Conference Session

Materials Division (MATS) Technical Session 1

Collection

2024 ASEE Annual Conference & Exposition

Authors

Joel L Galos, California Polytechnic State University, San Luis Obispo; Aaron Zachary Chandler Friedman, California Polytechnic State University, San Luis Obispo; Ethan Jamosmos, California Polytechnic State University, San Luis Obispo; Sarah Isabel Allec, Citrine Informatics; Brina Blinzler, The University of Kansas; Lessa Grunenfelder, University of Southern California; Adam R Carberry, The Ohio State University

Tagged Divisions

Materials Division (MATS)

, which can enable students to understand and identify the characteristics ofsuccessful AI-driven product development projects. The ability for students to learn andperform an end-to-end data science workflow without writing a single line of code, all withinthe context of materials design, has the potential to enhance their educational experience butwill also improve their employability in a rapidly advancing field. Figure 3: Citrine Platform ‘branched’ workflow for investigating materials development using AI/ML without the need for computer programming.Following 3D printing and material characterization, students curate the material propertydataset so that it can be ingested in the Citrine Platform to train a ML model. The output ofthis

Conference Session

Materials Division (MATS) Technical Session 4

Collection

2025 ASEE Annual Conference & Exposition

Authors

Rajan Kumar, Northwestern University

Tagged Divisions

Materials Division (MATS)

challenging [10-11]. Students need multiple opportunities to practice and applyconcepts at an introductory and intermediate level before they can begin to think like an expert.In turn, instructors and departments must scaffold both their individual courses and theircurriculum as a whole for students to achieve these higher-order learning outcomes.Implementing open-ended experiments and projects also requires extensive preparation andtroubleshooting and may not always be scalable. Instructors and departments often have tobalance authentic approaches with practical limitations.In this work, I present a framework for incorporating higher-order learning outcomes into thematerials science and engineering undergraduate curriculum through a single

Conference Session

Materials Division (MATS) Technical Session 4

Collection

2025 ASEE Annual Conference & Exposition

Authors

Joel L Galos, California Polytechnic State University, San Luis Obispo; Mohsen Beyramali Kivy, California Polytechnic State University, San Luis Obispo; Lessa Grunenfelder, University of Southern California; Ken-ichi Nomura, University of Southern California; James E. Saal, Citrine Informatics, Inc.

Tagged Divisions

Materials Division (MATS)

development projects. The ability for students to learn and perform an end-to-end data science workflow without writing a single line of code, all within the context ofmaterials design, has the potential to enhance their educational experience and improve theiremployability in a rapidly advancing field.The Citrine Platform has been used to help expose second- and third-year undergraduateMS&E students to AI and ML through an iterative activity that involves development andcuration of a material and process property dataset of 3D printed plastics [25]. The process isshown in Figure 8. Students began by collecting and organizing plastic filament data frompublished literature and from an existing dataset provided by the instructor. The output ofthis

Conference Session

Materials Division (MATS) Technical Session 2

Collection

2024 ASEE Annual Conference & Exposition

Authors

Nutnicha Nigon, Oregon State University; Julie Tucker, Oregon State University; Milo Koretsky, Tufts University

Tagged Divisions

Materials Division (MATS)

does make sense when looking at the provided figures and briefexplanation from the CALM, the intended correct connection would be “a lattice point representsan atom, usually located at the center of an atom, which are at corners of the unit cell for the SCstructure.” This connection was not established for Max. Figure 9. A supplemental video slide showing a concept of lattice parameter. The original pictures used in this slide are from [47], which is the required textbook in the course.DiscussionThis paper is part of our broader project addressing the development of conceptual understandingin adaptive personalized learning systems. In the study reported here, we observed in detail howfour students interacted with the tool to develop

Conference Session

Materials Division (MATS) Technical Session 4

Collection

2025 ASEE Annual Conference & Exposition

Authors

Jacob Z. Kelter, Northwestern University; Jonathan Daniel Emery; Uri Joseph Wilensky

Tagged Divisions

Materials Division (MATS)

], [22],biology [23], [24], probability [25], social sciences [26], [27], and materials science [15]. Therehave been calls to integrate computational modeling, and the perspective of emergence ithighlights, across K-16 STEM curricula in general [28], [29] and specifically to make “one-to-many” computational models the backbone of the MSE curriculum [15]. However, prior work oncomputational restructurations have only designed learning interventions for specific topicswithin a subject. The course redesign reported in this paper is the first time that a project rootedin restructuration theory has taken on the task of redesigning an entire course.2.3 Prior workIn [1], we described the course redesign in detail, including conceptual explanations of

