Society for Engineering Education, pp. 1-13, Mar. 2013.[3] S. B. Nite, R. M. Capraro, M. M. Capraro, G. D. Allen, M. Pilant, and J. Morgan, “A bridgeto engineering: A personalized precalculus (bridge) program” In 2015 IEEE Frontiers inEducation Conference (FIE), IEEE, pp. 1-6, Oct. 2015.[4] T. J. Pritchard, J. D. Perazzo, J. A. Holt, B. P. Fishback, M. McLaughlin, K. D. Bankston,and G. Glazer, “Evaluation of a summer bridge: Critical component of the Leadership 2.0Program” Journal of Nursing Education, vol. 55(4), pp. 196-202, 2016.[5] L. Cançado, J. Reisel, and C. Walker, “Impacts of a summer bridge program in engineeringon student retention and graduation” Journal of STEM Education, vol. 19(2). pp. C, 2018.[6] N. L. Cabrera, D. D. Miner, and J
-1504576 from the National Science Foundation(NSF). This support is gratefully acknowledged. Any opinions, findings, conclusions, orrecommendations expressed in this paper are those of the writers and do not necessarily reflectthe views if the NSF.IX. ReferencesAllen, D., Murphy, C., Allenby, B., and Davidson, C. (2006). “Sustainable engineering: a model for engineering education in the twenty-first century?” Clean Technologies and Environmental Policy, 8(2), 70-71. 10.1007/s10098-006-0047-6.Auchey, F. L., Mills, T. H., Beliveau, Y. J., and Auchey, G. J. (2000). “Using the learning outcomes template as an effective tool for evaluation of the undergraduate building construction program.” Journal of Construction Education, 5
administrative pathways 2.50 2.00 3.33Note: The results are reported as an average on a scale of 1 to 4 (1 = strongly disagree; 2 = disagree; 3 =agree; 4 = strongly agree).ReferencesBerk, R. A., Berg, J., Mortimer, R., Walton-Moss, B., & Yeo, T. P. (2005). Measuring the effectiveness of faculty mentoring relationships. Academic Medicine, 80(1), 66-71.Blackwell, J. E. (1989). Mentoring: An action strategy for increasing minority faculty. Academe, 75, 8-14.Cawyer, C. S., Simonds, C., & Davis, S. (2002). Mentoring to facilitate socialization: The case of the new faculty member. Qualitative Studies in Education, 15(2), 225-242.Fowler, E. J. (2009). Survey research methods
Worked-Example Instruction in Electrical Engineering: The Role of Fading and Feedback during Problem-Solving Practice, Journal of Engineering Education, 98(1), 83-92.17. Collins, A., J.S. Brown & A. Holum. (1991). Cognitive apprenticeship: making thinking visible. American Educator. 15(3), 6-11,38-39.18. Schön, D.A. (1987). Educating the reflective practitioner: toward a new design for teaching and learning in the professions, San Francisco: Jossey-Bass.19. Gilbuena, D., B. Sherrett, E. Gummer, and M. D. Koretsky. (2011). Episodes as a discourse analysis framework to examine feedback in an industrially situated virtual laboratory project. Proceedings of the 2011 ASEE Annual Conference & Exposition, Vancouver, BC, Canada
, racism, and social marginalization (First edition.). Stylus Publishing, LLC.[9] Mondisa, J. L. & McComb, S. A. (2015) Social community: A mechanism to explain the success of STEM minority mentoring programs. Mentoring & Tutoring: Partnership in Learning. 23(2), 149-163. doi:10.1080/13611267.2015.1049018[10] Maton, K. I., Beason, T. S., Godsay, S., Sto. Domingo, M. R., Bailey, T. C., Sun, S., & Hrabowski, F. A., III. (2016) Outcomes and processes in the Meyerhoff Scholars Program: STEM PhD completion, sense of community, perceived program benefit, science identity, and research self-efficacy. CBE - Life Sciences Education, 15(3), ar48. doi: 10.1187/cbe.16-01-0062[11] Atkins, K., Dougan, B. M
, on questionsrelated to strengths, in general. Research is currently underway led by Co-PI Almeida that isfocused on the intersections of strengths, social identity, context, and social networks. Almeida isutilizing social network analysis [48], survey methods, and qualitative interviewing to advanceunderstanding of how NSF S-STEM ENGAGE activities focused on student personaldevelopment via “strengths training from a social justice perspective in engineering andcomputer science as context” contribute to a) growth of student social networks and b) increasein student resilience, confidence, sense of community, and sense of belonging. In addition, thisresearch investigates whether growth in these areas is related to increased student retention
