to Out-of-Class Participation: Profile of Civil Engineering Student Engagement,” J. Prof. Issues Eng. Educ. Pract., vol. 144, no. 2, p. 04017015, 2018.[7] A. J. Barlow, B. D. Lutz, N. P. Pitterson, N. Hunsu, O. Adesope, and S. A. Brown, “Development of the Student Course Cognitive Engagement Instrument ( SCCEI ),” Rev., 2018.[8] B. D. Lutz, A. J. Ironside, N. Hunsu, C. J. Green, S. A. Brown, and O. Adesope, “Measuring Engineering Students ’ In-class Cognitive Engagement : Survey Development informed by Contemporary Educational Theories,” ASEE Annu. Conf. Expo. Proc., 2018.[9] A. J. Ironside et al., “Incorporating Faculty Sense Making in the Implementation and Modification of an Instrument to
terminology was a concern of theparticipants. Participant A: “..sometimes some of the students even have a hard time understanding bending moment and torque. They are taking Physics at the same time and the terminology doesn’t always match. The Physics’ instructor uses torque a lot. I don’t know if anyone else..” Participant B: “Yeah my students have come with the same thing. They use torque and moment is a new term for them. So they want to know what the difference between moment and torque is.” Page 26.980.6In Physics (often taken before or concurrently with Mechanics of Materials), students are taughtthat
; Exposition, 2020. [7] A. E. Foley, J. B. Herts, F. Borgonovi, S. Guerriero, S. C. Levine, and S. L. Beilock, “The Math Anxiety-Performance Link,” Current Directions in Psychological Science, vol. 26, no. 1, pp. 52–58, Feb 2017. [Online]. Available: http://journals.sagepub.com/doi/10.1177/0963721416672463 [8] N. von der Embse, D. Jester, D. Roy, and J. Post, “Test anxiety effects, predictors, and correlates: A 30-year meta-analytic review,” Journal of affective disorders, vol. 227, pp. 483–493, 2018. [9] N. Spadafora, E. L. Murphy, D. S. Molnar, and D. Zinga, “Test anxiety in potential first-generation students: A longitudinal examination of the role of psychological needs,” Journal of Teaching and Learning, vol. 14
. (2011). Engineering Education Discourses on Underrepresentation: Why Problematization Matters. International Journal of Engineering Education, 27(5), 1117. 4. Lewis, B. F. (2003). A critique of literature on the underrepresentation of African Americans in science: Directions for future research. Journal of Women and Minorities in Science and Engineering, 9(3&4). 5. Moore, J. L. (2006). A qualitative investigation of African American males' career trajectory in engineering: Implications for teachers, school counselors, and parents. Teachers College Record, 108(2), 246. 6. May, G. S., & Chubin, D. E. (2003). A retrospective on undergraduate engineering success for underrepresented minority
wealth,” Race Ethn. Educ., vol. 8, no. 1, pp. 69–91, 2005.[18] C. G. Vélez-Ibáñez and J. B. Greenberg, “Formation and transformation of funds of knowledge among U.S.-Mexican Households,” Anthropol. Educ. Q., vol. 23, no. 4, pp. 313–335, 1992.[19] A. L. Pawley and C. M. L. Phillips, “From the mouths of students: Two illustrations of narrative analysis to understand engineering education’s ruling relations as gendered and raced,” presented at the ASEE Annual Conference, Indianapolis, IN, 2014.[20] J. Walther, N. W. Sochacka, and N. N. Kellam, “Quality in interpretive engineering education research: reflections on an example study: Quality in interpretive engineering education research,” J. Eng. Educ., vol. 102, no. 4, pp
. J. Eng. Educ., pp. 1–16, 2020, doi: 10.1080/03043797.2020.1835828.[5] A. P. Smith, Student Workload , Wellbeing and Academic Attainment. Springer International Publishing, 2019.[6] A. Danowitz and K. Beddoes, “Characterizing mental health and wellness in students across engineering disciplines,” 2018.[7] W. Cao, Z. Fang, G. Hou, M. Han, X. Xu, and J. Dong, “The psychological impact of the COVID-19 epidemic on college students in China,” Psychiatry Res., vol. 287, no. March, p. 112934, 2020, doi: 10.1016/j.psychres.2020.112934.[8] C. A. Perz, B. A. Lang, and R. Harrington, “Validation of the Fear of COVID-19 Scale in a US College Sample,” Int. J. Ment. Health Addict., pp. 1–11, 2020, doi
