understanding the material and solving engineering problems as well as on theirdesire to become an engineer. Finally, students were asked how often they felt specific emotionswhile using the zyBook, such as interested, distressed, excited, and ashamed. The student surveydata showed that the majority of students reported that the interactive elements contributed totheir success in the course and the zyBook increased their understanding of the course contentand increased their confidence in solving engineering problems.IntroductionSelf-efficacy is grounded in a large theoretical framework known as social cognitive theory,which states that human achievement depends on interactions between one's behaviors, personalfactors, and environmental conditions [1
describe the structureof the course as a whole, provide detailed descriptions of two units in the course to illustrate howcomputational models can be used to teach core MSE concepts, and discuss how this approachdiffers from the traditional approach.1 Background: computation in MSE, ABM in education, and learning theories1.1 Computation in MSEComputational materials science and engineering (MSE) dates to at least the 1980s, and in thepast 20 years the MSE community has begun to recognize the crucial importance ofcomputational tools in accelerating the development, discovery, and design of new materials.There is widespread consensus among academics, national labs, and industry that computationwill play an increasingly important role in MSE and that
promotes AIliteracy for students before they enter higher education. Specifically, Laupichler et al. andHornberger et al. [6-8] developed assessments that include questions ranging from ‘Nameexamples of technical applications that are supported by artificial intelligence’ to ‘Give a shortoverview about the history of artificial intelligence’.In this work we describe an active learning framework where students design, manufacture, andtest to create robust process-structure-properties linkages of 3D printed materials. We aim toexplore these aspects using a novel ‘design-driven’ approach (Figure 1) that emphasizes the useof software interfaces that do not require computer programming skills to solve engineeringproblems with AI and ML. This approach
performancebased on the coefficient of determination R2 value (0.94) revealed that the model demonstratesgood performance in predicting the bulk modulus of the perovskite materials used during thepractical sections. The survey results after the teaching and practical sessions indicate that thelearning modules are an effective introduction for novice engineering students in this domainand raise awareness of the importance of this important sub-section of AI.Keywords: Engineering Education; Artificial Intelligence; Machine Learning; Perovskites;Materials Science 1. IntroductionMachine learning (ML) is a subfield of artificial intelligence (AI) that has been effectivelyapplied in various problem domains such as computer vision [1], speech recognition [2
contextsimproves student learning and engagement and increase retention [1], [2]. Thus, to address theseissues, between the spring 2021 and spring 2022 offerings we redesigned the ModSim sequenceto add several specific connections between the systems studied across the physical labsequences.This work to integrate computational approaches in the materials curriculum is especiallyrelevant to share with other departments across the country given the recent national emphasis,through the Materials Genome Initiative and other programs, in using computational tools toenable rational design of materials [3]. In one example, CALPHAD was applied to design a new,cheaper alloy used to manufacture nickels [4]. Computational tools are crucial towards the goalof inverse
microplastics) [1], [2]. Particle science plays acrucial role in product quality, material transport and storage, manufacturing processes andadvancement of materials science [3]. For example, understanding particle behavior (i.e., dryflow, aggregation and agglomeration) at a mass scale is crucial to the safety and improvement ofstorage, transport and manufacturing processes [3].Despite calls since the 1990’s to increase the availability of a uniform particle sciencecurriculum, little progress has been made in integrating particle science into the currentengineering curriculum—resulting in a limited number of engineers trained in the field [1].Within the United States, particle science courses are sparse and lack uniformity within thematerials and
development of innovative and engagingeducational games and extend the reach of such pedagogical strategies across various STEM andnon-STEM fields. 1. IntroductionThe U.S. undergraduate engineering programs are experiencing a decline in enrollment [1]. Thistrend weakens the United States’ longstanding leadership in global engineering and STEM fields,which has been declining over the past decade [2]. While the engineering workforce is evolving,there's an increasing emphasis on diversifying and expanding the appeal of undergraduateengineering programs. Addressing this challenge requires a shift towards more engaging anddiverse educational approaches in engineering education. This shift is not only essential formaintaining the country's competitive
, Materialsand Sustainability was introduced to prepare students to better meet the needs of variousindustries towards a circular economy and sustainable Earth.We strongly believe that the newly revamped curriculum will prepare Materials Engineeringstudents with essential knowledge and skills necessary to adapt in the ever-advancingengineering industry and excel in their career.1. BackgroundThe fast-paced advancement in science and technology means timely revision of existingcurriculums is important to avoid instances where learners gain obsolete skills that lackglobal competitiveness [1], [2]. In 2020, we embarked on a curriculum review for MaterialsEngineering undergraduate programme. We are determined to ensure that our curriculumadequately prepare
those who did not answer correctly receiving aless difficult question. However, sometimes, when correct, a student interpreted a similarquestion as an indication they were incorrect the first time. We also describe differences in theways students negotiated uncertainty and how they engaged in the more extensive instructionaltools. This paper contributes both to how students conceptually engage with complex materialsscience content and how student-technology interactions can support or hinder learning.Keywords: conceptual learning, knowledge in pieces, adaptive learning module, think aloud,materials science.IntroductionEngineering educators are increasingly emphasizing the importance of students’ conceptuallearning [1]. At the same time, the
throughout the program’s curriculum to complete a design project. This paperinvestigates the ongoing work of restructuring a traditional one-semester, 3-credit springcapstone experience in materials science and engineering into a two-semester fall (1-credit) andspring (2-credit) experience. During the restructuring of the capstone experience, the Human-Centered Design (HCD) framework, a method to formalize the design process in discrete stages,was integrated into the course content. Due to course catalog constraints, a 1-credit fall coursewas piloted in Fall 2022 as an elective for seniors (enrollment was approximately 30% of thesenior population); the traditional 3-credit course was still required of all seniors in Spring 2023.Aspects of HCD were
design of PB-Lab engages students with active learning and authentic learning; theysee how what they are learning in materials sciences can be applied as working engineers.Students experience the interdependent and integrated nature of the materials developmentprocess in the lab and generate their own concepts about addressing global challenges. Insummary, PB-Lab engages students in identifying problems, developing potential solutionsthrough materials characterization and analysis in the lab, and delivering effectivecommunication in the form of lab reports or presentations. 1. Introduction Materials science (MER 213/lab) at Union College is a sophomore-level course integralto understanding the properties and applications of
institutions and industry cannot be overstated [1, 2]. Out of the four key stakeholders(students, faculty, industry and society) in engineering education, industry is considered a majorone as it is a ultimate customer for the students universities graduate [3]. Not only does theindustry set the requirements for the engineering education but also plays a pivotal role inshaping the curriculum to meet the evolving needs of the workforce. The relationship betweenacademia and industry relies on feedback between the stakeholders (students, faculty andindustry) allowing educational institutions to align their programs with industry standards andadvancements, ensuring that graduates are well-prepared and relevant in a rapidly changingconsumer market space
, meaning that eachstudent already has unique pre-existing knowledge about how materials behave. From cooking,to skincare and makeup, to car maintenance, we all have hands-on life experience with countlessmaterials that guides us towards an understanding of structure-property relationships.In this work, we implement a final project in an introductory MSE course in which students areasked to 1) identify an area of opportunity or “problem” on campus, 2) propose a materials-enabled solution to the problem, and 3) present a poster that outlines the proposed on-campusproject. By setting the project on-campus, students are being asked to draw from their own lifeexperience and think about issues that impact themselves and other members of the