learning instructional strategies and auto-graded online homework. Eric has been an active member of ASEE since 2001. He was the recipient of the 2008 Pacific Northwest Section Outstanding Teaching Award and currently serves on the ASEE Board of Directors as Zone IV Chair.Dr. Lee Singleton, Whatcom Community College Lee Singleton is a professor at Whatcom Community College, in Bellingham, WA. He holds a BS in mathematics from Harding University, a MS in mathematics and PhD in biomedical mathematics from Florida State University. His current interests include 3D-prinRebecca S. Borowski ©American Society for Engineering Education, 2023 An Exploration of How Students Make Use of Hands-On Models to
Paper ID #37722Teaching the Concept of Tipping in Statics: Pedagogy, PracticalExamples, and Potential ActivitiesDr. Sridhar S. Condoor, Saint Louis University Professor with a demonstrated history of working in the design innovation and technology entrepreneur- ship areas. Skilled in Innovation Management, Applied Research & Product Design, Entrepreneurship, and Training Next Generation Innovators and Entrepreneurs.Bryan MacGavin, Saint Louis UniversityDr. Raja Shekar P. V. Dr. Raja Shekar P. V is presently working as an Associate Professor of Physics in SR Engineering Col- lege, Warangal. He did his Ph.D in Materials
. She graduated cum laude from the University of Florida with a B.S. in Mechanical Engineering. Captain Welsh earned her M.S. in Systems Engineering from the Air Force Institute of Technology at Wright-Patterson Air Force Base, Ohio. Her research interests include concept based learning and design of autonomous systems.Dr. Lorena S. Grundy, Tufts University Lorena Grundy is an ASEE eFellows postdoctoral fellow at Tufts University, where she works with Milo Koretsky to study chemical engineering education. She received her BSE from Princeton in 2017 and PhD from UC Berkeley in 2022, both in chemical engineering.Dr. Brian P. Self, California Polytechnic State University, San Luis Obispo Brian Self obtained his B.S. and
, measure of learning. It has been suggested that instructors maybe more lenient with expectations and award higher grades that normal in an attempt tocompensate for the negative circumstances [10] and that grades during this time period wereinflated [11].To date, the majority of studies that explore student performance compare performance duringthe COVID affected semester(s) to performance pre-COVID. We sought to better understandboth the immediate and the ongoing effects of the COVID-19 pandemic and the associatedinstitutional response on our engineering students. We explore student performance in three largemulti-section foundational mechanics courses: Statics, Mechanics of Deformable Bodies(Deformables), and Dynamics. These courses are required
S - Incorrect sign on one or more components Resolve a vector F - Incorrect value of one or more components Add vectors N/A Q - Vector sketched in quadrant inconsistent with vector expression Sketch a vector A - Angle indicated on sketch inconsistent with calculated angleIn problem 2, students were asked to determine the moment of each force about a given point,then find the magnitude and
accountability for watching the videos.In addition to watching the videos and completing the notetaker, students would also write-up thetwo or three homework problems from the previous lesson that were due at the start of class. Theproblems were typically graded by students in class.In-class activitiesIn general, the in-class activities were similar for all three instructors. The class started with abrief quiz over the material covered in the videos. For Instructors 1 and 3, the quiz was oftenstarted individually, but after about 5 minutes, students were allowed to work with the peoplearound them. Instructor 2’s quiz was delivered using the polling software and the questions wereall multiple choice.Following the quiz the instructors presented a very
Paper ID #39447Work in Progress: Evaluating the Effect of Symbolic Problem Solving onTesting Validity and ReliabilityDr. Yan Tang, Embry-Riddle Aeronautical University, Daytona Beach Dr. Yan Tang is an associate professor of mechanical engineering at Embry-Riddle Aeronautical Uni- versity in Daytona Beach, Fla. Her current research in engineering education focuses on cognitive load theory, deliberate practice, and effective pedagogical strategies.Lin Ding, The Ohio State University Lin Ding, Ph.D., is an associate professor in the Department of Teaching and Learning at The Ohio State University. Dr. Dingˆa C™s scholarly
for theircontributions to this study's assessment components.This material is based upon work supported by the National Science Foundation under Grant No.2141984. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation.10. References[1] A. Vidak, I. Movre Šapić, and V. Mešić, "An augmented reality approach to learning about the force of gravity," Physics Education, vol. 56, 2021, doi: 10.1088/1361-6552/ac21a3.[2] R. A. Serway and J. W. Jewett, Physics for Scientists and Engineers, 10 ed. Cengage Learning, 2019, p. 1162.[3] A. Bedford and W. Fowler, Engineering Mechanics: Statics, 6th ed. Upper Saddle