Conference Session

Materials Division (MATS) Technical Session 1

Collection

2024 ASEE Annual Conference & Exposition

Authors

Ryan Barlow, zyBooks; Adrian Rodriguez, zyBooks; Lauren Fogg; Linda Ratts, Wiley; Yasaman Adibi, zyBooks; Jenny Welter, Wiley; Mary Fraley, Michigan Technological University

Tagged Divisions

Materials Division (MATS)

Louisiana Tech University. She has a Bachelor’s degree in Mechanical Engineering and a Master’s degree in Mechanical Engineering. Her research interests are diversity, gender equity, retention, project-based learning, and cognitive models of problem-solving.Ms. Linda Ratts, WileyYasaman Adibi, zyBooks Yasaman Adibi is an Engineering Content Author at zyBooks. She earned her PhD in Electrical Engineering from the University of Minnesota in 2015, where her research focused on medical imaging using ultrasound. She also did two years of postdoctoral researMs. Jenny Welter, WileyMs. Mary Fraley, Michigan Technological University Mary Fraley is a Senior Lecturer in the Department of Engineering Fundamentals at Michigan

Conference Session

Materials Division (MATS) Poster Session

Collection

2025 ASEE Annual Conference & Exposition

Authors

David Olubiyi Obada, Africa Centre of Excellence on New Pedagogies in Engineering Education (ACENPEE), Ahmadu Bello University, Zaria, Nigeria; Ayodeji Nathaniel Oyedeji, Ahmadu Bello University; Simeon Akindele Abolade; Shittu Babatunde Akinpelu, Atlantic Technological University, Ireland; RAYMOND BACSMOND BAKO; Adrian Oshioname Eberemu; Akinlolu Akande

Tagged Divisions

Materials Division (MATS)

problems, waste containment barriers and covers, Biogeochemical Processes in Geotechnical Engineering (Microbial Induced Calcite Precipitation) and unsaturated soils (collapsible soils) and lately engineering education. He has many published works in peer-reviewed journals, conference proceedings and chapters as well as technical reports to his credit in the various research area. He is currently the academic and research coordinator with the African Center of Excellence on New Pedagogies in Engineering Education (ACENPEE), Ahmadu Bello University Zaria; a World Bank funded Development Impact project with the aim of scaling up post graduate education at the MSc/PhD levels through regional specialization and

Conference Session

Materials Division (MATS) Technical Session 2: Activities with Impact! Special Session

Collection

2025 ASEE Annual Conference & Exposition

Authors

Asher Barnsdale, University of Victoria; Olivia Daugela, University of Victoria; Joel L Galos, California Polytechnic State University, San Luis Obispo; Elisabeth Hülse, ANSYS, Inc.; Kaitlin Tyler, ANSYS, Inc.; Bosco Yu, University of Victoria

Tagged Divisions

Materials Division (MATS)

served as a Teaching Assistant Professor at McMaster University from 2020 to 2022, where he played an integral role in curriculum development for materials science education within a project-based learning initiative. His outstanding contributions to materials science education and pedagogy practice were recognized and he was honoured to receive the ASEE - New Materials Educator Award in 2023. Since joining UVic in 2022, as the principal investigator (PI) of the Hybrid 3D lab, Dr. Yu has focused on the research goals of systematically investigating the mechanics of heterogeneous architected metamaterials and demonstrating their strong potential to solve engineering design challenges in a wide range of sectors

Conference Session

Materials Division (MATS) Technical Session 4

Collection

2025 ASEE Annual Conference & Exposition

Authors

Sarah A Goodman, Georgia Institute of Technology; Louis Oh, Stevens Institute of Technology (School of Engineering and Science); Elizabeth Zarr Paolella, Stevens Institute of Technology (School of Engineering and Science)

Tagged Topics

Diversity

Tagged Divisions

Materials Division (MATS)

) metallurgy, CAD made. I’ve always been projects. focused more on the aesthetics of crochet more than how it can impact the material properties of a fabric. It introduced me to the potential that

Conference Session

Materials Division (MATS) Technical Session 1

Collection

2024 ASEE Annual Conference & Exposition

Authors

Jacob Kelter, Northwestern University; Jonathan Daniel Emery, Northwestern University

Tagged Divisions

Materials Division (MATS)

MSE curricula at upper-level undergraduateand graduate courses, introductory courses are still largely taught with traditional diagrams andformulae approaches, leaving computational thinking, exploration, and modeling for later. Thistraditional approach misses an opportunity to leverage computational modeling as a coreteaching and learning tool when students begin their study of MSE. According to the OpenSyllabus project [11], which has collected over 230,000 engineering syllabi, the most popularintroductory MSE textbook, authored by Callister and Rethwisch [12], is the second mostassigned textbook across all engineering disciplines. This textbook has been through manyeditions, but it was originally written in 1985 and does not include any