Program Chair for the ASEE Faculty Development Division, and the Vice Chair for the Research in Engineering Education Network (REEN). He holds degrees in Industrial Engineering (BS, MS) from the National Experimental University of T´achira, Master of Business Administration (MBA) from Temple University, and Engineering Education (PhD) from Virginia Tech.Dr. Jennifer Lyn Benning, Virginia Polytechnic Institute and State University Dr. Jennifer Benning is an Instructor in the Engineering Education Department at Virginia Tech.Donna Westfall-Rudd ©American Society for Engineering Education, 2023 P R E S E NT A T I ON B Y Q U A L L A J O K E T CH U MWALKING BETWEENTWO WORLDSCreating a Framework for
, New Orleans, June 20165. K. Connor, Y Astatke, C. Kim, M. Chouikha, D. Newman, K. Gullie, A. Eldek, S. Devgan, A. Osareh, J. Attia, S. Zein-Sabatto, D. Geddis, “Experimental Centric Pedagogy in Circuits and Electronics Courses in 13 Universities,” ASEE Annual Conference, New Orleans, June 20166. K. Connor, D. Newman, K. Gullie, Y. Astatke, M. Chouikha, C. Kim, O. Nare, P. Andrei, L. Hobson, “Experimental Centric Pedagogy in First-Year Engineering Courses,” ASEE Annual Conference, New Orleans, June 20167. Y. Astatke, K. Connor, J. Attia, O. Nare, “Growing Experimental Centric Learning: The Role of Setting and Instructional Use in Building Student Outcomes,” ASEE Annual Conference, New Orleans, June 20168. Y. Astatke, J
time of flight, t = P + Q*sqrt(-1) for example, could have a physical interpretation.For an object being thrown upward inside a well of depth -120m under a gravity downwardpulling of 9.8 m/s/s, the equation 0 = v0*t + 0.5*9.8*t*t -120 would support a physical situation 2018 ASEE Mid-Atlantic Spring Conference, April 6-7, 2018 – University of the District of Columbiawith a modified depth of (-120 + 0.5*9.8*Q*Q) which carries P as the time of flight since thesqrt(-1) terms must cancel out. Kinematics learning requires a minimum memory capacity whencompared to other physics topics. The long term memory of putting the initial numerical valuesin their appropriate terms could be learned by analyzing each math term in a given equation. Theshort
control blocks (i.e., blocks contain statements ortuple G(V, E, s, t, e), where G’(V, E) is a simple digraph. The vertex set V = Vs *control statements) in M, respectively. The edge set E represents the flow of controls betweenstatement and control blocks in M, i.e., E ⊆ {Vs →Vc ∪ Vc →Vs} where d is a predicate de-t is a termination vertex represents the exit point of M. e contains one edge e1=s →V and acision with either True or false value. s is a start vertex represents the entry point of M andset of edges e2 ⊆ {v →t}. It indicates that a program only has one incoming edge and mayhave a set of e2 if it has multiple return statements.2.3 Construct
can be tested in future research among Native American engineeringstudents, and that can be employed when considering educational interventions for currentstudents.References[1] B. L. Yoder "Engineering by the Numbers," in Engineering College Profile & Statistics Book, Washington DC: American Society for Engineering Education, 2016, pp.11-47.[2] R. W. Lent, S. D. Brown, and G. Hackett, “Toward a unifying social cognitive theory of career and academic interest, choice, and performance,” Journal of Vocational Behavior, vol 45, pp. 79-122, Aug. 1994.[3] R. W. Lent, S. D. Brown, and G. Hackett, “Contextual supports and barriers to career choice: a social cognitive analysis,” Journal of College Student
Paper ID #41826Work in Progress: Transformation Course-Based Undergraduate ResearchExperience (T-CURE)Dr. Heather Dillon, University of Washington Dr. Heather Dillon is Professor and Chair of Mechanical Engineering at the University of Washington Tacoma. Her research team is working on energy efficiency, renewable energy, fundamental heat transfer, and engineering education.EC Cline, University of Washington Tacoma Associate Professor in Sciences and Mathematics, and Director of ACCESS in STEM, an NSF S-STEM supported program that supports students in natural science, mathematics, and engineering at UW Tacoma.Dr. Emese
Science and Engineering Fairs (Evaluation)Science and Engineering (S&E) fairs are a valuable educational activity that are believed toincrease students’ engagement and learning in science and engineering by using inquiry-focusedlearning, engaging students in authentic scientific practices and engineering design processes [1-3], and emphasizing creativity [4, 5]. Proponents also argue that S&E fairs enhance students’interest in science and science careers [6, 7] as well as engineering [2]. From the fair, studentsreport that they have learned more about the scientific process and engineering design, althoughthey may not all feel their attitudes towards STEM fields has improved [2, 8]. In this paper, wefocus on science attitudes, but because