traditional methods: A six-thousand survey of mechanics test data for introductory physics courses, American Journal of Physics, 66(1), 64-74.[3] Krause, S., Baker, D., Carberry, A., Alford, T., T., Ankeny, C., Brooks, B.J., Koretsky, M., Waters, C., Gib- bons, B. (2015). Effect of Implementation of JTF Engagement and Feedback Pedagogy On Faculty Beliefs and Practice and on Student Performance. 2015 American Society for Engineering Education Conference Proceedings.[4] Bransford, J., Brown, A., and Cocking, R. (2000). How People Learn. National Academy Press.[5] Prince, M., Borrego, M., Henderson, C., Cutler, S., and Froyd, J. (2013). Use of research based instructional strategies in core chemical engineering
relationships between the dimensions of culture and a) student choice ofmajor, and b) student success with a major? RQ3: How do students change over time in their academic programs with respect to thedimensions of culture? RQ4: What factors affect those changes, e.g., pedagogical practices, curriculum, instructors? RQ5: Do the relationships in RQ1-4 vary with demographic indicators, e.g., race or gender? RQ6: What patterns of pedagogical practice operate within academic disciplines?To address these issues, the grant is being developed in a 4-year study to investigate patterns ofcultural traits in students across disciplines, and to build an actionable theory of engineeringculture that can support pedagogies of inclusive and collaborative
conceptually and epistemologically during the course of their first 2 years of practice? a. How do the changes inspired in undergraduate engineering programs help or hinder engineers through their first 2 years of practice? b. How do engineers use the engineering content (laws, equations, computational skills, understanding of fundamental phenomena) they remember? 3. What conceptual and epistemological differences are there between the sociocultural contexts represented in our sample?Activities Page 23.1365.2Participant population There are two cohorts of participants. Cohort 1 has a total of
provided the big picture status of the project.Over the course of this project, students were successful in characterizing the dynamic forces andvibrations experienced via a design of experiments (Figure 2(a)). These results along with thegraduate mentor’s numerical analysis have been documented as a peer-reviewed conferenceproceeding [1] and eventually as an archival journal publication [2]. Students also finalized thedesign of an actuator and manufactured a functional prototype (Figure 2 (b) and (c)) along withperforming psychophysical tests to understand human perception to the vibration and its changes(Figure 2(d)). The human perception study provided useful information to determine theessential aspects of force and vibration that needed to be
,and networking in professional settings. The project team approached alumni who had A)previously held an F1 visa, B) pivoted from traditional teaching/research focus to industry, andC) intentionally sought leadership roles before and after graduation. CAR 551 students thendeveloped a series of questions to prepare for mentoring sessions with the alumni.Through in-person and virtual meetings with these former F1 students, participants more openlydiscussed how to maintain their identities as a scientist or an engineer, balance personal goals,and skills needed for advancement. Having access to alumni with direct experience managingwork visa timelines, academic obligations, and individual goals was a turning point for thestudents. As they
research.Dr. Abhik Roy, West Virginia University Abhik Roy is a professor educational psychology in the Department of Learning Sciences & Human Development (https://lshd.wvu.edu/) within the College of Education & Human Services at West Virginia University. Dr. Roy holds a Ph.D. in Program Evaluation with expertise in data science, visualization, and social network analysis and is an evaluator on multiple federal grants spanning both the National Science Foundation and the National Institutes of Health. He currently conducts research in (a) the use of machine learning to evaluate programs, (b) using predictive networks to assess change, and (c) deep learning architectures for text classification.Dr. Karen E. Rambo
