Paper ID #38508Introductory materials science: A project-based approachDr. Lessa Kay Grunenfelder, University of Southern California Lessa Grunenfelder has a BS in astronautical engineering and a MS and PhD in materials science, all from the University of Southern California. In 2015 she joined the Mork Family Department of Chemical En- gineering and Materials Science at USC as teaching faculty. She teaches both undergraduate and graduate courses on material properties, processing, selection, and design. She is passionate about sharing her love of materials science with students through curriculum that combines
Miura ori fold which demonstrated interesting material properties like thenegative Poisson’s ratio. In addition, the students predicted and then tested the strength of thefolded paper. The teaching module is presented here. In this course, the students are usuallyexposed to different materials every week. They then pick one material and study it in-depth inthe last few weeks of class as their project. Three of the nine students in the class picked thistopic. Details of the projects are also presented here. Additionally, what worked, what did notwork, and why, is then discussed in this paper, along with suggestions for improvement.Introduction: Origami has been used for several years as works of art, but in recent years has been usedfor
) providing opportunities for leadership, mentorship,and networking.xxiiiThe Researcher Incubator technique developed originally by Traum & Karackattu was applied tosuccessfully engage URSP students in the research enterprise. xxiii The Researcher Incubator positsthat if students are 1) taught needed skills, 2) empowered by group work, and 3) vested withserious responsibility they will spontaneously find and/or develop whatever knowledge isrequired to succeed on the project.xxii This technique has proven effective to engage lowerdivision engineering students and even high school students in productive research.Two URSP freshmen were recruited into the project. These students enrolled in a research-for-credit course in parallel with a classroom
- terials science instructor for the Engineering 1 program at McMaster University. He was also one of the lead project developers for the first-year multidisciplinary project-based learning course (ENG 1P13). Dr. Yu’s pedagogical approach focuses on experiential learning, collaborative learning, gamified learning, student-centred education, and design-led materials science education. Dr. Yu joined the Department of Mechanical Engineering at the U. of Victoria in September 2022 as an Assistant Professor. He leads a research group (”Hybrid 3D”) that leverages additive manufacturing to develop new generations of hy- brid materials that are lightweight, recyclable and highly tunable to solve global sustainable development
Associate Professor in the Mechanical Engineering department at Texas A&M. He teaches in the areas of materials, manufacturing, and design. His interests are in the areas of Engineering Design for Disciplinary STEM Educational Research, Team Formation and Team Skill Education.Prof. Bruce L. Tai, Texas A&M University Dr. Tai is an Associate Professor in J Mike Walker ’66 Department of Mechanical Engineering at Texas A&M University. His research in manufacturing focuses on machining processes, additive manufactur- ing, and data-driven surgical training. He has over a 15-year track record in manufacturing research and education. The recent research projects include machining non-traditional metal alloys
University (Mechanical En- gineering), and The University of Utah (in both Materials Science and Engineering, and Metallurgical Engineering). Nonacademic pursuits include tending his orchards (he’s a fruit philanthropist) and playing the piano.Dr. David G. Rethwisch, The University of Iowa Dr. Rethwisch is a professor of chemical and biochemical engineering at the University of Iowa. His current research interest is assessing the impact of secondary curricula (particularly problem/project based learning curricula) on student interest and pe ©American Society for Engineering Education, 2023 A New Paradigm for Learning the Fundamentals of Materials
reasonably expectthat most juniors have more practice and experience with computational tools than freshmen, andtherefore would have higher confidence in their abilities. Fig. 1. Plots depicting comparisons between NCS freshman and junior mean responses regardingprogramming/simulation self-efficacy (a) and valuation (b). For all questions relating to self-efficacy, the Likert scale translates to 1 = “Not at all confident” to 6 = “Extremely Confident.” For self-efficacy questions, the scale translates to 1 = “Strongly Disagree” to 6 = “Strongly Agree.”Our findings revealed a surprising similarity in NCS freshmen and junior mean responses related tomotivation and ability to strategize for programming and simulation-related projects
Multifunctional Materials Laboratory, Shell Office Complex, Department of Mechanical Engineering, Ahmadu Bello University, Zaria, Nigeria 7 School of Science, Atlantic Technological University, Ash Lane, Ballytivnan, Sligo, Ireland8 Department of Materials Science and Engineering, University of Ghana, Legon, Ghana Corresponding author: David O. Obada (doobada@abu.edu.ng)ABSTRACTGroup project forms an integral part of engineering education because creatingconnections between the course modules and its applications can be a difficult task.Therefore, team dynamics/cooperative learning can play a major role in determining thesuccess rate of learners, with new pedagogies and think-pair
Paper ID #39350Exploring how Different Instructional Methods Compare to Improve StudentPerformance and Satisfaction in an Online Environment.Mr. Michael Roberts, University of Florida Currently, I work as a Technology Coach for a research grant. I have research experience in numerous fields including Magnetic Barkhausen Noise (MBN) in HY80 steel, Engineering Education, Artificial Intelligence (AI), and my current senior design project involves designing a sensor to detect volatile gases in moon regolith (moon rock). long with my research experience, I have developed my programming and computational skills which have
apply. Figure 3: Data AnalysisSkills related to CodingIn addition to “Programming Languages” section, to investigate the need for coding related skillsin more detail, we asked alumni to rate how relevant the following practices for their job are (eachon a 5-point Likert Scale): • Skill 1: “Working with big coding projects collaboratively” • Skill 2: “Managing workflows and version control” • Skill 3: “Testing and verifying code” • Skill 4: “Finding your way around complicated chunks of code”These practices can be considered to be specific to software engineers, however, in Figure S1 weshow that for approximately half of the MSE graduates
, namely, Mechanical,Civil, Electrical, Chemical and Industrial, have courses on materials, both at the undergraduate andgraduate levels as well as funded research projects in materials. Furthermore, the Faculty of Arts andSciences has similar emphasis in materials, in the departments of Physics, Chemistry, Biology and Geology.In sum, the Division of Materials of ASEE is of great interest for our academic improvement [1]. Hence, thispaper!Over the last few years, several natural and man-made phenomena have affected any progress of thissmall island. While the earthquakes and the hurricanes are natural phenomena, not disasters, COVID-19was certainly a man-made cataclysm. We had a severe earthquake, over 7 on Richter’s Scale, plus COVID-19 started
, “Series of Jupyter notebooks using Python for an analytical chemistry course,” Journal of Chemical Education, vol. 97, no. 10, pp. 3899–3903, 2020.[10] M. van Staveren, “Integrating Python into a physical chemistry lab,” Journal of Chemical Education, vol. 99, no. 7, pp. 2604–2609, 2022.[11] T. Kluyver, B. Ragan-Kelley, F. P´erez, et al., “Jupyter notebooks - a publishing format for reproducible computational workflows,” in Positioning and power in academic publishing: Players, agents and agendas (F. Loizides and B. Schmidt, eds.), pp. 87–90, 2016.[12] Executable Books Project, “Jupyter Book.” Zenodo, 2020. v0.12.3.[13] E. Chen and A. M. Minor, “MSE 104L Data Analysis.” GitHub, 2023. https://enze-chen.github.io/mse104l/.[14