Paper ID #33294A Study on the Impact of Using Industry Standard Tools and Practices onSoftware Engineering Courses ProjectsDr. Tajmilur Rahman, Gannon University Tajmilur Rahman PhD, is an assistant professor in the department of Computer and Information Science at Gannon University in Erie, Pennsylvania. His overarching research interest is to investigate release engineering practices in software systems. His research works are driven by the desire to determine the empirical factors that lead to a successful software development and release. His research interests also include understanding the significance of software
, "Developing an Integrated Curriculum-wide Teamwork Instructional Strategy," in ASEE Annual Conference & Exposition, Salt Lake city, UT, 2018.[9] A. S. o. C. Engineers, "the Vision for Engineering in 2025," ASCE, Reston, VA, 2007.[10] A. S. o. M. Engineers, "Vision 2030: Creating the Future of Mechanical Engineering Education," ASME, NY, 2012.[11] S. G. S. C. H. L. D. K. L. G. E. Ö. L. M. &. T. G. Sheppard, "Exploring the Engineering Student Experience: Findings from the Academic Pathways of People Learning Engineering Survey (APPLES) (TR-10-01)," Center for the Advancement for Engineering Education., Seattle WA, 2010.[12] K. J. B. Anderson, S. S. Courter, T. McGlamery, T. M. Nathans-Kelly and C. G. Nicometo
. The FE, for example, tends toconcentrate on engineering subject-area and knowledge acquisition. Less attention is devoted tothe engineering skills students may or may not have developed. Some have argued that FE scoresare appropriate for assessing certain of ABET's EC2000 Criterion 3.a-k outcomes, specifically"Criterion 3: (a) an ability to apply knowledge of mathematics, science, and engineering; (b) anability to design and conduct experiments, as well as to analyze and interpret data; (c) an abilityto design a system, component, or process to meet desired needs; (e) an ability to identify,formulate, and solve engineering problems; (f) an understanding of professional and ethicalresponsibility, and (k) an ability to use the techniques
., 2002.[5] B. Palmer and R. M. Marra, “Individual Domain-Specific Epistemologies: Implications for Educational Practice,” in Knowing, Knowledge and Beliefs, M. S. Khine, Ed. Dordrecht: Springer, 2008, pp. 325–350.[6] J. H. Yu and J. Strobel, “Instrument Development : Engineering-specific Epistemological , Epistemic and Ontological Beliefs,” Proc. Res. Eng. Educ. Symp. 2011 - Madrid, pp. 1–8, 2011.[7] J. P. Gee, How to do discourse analysis: A toolkit., 2nd ed. Thousand Oaks, CA: Routledge, 2014.[8] J. Maeda, “STEM + Art = STEAM,” STEAM J., vol. 1, no. 1, 2013.[9] A. Oner, S. Nite, R. Capraro, and M. Capraro, “From STEM to STEAM: Students’ Beliefs About the Use of Their Creativity,” STEAM J., vol. 2, no. 2
and I want people to think highly of me. I care what people think about me a lot, so I…just want – I just want to fit in and I think that would help me fit in.” UrsaAt the end of the interview, Ursa expressed this when I asked her if she had any parting thoughts.She is speaking directly to me, the PI. “I don’t want you to think of me as a person that – that’s lazy. I want you to think highly of me. Not too highly but I want to be just like the same level as everybody else.” UrsaUrsa is concerned with what I think of her based on our short time together for the interview.THEME IV: “If plan a and b don’t work, there’s plan c, plan d, all the way to z.”This theme relates to help-seeking behavior as a learned action or skill
. Csikszentmihalyi, M., Flow: The psychology of optimal experience. 1990, HarperPerennial: New York. p. 43-93.12. Coller, B. and D. Shernoff. An initial analysis of student engagement while learning engineering via video game. 2010. Louisville, KY, United states: American Society for Engineering Education.13. Froehlich, J., et al. Increasing the breadth: Applying sensors, inference and self-report in field studies with the MyExperience tool. 2007. San Juan, Puerto rico: Association for Computing Machinery.14. Stone, A. and S. Shiffman, Capturing momentary, self-report data: A proposal for reporting guidelines. Annals of Behavioral Medicine, 2002. 24(3): p. 236-243.15. Patton, M.Q., Qualitative Research & Evaluation
