (see Figure 3 (b)). The final research presentations were heldat the end of the program on the college’s campus. Students presented their posters to other summerresearch students, college faculty, and guests.During this REU, we were able to involve a
25.1356.7In the OSU course, students follow the complete design cycle for each of the labs.Implementation: This course introduces students to the methods by which math topics are usedin engineering science and design courses. Students apply mathematics through experimentationand design projects. Both analytical and computational (MATLAB) techniques are used for dataanalysis and graphical representation. The course objectives are listed below. At the conclusionof the course the students should be able to: a) Use algebra, systems of equations, trigonometry, sinusoids, derivatives, and integrals in solving engineering analysis and design problems b) Work effectively in teams c) Communicate engineering work effectively in written form
% 71.4% % Returning - 27.3% 50% % Caucasian/African American 100%/0% 91%/0% 79%/14% % from Minority Serving Districts 54.5% 45.4% 50% District School School Districts* a(2),b(1),c(2 a(2),b(2),c(1),f( a(1),b(3),c(3),g( ),d(1),e(1),f( 2),g(1),h(1),i(1) 1)h(3),I(1),j(1),l( 1),j(1), k(2) 1) % Math 27.3% 18.2% 42.9
model maps for high and low performing teams, respectively. Page 26.771.7 VCVD: Team AFigure 3. Model map for a high performing VCVD team. VCVD: Team B Instructor Material Consultation Thickness