a student enrolls into an institution perceivedas having a particular identity, s/he must engage with that identity and ultimately choose whetherto accept or reject it as personally relevant and desirable or tolerable. Engineering students,particularly at a STEM-intensive institution, must engage with the broader cultural perceptionthat engineers are geeks; at MT, students often refer to themselves and their peers as “engi-nerds,” so closely is the identity of an engineer tied to being geeky or nerdy. APS data indicatethat this process of identification is emergent; first-year students react differently than second-year students to the connection between geeks and engineers. The shift among MT students is todistance themselves from being
common knowledge in the field of engineering education that numbers of women andminorities obtaining engineering degrees is far below their representation in the U.S.population[1]. Many studies have sought to discern reasons for lack of representation of womenand minorities in science, mathematics and engineering degree programs. Studies related tominority students point to, among other factors, lack of pre-college academic preparation,financial difficulties, barriers related to being first generation college students [e.g. 2, 3, 4] and socio-cultural factors [5]. Studies related to female student underrepresentation in S&E fields havesuggested that women leave not from a lack of academic ability, but among other reasons,because of socio
Written System Interactions Constitutive Eqn Principles 0 absent absent absent absent absent Description Picture present Incorrect Incorrect present but Incorrect 1 but missing governing constitutive missing heat interactions heat exchanger principles equation(s) exchanger
with mention of scientific study. The information presented was simplyaccessed and assimilated into their solutions without any concerns for accuracy or credibility.The subjects did not also address the limitations in the source that reported data only to a speedof 8 m/s for helmets, but relied on concept based assumptive relationships between the height ofthe hill, co-efficient of friction and velocity, of which the accuracy and implications remainedunquestioned.Analysis of Engineering Post-test Safety Recommendations UnitIn this post-test, the subjects based their conclusions off of their initial analysis supplemented byconcepts and supplemental information. There were minimal conclusions based off ofassumptions formed by first person or
idea of possible selvesand identity play to examine this process.Interactive Response and InteractionsFrom our early observations of the students’ use of the portfolios, we could see that identitywork and play occur in a variety of contexts, mediated by individual reflections as well as theresponses and interactions of other individuals. These observations informed our categorizationof “Interactive Response” (IR) as a site of learning mediated by diverse interactions with bothpeople (instructors, peers, friends/family, clients) and symbolic artifacts (e.g., professional codesof ethics). In this conception of IR, we pick up on Hattie and Timperley’s broader notion offeedback as provided by multiple “agent[s]”[8] in response to a particular
. Mizukami, Student Assessment of a Problem- Based Learning Experiment in Civil Engineering Education. Journal of Professional Issues in Engineering Education & Practice, 2005. 131(1): p. 13-18.22. Downey, G.L., et al., The globally competent engineer: working effectively with people who define problems differently. Journal of Engineering Education, 2006. 95(2): p. 107- 122.23. Hennessey, M.P. and S. Kumar, Integrated graphical game and simulation-type problem- based learning in kinematics. International Journal of Mechanical Engineering Education, 2006. 34(3): p. 220-451.24. Butler, A.B., Effects of Solution Elicitation Aids and Need for Cognition on the Generation of Solutions to Ill-Structured Problems
knowledge (knowledge about when and why to usestrategies).32 Knowledge of cognition has been shown to play a key role in decision making andperformance.33–35 Regulation of cognition refers to an individual’s ongoing cognitive processesand includes five skills: planning, information management strategies, comprehensionmonitoring, debugging strategies, and evaluation. These skills have been suggested to play acritical role in problem solving as they allow learners to organize and monitor their thinking.35Metacognition was operationalized in this work to assess students’ perceptions of their ability touse metacognitive strategies when solving an engineering problem. Items were adapted from Leeet al.’s (2009) work originally used to assess elementary
retention, and how to best teach work skills throughout the engineering curriculum.Dr. Patricia A Ralston, University of Louisville Dr. Patricia A. S. Ralston is Chair of the Department of Engineering Fundamentals at the University of Louisville and also has an associate appointment in Chemical Engineering. Dr. Ralston teaches under- graduate engineering mathematics and is currently involved in educational research on the effective use of Tablet PCs in engineering education, the incorporation of critical thinking in undergraduate engineer- ing education, and retention of engineering students. Her fields of technical expertise include process modeling, simulation, and process control.Dr. Kate E. Snyder, University of