withinnovative technologies. The researchers retrieved intervention content areas, interventionpedagogical practices, intervention durations (e.g., implemented for a unit, a semester, a year, ormultiple years), and whether the intervention consisted of an explicit career developmentcomponent (e.g., career counseling), from the primary studies. Intervention characteristics werecoded as moderators for this analysis. This review utilized a broad definition of “careeroutcomes” in order to capture any study that should be included for meta-analysis. Following thework of STELAR scholars, STEM career-related outcomes were coded into four categories (a)dispositions, (b) knowledge, (c) skills, and (d) actions [1]. For example, attitude toward STEMcareers was
), ● Strategies for dealing with power differentials and competition for scarce resources (political issues like, for example, addressing differences between tenure-track and non- tenure track positions), ● Strategies for dealing with cultural aspects of an organization (symbolic issues like, for example, dealing with how change impacts perceived rigor in different departments)Our REDPAR team has developed some initial generalizable strategies and tips for dealing withsome of the aforementioned obstacles, such as dealing with leadership succession challenges,shared vision development, development of strategic partnerships, and communicating aboutchange (REDPAR, 2017 a, b, 2018, 2022). For example, during the working session with
) were enrolled in MATH 140 and PHYS 211 courses during the fall 2022 semester of theirfreshman year. However, for the first time, two courses were block scheduled into one “virtually”integrated MATH 140/PHYS 211 course that was taught jointly by mathematics and physicsprofessors in one classroom for 9 contact hours each week. We used “virtual” integration ratherthan creating a formally new experimental course because: (a) creating new courses requires asignificant amount of time for approval at Penn State, where the process of curriculardevelopment is centralized and involves all 20 undergraduate Commonwealth campuses; (b) itmay have potential negative effects on the transfer of credits to other institutions and the processof changing majors
, “Comparing student satisfaction with distance education to traditional classrooms in higher education: A meta-analysis,” American Journal of Distance Education, vol. 16, no. 2, pp. 83–97, 2002.[8] R. M. Bernard, P. C. Abrami, Y. Lou, E. Borokhovski, A. Wade, L. Wozney, P. A. Wallet, M. Fiset, and B. Huang, “How does distance education compare with classroom instruction? A meta-analysis of the empirical literature,” Review of Educational Research, vol. 74, no. 3, pp. 379–439, 2004.[9] C. Klimas, “Twine.” https://twinery.org/. Accessed: 14 February 2023.[10] M. Soliman, “Gemba Walks the Toyota Way: The Place to Teach and Learn Management,” pp. 2-5, October 2020. Print.[11] B. Rammstedt and O. P. John, “Measuring
the Research. Proceedings of the 120th ASEE Annual Conference & Exposition, Atlanta, GA, June 23-26.[3] Brown, S., L Flick, and T. Fiez (2009), “An Investigation of the Presence and Development of Social Capital in an Electrical Engineering Laboratory”, Journal of Engineering Education, 98(1). 93-102.[4] Etcheverry, E., Clifton, R., & Roberts, L. (2001). Social Capital and Educational Attainment: A Study of Undergraduates in a Faculty of Education. Alberta J. of Educational Research, 47(1). 24-39.[5] Gates, S.J. and Mirkin, C. (2012). Engage to Excel. Science, 335(6076), 1545.[6] Goodwin, B., and Miller, K. (2013). Evidence of Flipped Classrooms is Still Coming In. Educational Leadership 70(6), 78-80.[7] Lage, M.J., Platt
Research Experiences”. Science, Vol. 316, No. 24, pp. 548-549.10. Yoder, B. Engineering by the Numbers: www.asee.org/papers-and-publications/publications/14_11-47.pdf.11. Huston, J.C. and Burnet, G. (1982). “Iowa State University Senior Engineering Student Attitudes about Graduate Study”, Proceedings of the 1982 Frontiers in Education Conference, Columbia, SC.12. Carpinelli, J. D., Hirsch, L., S., Kimmel, H., Perna, A., & Rockland, R. (2007). “A Survey to Measure Undergraduate Engineering Students’ Attitudes toward Graduate Studies”, Paper presented at the International Conference on Engineering Education, Honolulu, HI.13. Hirsch, L. S., Carpinelli, J. D., Kimmel, H., and Perna, A. (2008). “Measuring Engineering