AC 2010-91: A PILOT VALIDATION STUDY OF THE EPISTEMOLOGICALBELIEFS ASSESSMENT FOR ENGINEERING (EBAE): FIRST-YEARENGINEERING STUDENT BELIEFSAdam Carberry, Tufts University Adam R. Carberry is a Doctoral Candidate in Engineering Education in the Tufts University Math, Science, Technology, and Engineering Education program. He holds an M.S. in Chemistry from Tufts University and a B.S. in Material Science Engineering from Alfred University. He is currently working at the Tufts University Center for Engineering Education and Outreach as a research assistant and manager of the Student Teacher Outreach Mentorship Program (STOMP).Matthew Ohland, Purdue University Matthew W. Ohland is an Associate Professor in
Ajzen’s theory of planned behavior, behavioral intentions, such as plans to major inor work in engineering, are informed by three factors: (a) attitude toward the behavior, (b)subjective norms, and (c) perceived behavioral control [5]. Ajzen defined attitude toward thebehavior as the general disposition toward performing a particular behavior; thus behavioralintentions serve as proxies for motivations. In general, the magnitude of a behavioral intention istheorized to correspond to the likelihood of behavioral performance.Ajzen recognized that general dispositions toward behaviors alone are poor predictors ofbehaviors. Thus, he added the concepts of subjective norms and perceived behavioral control toaid in explaining additional variation in
out: Classification and it consequences. Cambridge, MA: MIT Press.10. Horn, I. S., Kane, B. D., & Wilson, J. (2015). Making Sense of Student Performance Data Data Use Logics and Mathematics Teachers’ Learning Opportunities. American Educational Research Journal.11. Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. New York: Cambridge University Press.12. Lave, J. (1988). Cognition in Practice. New York: Cambridge.13. De Fina, A., Schiffrin, D., & Bamberg, M. (Eds.). (2006). Discourse and identity (Vol. 23). Cambridge University Press.14. Bauman, R., & Briggs, C. L. (1990). Poetics and performance as critical perspectives on language and social life. Annual
Engineering Programs,” ABET, Inc.,November 17, 2007, accessed at http://www.abet.org/Linked%20Documents-UPDATE/Criteria%20and%20PP/E001%2008-09%20EAC%20Criteria%2011-30-07.pdf. 2. Miller, R. L. and Olds, B. M., “A Model Curriculum for a Capstone Course in Multidisciplinary EngineeringDesign,” Journal of Engineering Education, October 1994. 3. Whitman, L.E., Malzahn, D. E., Chaparro, B.S., Russell, M., Langrall, R., and Mohler, B.A., 2005, “AComparison of Group Processes, Performance, and Satisfaction in Face-to-Face Versus Computer-MediatedEngineering Student Design Teams,” Journal of Engineering Education, July 2005. 4. McKenzie, L.J., Trevisan, M.S., Davis, D.C., and Beyerlein, S.W., 2004, “Capstone Design Courses andAssessment: A
women and contributing to the maintenance ofgender segregation in organizations ( p.139)1Work organizations in the United States are primarily male-dominated1 in that men continue tooccupy the important and powerful positions in their workplaces. In large-scale federal/state-sponsored organizations and economic organizations, benefits and power are concentrated in thehands of the male workers,b a truth not challenged in academic contexts until second wavefeminism in the early 1970s. Eminent feminist scholars questioned and challenged this taken-for-granted phenomenon of women’s marginalization in different organizational settings, includingin academia.8; 5; 7; 9 Thus scholars started examining workplace factors like income, rewards,promotion
toward becomingindependent learners which can be compared to self-regulated learners12,13. Because the trainingtutors receive impacts how the peer tutors engage each student, it is important that the training iswell-rounded and consistent to enable each peer tutor to adapt to each student’s learningpreferences. Building a culture of learning amongst the tutors can help to foster motivation14 .Self-regulated learning holds promise for reducing student attrition13. Not only are tutors trained on the Socratic method of inquiry which students canrepurpose for themselves as they grow as learners, tutors are also trained on setting an agendaand the steps of an agenda (see Appendix B for details). This agenda can be repurposed by anindividual to