also be explored.AcknowledgementsSupport for this work was provided by the National Science Foundation under Award No.2301341. Any opinions, findings, and conclusions or recommendations expressed in this materialare those of the author(s) and do not necessarily reflect the views of the National ScienceFoundation. Research work was conducted under institutional IRB protocols, IRB#1965654. Theauthors would also like to thank Dr. Jenni Buckley for providing copies of her EngineeringStatics class notes for use in this work.References1. ABET, “Criteria for Accrediting Engineering Programs, 2020 – 2021 | ABET,” ABET, 2021. https://www.abet.org/accreditation/accreditation-criteria/criteria-for-accrediting-engineering- programs-2020-2021
engineering computer applications. Proceedings of the 2022 ASEE Annual Conference & Exposition, Minneapolis, MN. https://peer.asee.org/413492 Moore, J. P., & Ranalli, J. (2015, June), A Mastery Learning Approach to Engineering Homework Assignments. Proceedings of the 2015 ASEE Annual Conference & Exposition, Seattle, Washington. 10.18260/p.234053 R. Averill, S. Roccabianca, and G. Recktenwald, A Multi-Instructor Study of Assessment Techniques in Engineering Mechanics Courses. Proceedings of the 2019 ASEE Annual Conference & Exposition, Jun. 2019. https://peer.asee.org/a-multi-instructor-study-of-assessment-techniques-in-engineering-mechanics- courses4 Sangelkar, S., & Ashour, O. M., &
Aconsisted of 19 minutes of silence (34% of the video), whereas when working on the same partof the project, Group B’s recorded meeting had 48 minutes of silence (86.26% of the video).Overall, students spent a large portion of their time together not engaged in codable activity(70%) including sitting in silence, or discussing non class topics, such as schedules and athletics.Data across both groups totaling 16.2 hours was used to make the following table which showsthe percentage of time and the unique number of times that students engaged in a code.Table 5: Activity of Groups A and B Code Total time % of Total % of CodedCode Name Color (s) Unique Times Time
errors, in turn, resulted inusers obtaining inaccurate responses. Examples of successful and unsuccessful problem solutionsare included below. Full solutions from ChatGPT are included in Appendix B.• Example problems for which ChatGPT provided correct responses: o Statics ➢ The bending moment on a beam is given by 𝑀 = −4𝑥 3 + 3𝑥 2 − 23𝑥 + 5 N.m, calculate the shear force at 𝑥 = 3 m. (Correct Answer: V = 113 N; ChatGPT answer: 113 units [whatever the units of the bending moment are]) o Dynamics ➢ The position of a particle is given by 𝑠[𝑡] = 𝑡 3 − 12𝑡 2 + 44𝑡 + 11 m, calculate the acceleration value at 𝑡 = 5 s. (Correct Answer: a = 6 m/s2; ChatGPT answer: acceleration at t=5s
those connections and find therelevant information themselves. The points in which students are asked to identify theirquestions will remain, but there will be fewer times when the class reassembles as a whole.However, students are welcome to discuss with other groups, and the lab instructor(s) will becirculating to address any extreme misdirection.As a deliverable, students write a short memo with their recommendation for the design briefwith justification. They must include their experimental data in that justification and clearlyexplain any assumptions they made. Students must also turn in their documentation from the labperiod with the initial brief, the prompting questions, and their plan. This ensures students workmethodically to create a
Provost forproviding funding and resources to initiate this pilot project.This material is based upon work supported by the National Science Foundation under Grant No.2141984. Any opinions, findings, and conclusions or recommendations expressed in thismaterial are those of the author(s) and do not necessarily reflect the views of the NationalScience Foundation.The authors would also like to thank Dr. Hammam Alsafrjalani and Berk Basarer for theircontribution to the app development and testing.10. References[1] M. Billinghurst, H. Kato, and S. Myojin, "Advanced Interaction Techniques for Augmented Reality Applications," presented at the Virtual and Mixed Reality, Third International Conference, VMR 2009, San Diego, CA, July 19-27, 2009.[2