ideas were accurate. Examples of apre and post-concept map are shown in Figures 1 a and b. Page 26.1251.7Figure 1a. Example of a Systems Medicine Concept Map at Start of Program. Page 26.1251.8Figure 1b. Example of a Systems Medicine Concept Map at End of Program.Figure 1a shows a map that is primarily “linear” in terms of the branches out from the center-point of Systems Medicine. There are some linkages between the branches, but many aremissing, such as a complete disconnect between experiments (bottom center) and other branchescontaining lab work, analysis tools
Research Experiences for Teachers (RET) site? Three perspectives on Big Data and Data Science Stephanie B. Philipp, Olfa Nasraoui, and Jason Immekus University of Louisville College of Education and Human Development & J.B. Speed School of Engineering Louisville, KY 40292 stephanie.philipp@louisville.edu olfa.nasraoui@gmail.edu jason.immekus@louisville.eduAbstractThis paper will share initial findings from the first year of a Research Experience for Teacherssite, supporting nine secondary STEM teachers from diverse schools in six-week
explanation may point out limitationsof the other item (e.g., choosing Option A because “Option B cannot carry a thing.”). We applieda sentiment classifier (NLTK Vader [24]) to determine the degree that each comment waspositive, negative, neutral, or compound. Our findings showed a statistically significantdifference in the positive sentiment score when students referred to selected options, t(146) =5.87, p < .01. However, whether student comments related to the selected option or the notselected option, students used similar levels of neutral and negative words in their reasoning. A closer look at students’ positive comments revealed that students used shortercomments to give evidence for selecting an option. The low number of compound
, C. Regalia, C. Manzi, J. Golledge, and E. Scabini, “Beyond self-esteem: Influence of multiple motives on identity construction.,” J. Pers. Soc. Psychol., vol. 90, no. 2, p. 308, 20060313, doi: 10.1037/0022-3514.90.2.308.[9] J. L. Huff, J. A. Smith, B. K. Jesiek, C. B. Zoltowski, and W. C. Oakes, “Identity in Engineering Adulthood: An Interpretative Phenomenological Analysis of Early-Career Engineers in the United States as They Transition to the Workplace,” Emerg. Adulthood, vol. 7, no. 6, pp. 451–467, Dec. 2019, doi: 10.1177/2167696818780444.[10] T. Jungert, “Social identities among engineering students and through their transition to work: a longitudinal study,” Stud. High. Educ., vol. 38, no. 1, pp. 39–52, Feb
, “Supplemental Instruction Integrated Into an Introductory Engineering Course,” Journal of Engineering Education, October 1998, pp. 377-383.)[3] Robert A. Blanc, Larry E DeBuhr and Deanna C. Martin, “Breaking the Attrition Cycle, The Effects of Supplemental Instruction on Undergraduate Performance and Attrition,” Journal of Higher Education, Volume 54, Number 1, 1983, pp. 80-90.[4] John Flavell, “Metacognition and Cognitive Monitoring A New Area of Cognitive – Developmental Inquiry,” American Psychologist, Vol. 34, No. 10, pp. 906-911, October 1979.[5] John Flavell, “Metacognitive Aspects of Problem Solving,” in The Nature of Intelligence, Lauren B. Resnick ed., Lawrence Erlbaum Associates, Hilsdale , N.J., 1976.[6
experiencing a nano-lesson or series oflessons?” The S-STEM survey was designed for K-12 students. The survey invites students toprovide information about their attitudes toward science, technology, engineering and mathsubjects, postsecondary pathways, and career interests. The first four sections of the survey haveitems that load onto one four constructs. Each construct contains a series of items set on a 5-pointLikert-type scale ranging from strongly disagree (1) to strongly agree (5). The four constructincluded the following (for construct items, see Appendix B):1. Math: Mathematics self-efficacy, interests, and perceptions of its future value2. Science: Science self-efficacy, interests, and perceptions of its future value3. Engineering