material existence that comes from earning an engineeringdegree. Our analysis of the meritocracy of difficulty view is that this has been cultivated in thesame void that produced the engineering as lifestyle view. Our reasoning is as follows: a)because engineering students don’t yet have solid images of the actual qualities that distinguishspecific engineering craft skills from other fields that would warrant a high salary andprofessional security, b) they must construct—as all people do as story-tellers and sense-makersabout their own lives—reasons for this expected future bounty. The belief they construct is c)because they work harder now, they deserve more later.Before proceeding with our analysis we want to offer one clarification on the use
measures to quantitative results. More importantly, segmenting therespondents by demographic groups will reveal whether research opportunities are currentlystructured to encourage inclusive participation and, if not, which groups are beingmarginalized. This aspect will be especially important when designing programs to improveaccess to these activities for all students.References[1] E. Seymour, A.-B. Hunter, S. L. Laursen, and T. Deantoni, “Establishing the benefits of research experiences for undergraduates in the sciences: First findings from a three- year study,” Sci. Educ., vol. 88, no. 4, pp. 493–534, 2004.[2] A.-B. Hunter, S. L. Laursen, and E. Seymour, “Becoming a scientist: The role of undergraduate research in
frameworkin engineering. Work evaluating the nature of engagement linked to higher levels of learning inengineering classrooms would provide value feedback to faculty seeking to modify theirclassrooms. Further work is needed in the realm of survey development to better understand theways in which students can provide feedback with accuracy.References[1] R. S. Heller, C. Beil, K. Dam, and B. Haerum, “Student and Faculty Perceptions of Engagement in Engineering,” J. Eng. Educ., vol. 99, no. 3, pp. 253–261, Jul. 2010.[2] K. A. Smith, S. D. Sheppard, D. W. Johnson, and R. T. Johnson, “Pedagogies Of Engagement: Classroom Based Practices,” J. Eng. Educ., no. January, pp. 87–101, 2005.[3] H. L. Chen, L. R. Lattuca, and E. R. Hamilton
Paper ID #14928Instructors Playing the Role of Developer and Implementer: Impacts on Ma-terial DevelopmentGrace Panther, Oregon State University Grace Panther is a doctoral student conducting research in engineering education. She has experience conducting workshops at engineering education conferences and is currently a guest editor for a special issue of European Journal of Engineering Education on inclusive learning environments. Her research includes material development, faculty discourses on gender, and defining knowledge domains of students and engineers.Dr. Devlin Montfort, Oregon State University Dr. Montfort
, teachers, and students. British Journal of Educational Psychology, 75(4), 645-660.18. Lord, S. M., Prince, M. J., Stefanou, C. R., Stolk, J. D., & Chen, J. C. (2012). The effect of different active learning environments on student outcomes related to lifelong learning. International Journal of Engineering Education, 28(3), 606-620.19. Shekar, A. (2007). Active learning and reflection in product development engineering education. European Journal of Engineering Education, 32(2), 125-133.20. Jonassen, D., Strobel, J., & Lee, C. B. (2006). Everyday problem solving in engineering: Lessons for engineering educators. Journal of Engineering Education, 95(2), 139-151.21. Wu, Y.-T., & Tsai, C.-C. (2005). Effects of constructivist
Theory of Career and Academic Interest, Choice, and Performance,” J. Vocat. Behav., vol. 45, pp. 79–122, 1994.[19] R. W. Lent, S. D. Brown, and G. Hackett, “Social Cognitive Career Theory,” in Career Choice and Development, 4th ed., D. Brown, Ed. San Francisco, CA: Jossey-Bass, 2002, pp. 255–311.[20] K. M. Ehlert, M. L. Rucks, B. A. Martin, and M. K. Orr, “Predictors of Matriculation in Intended Major in a First-Year Engineering Program,” in Proceedings of the American Society for Engineering Education Annual Conference & Exposition, 2019.[21] N. L. Veurink and J. Foley, “How Well Do They Match? Does High Confidence in Selection of Major Translate to High Graduation Rates in a Major?,” in