anddevelopment. Prentice-Hall.[2] Letina, A. (2015). Application of Traditional and Alternative Assessment in Science andSocial Studies Teaching. Croatian Journal Educational / Hrvatski Casopis Za Odgoj I[3] Chrysochoou M, Zaghi AE, Syharat CM (2022) Reframing neurodiversity in engineeringeducation. Front. Educ. 7:995865. DOI: 10.3389/feduc.2022.995865[4] Armstrong, T. (2012). First, Discover Their Strengths. Educational Leadership, 70(2), 10.[5] Daniels, S., & Freeman, M. (2018). Gifted dyslexics: MIND-strengths, visual thinking, andcreativity. In S. B. Kaufman (Ed.), Twice exceptional: Supporting and educating bright andcreative students with learning difficulties, Oxford University Press (pp. 266-277).[6] von Károlyi, C. (2001). Visual–spatial
on one part of the car. • The smallest speed would be B in this one because B is toward the center and A C and D will have the same. • Which has the smallest speed. A B C or D … wow this is what got me in Physics, I really need to review this. Um I think A C and D speed … but B … No they might just all have the same speed if we’re looking at … yeah … I’m going to say they have … I’m going to say E • The “S” and “L” component of velocity based on the tire’s movement. Since it’s in the very center basically everyone one of them is moving at B, the velocity of the car, but each has their own velocity of the tire s well, except for B.Correct Responses • Nothing was said aloud – scored as incorrect
isolated testinglocation and 2) a grade/cash incentive to encourage active participation is needed. Finally, since most concept inventories include multiple questions that test the same concept, weshould include analysis of these other problems to investigate these issues more fully. However, theseresults are representative of student’s results. More analyses of student results on problems testing thesame concept are part of future work.Bibliography[1] D. Hestenes, M. Wells, and G. Swackhamer, “Force concept inventory,” Phys Teach, vol. 30, no. 3, pp. 141–158, 1992, doi: 10.1119/1.2343497.[2] D. Hestenes and I. Halloun, “Interpreting the FCI:A Response,” The Physics Teacher, vol. 33. pp. 502–506, 1995.[3] P. S. Steif
or Equivalent on First Attempt. D1 D2 D3 D4 D5 C1 C2/C3 C4 B1 M S M S M S M S M S M S M S M S M S#A 82 48 51 31 63 27 42 31 39 20 32 31 65 30 21 17 27 11 N 246 90 243 88 224 87 208 87 187 87 192 86 262 89 122 85 92 42% 33.3 53.3 21.0 35.2 28.1 31.0 20.2 35.6 20.9 23.0 16.7 36.0 24.8 33.7 17.2 20.0 29.3 26.2Notes: #A = raw number of tests scored with Approved
to visualize 2x2 and 3x3 matrices by Christian Otto Mohr in thelate 1800’s, Mohr’s circle has since become a foundational, visual tool for mechanics studentsworking to understand the stresses at play at derived points in materials [1]. Undergraduateengineering students are commonly introduced to Mohr’s circle in their Mechanics of Materialsclass as an analytical tool included in the lessons on stress transformations. The basic idea behindMohr’s circle is that normal and shear stresses on a plane within a material depend on theorientation of that plane [2]. Through graphical representation, Mohr’s circle simplifies theprocess of reorienting a given planar section of material to obtain the normal and shear stresses atthe new orientation. It
completed more variety of StaticViewproblems, more specific CAD models used as well as the timing on when they are introduced toyield more meaningful results.References[1] Steif, P. S., & Dollar, A. (2004, January). Reinventing engineering statics to address theconceptual difficulties of students. In ASME International Mechanical Engineering Congress andExposition (Vol. 47233, pp. 47-52).[2] Wingate, K. A., Ferri, A. A., & Feigh, K. M. (2018, June). The impact of the physics, statics,and mechanics sequence on student retention and performance in mechanical engineering. In2018 ASEE Annual Conference & Exposition.[3] Steif, P. S., & Dollar, A. (2005). Reinventing the teaching of statics. International Journal ofEngineering Education
acknowledge the contributions of the faculty and laboratorytechnicians from the United States Military Academy who supported this study especially Mr.Corey Smith, Mr. Matthew Stanton, and Ms. Gabriella Santiago. The authors also greatlyappreciate the support of Braeden Germundson and Tyler Esola in testing the samples andrecording the videos. The views expressed in this work are those of the authors and do notnecessarily reflect the official policy or position of the United States Military Academy,Department of the Army, DoD, or U.S. Government.References[1] S. Freeman et al., “Active learning increases student performance in science, engineering, and mathematics,” Proc Natl Acad Sci U S A, vol. 111, no. 23, pp. 8410–8415, Jun. 2014
that final exams (a proxy for knowledge retention), were much poorer (13-point mediandifference) for students taking the course in the middle of the pandemic. By spreading material over four exams, instead of three, and flipping a class – thereby allowingstudents access the lecture material at their convenience, we hoped for overall student improvement. Thiswas not the case. REFERENCES[1] S. Asgari, J. Trajkovic, M. Rahmani, W. Zhang, R. C. Lo, and A. Sciortino, “An observational study of engineering online education during the COVID-19 pandemic,” PLoS One, vol. 16, no. 4 April, Apr. 2021, doi: 10.1371/journal.pone.0250041.[2] N. L. Ramo, M. Lin, E. S. Hald, and A. Huang-Saad