specific student had what perception(s). The questions were: 1) Do you believe the incorporation of narration will help / has helped your learning of the course material? (strongly agree / agree / disagree / strongly disagree) Please explain. 2) Do you believe the incorporation of narration will provide / provided useful background for your mini-labs and labs? (strongly agree / agree / disagree / strongly disagree) Please explain. 3) Do you believe the incorporation of narration will provide / provided useful background for your Project Test Plan? (strongly agree / agree / disagree / strongly disagree) Please explain. 4) Do you feel comfortable participating in narration during class? (strongly agree / agree / disagree
", 2nd ed., Princeton University Press, 1957.5. P. Kohl and N.D. Finkelstein, "Patterns of Multiple Representation Use by Experts and Novices during PhysicsProblem Solvings" in Phys. Rev. ST Physics Ed. Research 4, 010111, 2008.6. A. H. Schoenfeld, “What’s All The Fuss About Metacognition?” in Cognitive Science and Mathematics p. 187.Erlnaum, Hillsdale, NJ, 1987.7. Lohmann, S., Ziegler, J., and Tetzlaff, L. "Comparison of Tag Cloud Layouts: Task-Related Performance andVisual Exploration." In Proceedings of the 12th IFIP TC 13 international Conference on Human-Computerinteraction: Part I (Uppsala, Sweden, August 24 - 28, 2009) Page
were selected: The Journal of EngineeringEducation, Advances in Engineering Education, and the International Journal of EngineeringEducation. These journals were selected for their engineering education specific audience andfull article content availability online. Selection criteria for the articles included theclassification of the article as “mixed methods” by the author(s) or by the specific mention ofqualitative and quantitative data collection in the abstract. Following an initial review of thearticles in each publication, the sample (nine articles) was insufficient to fully characterize mixedmethods research in the field. In light of this an internet search was conducted for additionalengineering education research articles featuring a
development will be discussed.Overview of Engineering Curriculum DevelopmentsThe quality of engineering education and the ability to recruit a U.S. engineering workforce hasbeen a growing concern among engineers in university and industrial settings. In the 1990’s,ABET, the engineering accreditor of postsecondary degree-granting programs, revamped theprogram outcomes and assessment criteria to improve quality by implementing the EngineeringCriteria 2000 (EC2000).5 Beginning in 2001, all accredited engineering programs were requiredto demonstrate that their graduates possess the following eleven skills (known as a-k): ≠ Ability to apply knowledge of mathematics, science, and engineering; ≠ Ability to design and conduct experiments, as well as to
handwritten homework to assess students' presentation skills. This isrelatively easy in lower enrollment courses (30-36 students) in which professors can oversee theproblem solving process. Some (like ourselves) have the ability to teach at smaller schools andthere are ways to use hybrid approaches of online and handwritten homework to assess andinstill the importance of effective technical communication. We are not sure what the solutionwill be in large enrollment courses.References[1] Kolowich, S., "A Truce on the Tech Front at San Jose State", The Chronicle of Higher Education, 2013.[2] Rose, A.T.," Graphical Communication Using Hand-Drawn Sketches in Civil Engineering", Journal of Professional Issues in Engineering Education &
. This preliminaryanalysis has also helped us understand what types of differences merit framing in underlyingeducational and social psychology for future work.AcknowledgementsThe authors would like to gratefully acknowledge the National Science Foundation for theirpartial support of this work under the REESE program (DRL-0909817). Any opinions, findings,and conclusions or recommendations expressed in this material are those of the author(s) and donot necessarily reflect the views of the National Science Foundation.Bibliography1. Bandura, A., (1997) Self-efficacy: The exercise of control. Macmillan.2. Richardson, M., Abraham C., & Bond, R. (2012) Psychological correlates of university students' academic performance: A
higher education in the future.References 1. Mark S. Reed, Anna C. Evely, Georgina Cundill, Ioan Fazey, Jayne Glass, Adele Laing, Jens Newig, Brad Parrish, Christina Prell, Chris Raymond, and Lindsay C. Stringer. “What Is Social Learning?” Ecology and Society, 15, no. 4, 2010. 2. Saalih Allie, Mogamat Noor Armien, Nicolette Burgoyne, Jennifer M. Case, Brandon I. Collier-Reed, Tracy S. Craig, Andrew Deacon, Duncan M. Fraser, Zulpha Geyer, Cecilia Jacobs, Jeff Jawitz, Bruce Kloot, Linda Kotta, Genevieve Langdon, Kate le Roux, Delia Marshall, Disaapele Mogashana, Corrinne Shaw, Gillian Sheridan, and Nicolette Wolmarans. “Learning as acquiring a discursive identity through participation in a community