with engineeringoutreach activities to enhance the learning experience of the students enrolled in an engineeringcourse (EGR 299 S course). The objective was to improve the retention of underrepresentedengineering students (majority at CPP) by providing them with opportunities to use theirtechnical engineering skills and by providing them with opportunities to work in diverse andmultidisciplinary teams (building confidence in their knowledge) in order to build relationshipswith K-12 students and to motivate the K-12 students to pursue STEM fields.Introduction to CPP engineering programsCal Poly Pomona is a four-year institution well-known by the diversity of its student population(0.2, 23.6, 3.3, 38.9, 0.1, 19.7, 3.9, 4.4 and 5.7 % of American
. Students establish methodologies for recognizing minerals based on what theyhave learned. From this knowledge, they develop recovery processes motivated by points foreach mineral correctly collected, identified, and accounted for. This can be used as one form ofinsight into the curriculum’s influence on the team’s decision processes and also an indicator ofwhether student learning of science occurred through the use of the structured EDP [30], [32],[33]. The comparison and analysis of the three final days (11,12 and 13) of the curriculumagainst team dialogue is performed.Day 11 Target Group 1 and 2 After preprocessing the conversation for Target Group 1, the result was a 2,824 x20matrix. Target Group 2’s preprocessed conversation produced
that ourapproach can be replicated in other fields and other student populations.AcknowledgementsThis material is based upon work supported by the National Science Foundation under Grants1842166 and 1329283. 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. We thank the SPHERE research group for their helpful feedback.References[1] S. Kovalchuk, M. Ghali, M. Klassen, D. Reeve, and R. Sacks, “Transitioning from university to employment in engineering: The role of curricular and co-curricular activities,” in 2017 ASEE Annual Conference & Exposition, 2017.[2] R. Korte, S. Brunhaver, and S. Zehr
practices in US classrooms," Teach. Teach. Educ., vol. 99, p. 103273, Mar. 2021, doi: 10.1016/j.tate.2020.103273[3] M. J. Hannafin, J. R. Hill, S. M. Land, and E. Lee, "Student-centered, open learning environments: Research, theory, and practice," Handbook of Research on Educational Communications and Technology, pp. 641-651, May 2013, doi: 10.1007/978-1-4614- 3185-5_51[4] B. L. McCombs and J. S. Whisler, The Learner-Centered Classroom and School: Strategies for Increasing Student Motivation and Achievement. The Jossey-Bass Education Series. San Francisco, CA: Jossey-Bass Inc., 1997.[5] J. N. Agumba¹ and T. Haupt, "Collaboration as a strategy of student-centered learning in construction technology
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
this lack of representation in higher education engineeringprograms, the University of Lowell S-STEM program, funded by the NSF Scholarships inScience, Technology, Engineering, and Mathematics Program (S-STEM), has the goal torecruit three cohorts of low-income, high-achieving students who wish to pursue a career inhigher education. The UML S-STEM program supports engineering scholars for four years,their last two years of undergraduate school and their first two years of graduate school. Thegoal of the program is to attract and retain diverse engineering S-STEM scholars and preparethem to enter the competitive pool of future faculty candidates. We present our successes and challenges in recruiting the first two cohorts of low-income
electrical at higherrates than traditional students (McNeil, Ohland, & Long, 2016). This paper focused on thestickiness measure for NTS students, and other statistical tests of prediction were outside thescope of this paper. Further research is needed to explore why NTS’ stickiness follows adifferent trend than traditional students. 5 ReferencesAlvord, C. J. (2004). First-time freshman graduation rates Fall 1980-Fall 1997 entering classes (Biennial Report). Retrieved from http://ms7.dpbwin2k.cornell.edu/documents/ 1000024.pdfAstin, A. W., & Astin, H. S. (1992). Undergraduate science education
. Rebecca A. Zulli, Cynosure Consulting c American Society for Engineering Education, 2019 AN ASSET APPROACH TO BROADENING P A R T I C I P AT I O N TIP S A ND T OOLS FOR STRATEGIC P L A NNINGA D R I E N N E S M I T H & R E B E C C A Z U L L I L OW EINTRODUCTION• All too often when thinking about recruiting, supporting, and retaining diverse students in our STEM majors and programs, the situation is approached from a deficit mindset; that is, one that focuses on what students or environments lack that must be remedied.• In our work supporting STEM departments with their broadening participation efforts, we focus on fostering an asset-minded approach to strategic planning.• This approach is grounded