Climate Change Impacts on Civil Infrastructure Resilience,” Sustain. Resilient Infrastruct., vol. 3, no. 4, pp. 175–192, 2018, doi: 10.1080/23789689.2017.1416845.[14] A. Raz, P. Balasubramani, S. Harrington, C. Guariniello, and D. A. DeLaurentis, “System- of-Systems Acquisition Analytics Using Machine Learning Techniques,” Seventeenth Annu. Acquis. Res. Symp., 2020.[15] J. F. Feldhoff et al., “Shaping Our Future with Sustainable Energy: a Direction from Young Engineers,” in 2012 ASME 6th International Conference on Energy Sustainability, 2016, pp
TACMAV systems in 2005. Around that time he volunteered as a science advisor and worked at the Rapid Equipping Force during the summer of 2005 where he was exposed to a number of unmanned systems technologies. His initial group composed of about 6 S&T grew to nearly 30 between 2003 and 2010 as he transitioned from a Branch head to an acting Division Chief. In 2010-2012 he again was selected to teach Mathematics at the United States Military Academy West Point. Upon returning to ARL’s Vehicle Technology Directorate from West Point he has continued his research on unmanned systems under ARL’s Campaign for Maneuver as the Associate Director of Special Programs. Throughout his career he has continued to teach at a
, theMathWorks website includes significant content explaining the functionality and implementationof live scripts 5. Furthermore, the MATLAB Central File Exchange 6 is a valuable resource fordiscovering live scripts that other users have created that can be readily adapted.References[1] M. Prince, "Does active learning work? A review of the research.," Journal of engineering education, vol. 93, no. 3, pp. 223-231, 2004.[2] S. Freeman, S. L. Eddy, M. McDonough, M. K. Smith, N. Okoroafor, H. Jordt and M. P. Wenderoth, "Active learning increases student performance in science, engineering, and mathematics.," Proceedings of the national academy of sciences, vol. 111, no. 23, pp. 8410-8415, 2014.[3] P. C. Wankat and F. S. Oreovicz, Teaching
; Exposition, 2018. [9] C.-W. Lee, A. Schleife, D. R. Trinkle, J. A. Krogstad, R. Maass, P. Bellon, J. K. Shang, C. Leal, M. West, T. Bretl, G. L. Herman, and S. Tang, “Impact of computational curricular reform on non-participating undergraduate courses: Student and faculty perspective,” in 2019 ASEE Annual Conference & Exposition, 2019.[10] J. Wagemann, F. Fierli, S. Mantovani, S. Siemen, B. Seeger, and J. Bendix, “Five guiding principles to make Jupyter notebooks fit for earth observation data education,” Remote Sensing, vol. 14, no. 14, 2022.[11] M. West, G. L. Herman, and C. Zilles, “PrairieLearn: Mastery-based online problem solving with adaptive scoring and recommendations driven by machine learning,” in 2015 ASEE Annual
First-Year Class 0.9 high 0.8 medium low Errors per FBD 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0 ed in s ht
(MSU). She was born and raised in Verona, Italy and received her B.S. and M.S. in Civil Engineering from the University of Trento, Italy. S ©American Society for Engineering Education, 2024 Paper or Silicon: Assessing Student Understanding in a Computer-based Testing Environment using PrairieLearnAbstractComputer-based testing is a powerful tool for scaling exams in large lecture classes. Thedecision to adopt computer-based testing is typically framed as a tradeoff in terms of time; timesaved by auto-grading is reallocated as time spent developing problem pools, but with significanttime savings. This paper seeks to examine the tradeoff in terms of accuracy in measuring
possible that many students can complete a coursesuch as Statics by performing operations but without ever drawing corresponding diagrams, or, in thecases when students do draw diagrams, it is unlikely that they draw them to accurate geometrical scaleunless explicitly prompted.This raises questions such as if creation and interpretation of accurate figures is a necessary part ofunderstanding vector operations, and if such skills enhance, or at least correlate with, overall problem-solving performance. One approach to introduce graphical reasoning is via concept questions, in whichstudents can identify from a given set of options which diagram(s) accurately represent a vector resultantor other characteristic. Another approach, as is explored in
faculty members using Spring 2022 Instructor 1’s materials Fall 2022 100% flipped, face-to-face and taught by Instructor 1 Table 2 – Summary of out-of-class and in-class activities Semester Out-of-class activities In-class activities Three videos (a mini lecture and two Concept questions via polling example problems) feature of Blackboard Required notetaker (collected) Quick review Fall 2020 McGraw-Hill LearnSmart reading Grade homework (flipped- remote) assignment