teaching awards, two Professorships, two national ASEE teaching awards, and is internationally recognized in his primary research field. c American Society for Engineering Education, 2016 Promoting Research and Entrepreneurship Skills in Freshman Engineering Students: A Strategy to Enhance Participation in Graduate and Enrichment ProgramsAbstractThis paper describes the structure, implementation strategy, and early results of an undergraduateNSF Scholarships in Science, Technology, Engineering, and Mathematics (S-STEM) Programaimed at: (a) increasing the number of graduating engineers with research and entrepreneurshipexperience, (b) preparing students for the future needs
foundational level, we are establishing empirically informed conceptualframeworks and associated survey instruments that help educators and resources understand (a)what knowledge gains result when students engage in specific reflection activities and (b) whattypes of reactions students have when they engage in the activity. On a practical level, we areexploring ways to distribute our conceptual frameworks alongside relevant information. With ourwork, we aim to advance conversations about potential impact of reflection and conversationsabout how to leverage reflection in teaching. In the paper and poster, we will focus on both thefoundational insights and practical resources that are emerging from this work.IntroductionEducation involves identifying
only Cohort 2 increasedsignificantly. On the measure of efficacy for engineering design, both Cohort 1 and 2 increased,though only Cohort 2 increased significantly. The difference in Cohort 1 and 2 may be the resultof improved ChangeMaker K12 materials and experiences. Overall, results suggest the materialscan have a positive impact on TC capacity for teaching systems thinking and engineering design.References[1] NGSS Lead States. 2013. Next Generation Science Standards: For States, By States. Washington, DC: The National Academies Press.[2] Meadows, D. H. (2008). Thinking in systems: A primer. White River Junction, VT: Chelsea Green[3] Senge, P., Cambron-McCabe, N., Lucas, T., Smith, B., Dutton, J., and Kleiner, A. (2012). Schools
fieldof SciTS, including the five domains of team science competencies [4]: 1) building genuinerelationships, 2) team communication, 3) managing team research, 4) collaborative problem-solving and creativity, and 5) leadership.Some of the key topics covered across the workshops included: a) expanding our ability toparticipate in a shared vision, b) understanding the importance of diversity and practicing usingtools for inclusive teamwork, c) enhancing our awareness of developing shared language, d)exploring and practicing collaborative writing, e) drafting team charters, and f) developingguidelines for decision making.We gathered several key takeaways from our workshop reflections: • Being mindful of the value of team members when they are
Dev. Quart, vol. 48, no. 1, pp. 3-18, 1999.(3) J. S. Eccles (Parsons), T. F. Adler, R. Futterman, S. B. Goff, C. M. Kaczala, J. L. Meece, and C. Midgley, “Expectancies, values, and academic behaviors,” in Achievement and Achievement Motivation, J. T. Spence, Ed. San Francisco, CA: W. H. Freeman, 1998.(4) S.R. Brunhaver, H.M. Matusovich, S. Sheppard, R.A. Streveler, C. Carrico, and A. Harris,“Engineering students’ professional pathways. A longitudinal mixed-methods study,” Proceedings of the Annual Conference of the American Society for American Engineering, June 26-29, 2016. New Orleans, LA.(5) C. Carrico, A. Harris, H.M. Matusovich, S.R. Brunhaver, R.A. Streveler, and S. Sheppard, “Helping engineering students get jobs
Performance. Journal of Vocational Behavior, 1994. 45(1): p. 79-122.13. Markus, H. and P. Nurius, Possible Selves. American Psychologist, 1986. 41(9): p. 954- 969.14. Eccles, J.S., Families, schools, and developing achievement-related motivations and engagement, in Handbook of socialization: Theory and research, J.E. Grusec and P.D. Hastings, Editors. 2007, Guilford Press: New York, NY. p. 665-691.15. Hidi, S. and K.A. Renninger, The Four-Phase Model of Interest Development. Educational Psychologist, 2006. 41(2): p. 111-127.16. Thomson, A.M. and J.L. Perry, Collaboration processes: Inside the black box. Public administration review, 2006. 66(s1): p. 20-32.17. Wood, D.J. and B. Gray, Toward a Comprehensive Theory of Collaboration