humanistic approach to engineering education, it is a suitable frameworkto evaluate the impact of sociotechnical engineering courses (i.e., a humanistic approach toengineering education) on students’ attitudes toward and perceptions of engineering.Furthermore, this framework explicitly describes and explains the possible connections betweenstudents’ attitudes toward and perceptions of engineering, making it appropriate for a studyinterested in exploring these relationships. The framework has been used to guide how weconceptualize sociotechnical engineering. The instrument used for this study included items andconstructs that align with all three dimensions of Fila et al.’s [1] framework.MethodsSurvey responses collected from undergraduate
WeConclusion[1] P. Altbach, and M. Yudkevich, “Twenty-first century mobility: The role of international faculty,” International Higher Education, vol. 90, no. Summer, pp. 8-10,2017. [Online]. Available: http://dx.doi/orMg/10.6017/ihe.2017.90.9760[ 2] A. Gahungu, A., “Integration of foreign-born faculty in academia: Foreignness as an asset,” The International Journal of Educational Leadership Preparation, vol.6, no. 1, pp. 1-22, Jan-Mar, 2011.[Online]. Available: http://cnx.org/content/m36649/1.2/[3] D. S. Kim, S. Twombly, and L. Wolf-Wendel, “International faculty in American universities: Experiences of academic life, productivity, and career mobility,”New Directions for Institutional Research, vol. 155, pp. 27–46, 2012. [Online]. Available: http
is to prepare the2023 Fall semester implementation. This will include a more detailed implementation frameworkfor 1101 Intro and UNIV 1301 sections. Further, the objective is to expand the interventions toinclude other departments in CECS and possibly to other colleges such as the College of Scienceor College of Business. Our vision is to have a sequence of interventions that continue thisFreshman Year experience with Sophomore, Junior, and Senior Year Innovator Experiences,with an increasing portfolio of skills each year. . T E S M ESS S ESS . T S . S E M T T
theproportional representation issue does not actually create an inclusive environment supportive ofstudent success [5-7]. Just as equality does not equal equity [8]; parity does not equal inclusion[6, 9]. Hurtado and colleagues (2012) pointed out how compositional diversity is only one factorin creating a diverse learning environment [10]. Efforts designed to increase compositionaldiversity neglect the experiences and different combinations of barriers that individuals mustconfront. "Underrepresented" could also be considered a form of spot-lighting, of continuouslyreminding students that each of them is a "representative" for their social identity group(s) [11].This socially-taxing language reminds individuals that their group is judged by the
motivations or reasons fortransferring to a different institution; an important aspect of our study is to untangle thosereasons for engineering transfer students in Texas. Students accumulate transfer student capital,or knowledge about the transfer process, at sending institutions (i.e., the place(s) where studentsbegin their degree paths), receiving institutions (i.e., the final degree-granting institution), andpotentially from non-institutional sources. The development of transfer student capital maycome from experiences related to learning and study skills, course learning, perceptions of thetransfer process, academic advising and counseling, and experiences with faculty. Upon arrivingat the receiving institution, students must adjust to the new
perceptionsof doing engineering work, regardless of occupational title. We also believe that a sequentialregression model will show that engineering belief measures predict a significant proportion ofvariance in perceptions of having jobs “related to” engineering, over and above SCCT variables.AcknowledgementsThe authors would like to thank the Purdue University Davidson School of Engineering, whosePipeline Center funded this project. This work was also supported by the NSF (DGE-1333468).Any opinions, findings, and conclusions or recommendations expressed in this material are thoseof the author(s) and do not necessarily reflect the views of the National Science Foundation.References[1] E. Cech, “The Self-Expressive Edge of Occupational Sex Segregation
Technology, New Delhi.Dr. Janet Callahan, Boise State University Janet Callahan is the Chair of Materials Science and Engineering at Boise State University. Dr. Callahan received her Ph.D. in Materials Science, M.S. in Metallurgy, and B.S. in Chemical Engineering from the University of Connecticut. Her educational research interests include materials science, freshman engineering programs, math education, and retention and recruitment of STEM majors. c American Society for Engineering Education, 2016 Lessons Learned from S-STEM Transfer Student Scholarship ProgramAbstractThis paper describes how the College of Engineering at Boise State University utilized