effectiveness of the strategies for helping your students learn the content, skills, and mindsets within engineering. 2. Select one strategy from the workshop, and explain how you can use it in your current or future teaching. Your explanation should include: a. A class context in which you will implement this strategy b. The reason you chose this particular strategy and how it will help your students learn c. How you will implement it in your teaching, and d. What challenges might you encounter in implementing this strategyUnlike typical program evaluation questions, which tend to focus on the value of the seminar orthe strength of the facilitator,11 these
organizing the research which includes four issues: (a) changing the culture; (b)catalyzing conversations about learning outcomes; (c) promoting adaptation; and (d) improvingfaculty development. In the following sections, we rationalize our choice of these four issues andoffer sample research questions related to each one.Changing the CultureFrequently, papers or talks promoting adaptation of evidence-based teaching approaches call forchanging the culture7,8. However, the term “culture” is too often used as a catchall term fornumerous things that need to be changed. Further, there are few useful descriptions of culture inacademic settings and few specifics about what aspects of the culture should be changed. As aresult calls to change the culture
Paper ID #6432Investigating the Impact of Model Eliciting Activities on Development of Crit-ical ThinkingDr. James A. Kaupp, Queen’s University Researcher and Adjunct Professor (Msc ’06, PhD ’12) at Queen’s University, Kingston, Ontario, Canada in the Faculty of Engineering and Applied Science. Educational research interests include engineering education development, critical thinking & problem solving, outcomes based assessment and interactive learning through technology. Scientific interests include regenerative medicine, tissue and biomedical engineering and human biomechanics.Dr. Brian M Frank P.Eng., Queen’s
Paper ID #9524Expert Innovators and Innovation Education: Mental Models in PracticeDr. Eden Fisher, Carnegie Mellon University Eden Fisher is Director of the Masters Program in Engineering & Technology Innovation Management (E&TIM) and Professor of the Practice at Carnegie Mellon University. She earned an A.B. in Chemistry from Princeton University and a Ph.D. in Engineering & Public Policy from Carnegie Mellon University. Her experience includes over twenty years in industrial technology planning and innovation management.Dr. Indira Nair, Carnegie Mellon University Indira Nair retired from Carnegie Mellon
. Basic and Applied Social Psychology, 30, 208-218.11. Spade, J. Z., Columba, L., & Vanfossen, B. E. (2007). Tracking in mathematics and science: Courses and course selection procedures. In J. H. Ballantine & J. Z. Spade, Eds. In Schools and society: A sociological approach to education, (3rd ed.), pp. 286-297. Thousand Oaks, CA: Sage.12. Larimore, J.A., & McClellan, G.S. (2005). Native American student retention in U.S. postsecondary education. New Directions for Student Services, 109, 17-32.13. Nelson-Barber, S., & Estrin, E.T., (1995). Culturally responsive mathematics and science education for Native American students. San Francisco, CA: Far West Laboratory for Educational Research and Development.14. Jacobs, J
, Inference and Consciousness, Harvard University Press, 1983.15. Rouse, W. B. & Morris, N. M., “On looking into the black box: Prospects and limits in the search for mental models”, Psychological Bulletin, 100, 1986, pp 349-363.16. von Hippel, E., The Sources of Innovation, Oxford University Press, 1994.17. Spear, S., The High-Velocity Edge: How Market Leaders Leverage Operation Excellence to Beat the Competition, McGraw-Hill, 2010.18. Simon, H. A., “What We Know About Learning”, Journal of Engineering Education, October 1998, pp. 343-348. Page 22.1100.12