learning: Faculty and student perceptions. Journal of Nursing Education, 40(3), 116-123.10. Stepien, W. J., Gallagher, S. A., & Workman, D. (1993). Problem-based learning for traditional and interdisciplinary classrooms. Journal for the Education of the Gifted, 16(4), 338-357.11. Gallagher, S. A., Stepien, W. J., & Rosenthal, H. (1992). The effects of problem-based learning on problem solving. Gifted Child Quarterly, 36(4), 195-200.12. Hmelo, C. E., & Ferrari, M. (1997). The problem-based learning tutorial: Cultivating higher order thinking skills. Journal for the Education of the Gifted, 20(4), 401-422.13. Torrey, L. (2012, July). Teaching problem-solving in algorithms and AI. Third Symposium on
Engineering Education (CAEE). Page 12.94.11Any 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.Bibliography[1] Huang, G., Taddese, N., Walter, E. Entry and Persistence of Women and Minorities in College Science and Engineering Education. NCES 2000-601. Washington, DC: U.S. Department of Education. National Center for Education Statistics, 2000.[2] Besterfield-Sacre, M.E., Atman, C.J., Shuman, L.J. "How freshman attitudes change in the first year," ASEE Annual Conference Proceedings, vol. 1, pp
‘Engineer:’ How to Do It and Why It Matters” Journal of Engineering Education 85 (2), 1996, pp 97-1014. Satwicz T “Beyond the Barrier: Insights into the Mathematical Practices of Engineering Students,” working paper from June 2004.5. Moussavi M “Mathematical Modeling in Engineering Education” Proceedings of the 1998 Frontiers in Education Conference, FIE 1998, Tempe, AZ, paper F4H-3.6. Fadali M S, Velasquez-Bryant N, and Robinson M “Work in Progress – Is Attitude Toward Mathematics a Major Obstacle to Engineering Education?” Proceedings of the 2004 Frontiers in Education Conference, FIE 2004, Savannah, Georgia, pp F1F19 – F1F24.7. Underwood D “Is Mathematics Necessary?” The College Mathematics Journal 28 (5), 1997, pp
. Proceedings of the 33rd ASEE/IEEE Frontiers in EducationConference. Session T3D-6. Page 12.782.1910 Allen, K., A. Stone, T.R. Rhoads, and T.J. Murphy. 2004. The Statistics Concept Inventory:Developing a Valid and Reliable Instrument. Proceedings of the 2004 American Society forEngineering Education Annual Conference and Exposition. Session 3230.11 Allen, K., T.R. Rhoads, and R. Terry. 2006. Misconception or Misunderstanding? AssessingStudent Confidence of Introductory Statistics Concepts. Proceedings of the 36th ASEE/IEEEFrontiers in Education Conference. Session S2E.12 Evans, D.L., G.L. Gray, S. Krause, J. Martin, C. Midkiff, B.M. Notaros, M
? Include the method used to resolve the differences of opinion and the level of agreement on your final assessment.” This question was preceded by the question, “Ethical issues in [multidisciplinary project teams] are of two types: those involving behaviors within the [team] and those involving the eventual application of [team] output to the larger society. Please outline the most important ethical problems the team has encountered over the entire semester. What was the issue and what was the outcome? From your experience(s) this semester please explain the best course of action the team could or should have taken to produce the optimal resolution to its ethical dilemma. How did you contribute? If
Qthermal reservoirs it is easy to calculate their entropy changes using the relationship ∆S = . TStudents are guided to realize that although the net energy of the system is indeed conserved, thenet entropy must increase.Students are asked to consider the magnitudes and signs of heat transfers to the two blocks; they Page 13.812.8are led to recognize that these heat transfers are equal in magnitude and opposite in sign, and thatnet energy change is zero. Students are then asked to consider the relative magnitudes and signsfor the entropy changes of each
leaving school having seenonly EOCNE’s, or types 1 to 3 in the Johnstone scheme, could easily be at a majordisadvantage when faced with other types of problems. Page 13.1092.9 References1. I. A. Halloun and D. Hestenes (1985) “The Initial State of College Physics Students” American Journal of Physics, 53, 10432. R. Hake (1998) “Interactive Engagement Versus Traditional Methods:A Six-thousand- student Survey of Mechanics Test Data for Introductory Physics Courses“, American Journal of Physics, 66, 643. E. Kim and S-J. Pak (2002) “Students Do Not Overcome Conceptual Difficulties After Solving 1000
this study. Also, we would like to thank CASEE for supporting Dr.Pierrakos as a NAE CASEE Postdoctoral Fellow, and graduate student Shankar Arul, whoassisted us with the analysis.References1. Seymour E., Hunter A.B., Laursen S.L., DeAntoni T., 2004, “Establishing the benefits of research experiences for undergraduates in the sciences: First findings from a three-year study,” Science Education, 88(4), pp. 493-534.2. Hunter A. B., S. L. Laursen, and E. Seymour, Jan. 2007, “Becoming a Scientist: The Role of Undergraduate Research in Students’ Cognitive, Personal and Professional Development,” Science Education, 91(1), pp. 36-74.3. Russell S.H., M.P. Hancock, J. McCullough, April 2007, “The Pipeline: Benefits of Undergraduate Research