) Page 26.1305.1 c American Society for Engineering Education, 2015 122th ASEE Annual Conference and Exposition Seattle, Washington, USA, June 14-17, 2015 Zhang, Z., Zhang, M., Chang, Y., Esche, S. K. & Chassapis, C.Real-time 3D Reconstruction for Facilitating the Development of Game-based Virtual Laboratories Zhang, Z., Zhang, M., Chang, Y., Esche, S. K. & Chassapis, C.AbstractGame-based virtual laboratories (GBVLs) represent an important implementation of virtual realityand are often considered to be simulations of real or artificial environments. They are based
knowledge rather than solely consumers of knowledge.BackgroundA 2016 Harvard Business School report found a faltering United States economy and a need forreform [1]. One principal reason for this faltering economy is the United States’ inability todevelop qualified science and engineering (S&E) human capital, in particular women andminorities. However, diversity in the S&E workforce has not improved over the last decade [2];and, given Hispanics aged 21 years and older represent 15% of the U.S. population, a mere 6%of the S&E workforce are Hispanic [2].The Bureau of Labor Statistics has projected that total employment in S&E jobs will increase at afaster rate (1.1% compound annual growth rate) from 2016 to 2026 than employment in
, 2024AbstractThere is substantial opportunity for engineering graduates to enter the workforce to engage in afulfilling career and achieve social mobility. Still, there is a lack of adequate support forlow-income, academically talented students. The purpose of this poster is to describe theinterventions designed to support S-STEM scholarship students at Rowan University in the firstyear of our S-STEM project. Our S-STEM project objectives are threefold: 1) Providescholarships to encourage talented students with low incomes and demonstrated financial need toinitiate and graduate from engineering majors in the College of Engineering at Rowan Universityand subsequently enter the engineering workforce or a graduate program; 2) Develop a supportsystem that
, no. 4, pp. 669–680, 1997, doi: 10.1037/0012-1649.33.4.669.[3] S. Sorby, E. Nevin, A. Behan, E. Mageean, and S. Sheridan, “Spatial skills as predictors of success in first-year engineering,” in 2014 IEEE Frontiers in Education Conference (FIE) Proceedings, Oct. 2014, pp. 1–7. doi: 10.1109/FIE.2014.7044005.[4] Y. Maeda and S. Y. Yoon, “Scaling the Revised PSVT-R: Characteristics of the First-Year Engineering Students’ Spatial Ability,” presented at the 2011 ASEE Annual Conference & Exposition, Jun. 2011, p. 22.1273.1-22.1273.19. Accessed: Dec. 22, 2021. [Online]. Available: https://peer.asee.org/scaling-the-revised-psvt-r-characteristics-of-the-first-year-engineering-students- spatial-ability[5] S. Dautle and S
support provided by the National Science Foundation under grantnumber 2315646. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the authors and do not necessarily reflect the views of the National ScienceFoundation.References[1] K. A. Bartlett and J. D. Camba, “Gender Differences in Spatial Ability: a Critical Review,” Educ. Psychol. Rev., vol. 35, no. 1, p. 8, Jan. 2023, doi: 10.1007/s10648-023-09728-2.[2] J. Wai, D. Lubinski, and C. P. Benbow, “Spatial ability for STEM domains: Aligning over 50 years of cumulative psychological knowledge solidifies its importance.,” J. Educ. Psychol., vol. 101, no. 4, pp. 817–835, 2009, doi: 10.1037/a0016127.[3] S. Sorby, “A Course in Spatial
toward science and engineering we included an adapted version ofthe Middle/High Student Attitudes Toward Science, Technology, Engineering and Math(S-STEM) survey [33]. The scale measures students' attitudes toward their own proficiency inSTEM subjects (e.g., “I know I can do well in science”), the value of STEM toward futureendeavors (e.g., “Knowing about science will allow me to invent useful things”), and interest inSTE|M careers (e.g., “I believe I can be successful in a career in engineering”). The measureshad sufficient levels of reliability on the pre (ɑ = 0.87) and post surveys (ɑ = 0.87) .Additionally, to measure students' perceptions of engineers and engineering we adapted itemsfrom the “What is Engineering?” survey instrument [9]. The
Lab., 2019.[3] D. S. Touretzky, C. Gardner-McCune, F. L. Martin, and D. Seehorn, “Envisioning AI for K-12: What Should Every Child Know about AI?,” In Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, Palo Alto, CA: AAAI Press, 2019.[4] J. McCarthy, “From here to human-level AI,” Artificial Intelligence, vol. 171, no. 18, pp. 1174–1182, 2017.[5] S. Akgun, and C. Greenhow, “Artificial intelligence in education: Addressing ethical challenges in K-12 settings, AI and Ethics, pp. 1-10, 2021.[6] J. Su, and Y. Zhong, “Artificial Intelligence (AI) in early childhood education: Curriculum design and future directions,” Computers and Education: Artificial Intelligence, vol. 3, 2022.[7