foil but has no effect on the block. Therefore, it can be valuable to takean active learning approach to teaching these key concepts, so that students can formulate anintuitive understanding of stress and strain that can carry forward as they encounter moreadvanced engineering concepts.Here, we present a discovery-based approach to introduce students to these concepts through theuse of crude tensile tests. The students are provided with elastomeric strips which are easy todeform using human strength and have the added advantage of being highly reusable due to theirelasticity.The classroom approach is as follows: 1) Introduce the concept of a tensile test as a way that engineers can probe the behavior of materials when they are subjected
materials. This town has also made itself known for forward-thinkingactivities within domestic infrastructure, such as biogas city buses [1], extensive renewabledistrict heating [2] and production technology [3], as well as higher education. It is a medium-sized Swedish town with links to this industrial history that makes it a main local provider ofgraduated Engineering students. That was also one reason for the online professionaldevelopment course program that was created by this University as an Industry-Academycollaboration, within the ExSus project (EXpert Competence for SUStainable Production).Since the Aerospace and Transport industry are some of the main local stakeholders, it wasnatural to include a strong focus on relevant, so called
download the information and implement the game intheir classrooms.1. IntroductionMaterials play a pivotal role in advancing the technologies that shape modern society, both fromunderstanding the connection between a material’s structure, properties, processing, andperformance in the field of materials science and selecting the correct materials for a particulardesign. Despite their significance, materials science as a field is often introduced later inengineering education – generally in the second year of university studies, following first-yeargeneral engineering courses. At that point, students have already established their academic focusand are less likely to appreciate how the study of materials science can play a role in their
monotonous.To address this, a project-based learning (PBL) approach was introduced as supplementaryinstruction. Literature suggest that PBL has emerged as a transformative educational approachthat significantly enhances student understanding, student engagement, knowledge retention, andthe development of stronger interpersonal and communication skills ([1], [2], [3], [4]). Accordingto [4], PBL motivates students to take more responsibility of their own learning as it helps tobridge the gap between theory and practice [4]. Some other studies [5], [6] reported that PBLplays a significant role in developing critical thinking and problem solving skills, which areessential for engineers. The study on engineering education [6] also reported that PBL helps
a novel project-basedmaterials science course that integrates experimental design, computational modeling, and peer-reviewed publication opportunities. Leveraging AI-powered tools such as Mathematica, the courseequips students with essential skills in programming, modeling, and the application of AI andmachine learning—competencies increasingly critical in modern engineering practice [1, 2].Central to the course is a project-based framework in which students design, execute, and analyzeexperimental systems while creating interactive Mathematica simulations. These simulationsenable students to model material behavior, generate predictive insights, and visualizeexperimental outcomes. By utilizing industry-standard tools, students gain hands
, she received the ”President of Pakistan Merit and Talent Scholarship” for her undergraduate studies.Dr. Bilal Mansoor, Texas A&M University Bilal Mansoor is an Associate Professor in the Materials Science and Engineering Department at Texas A&M University. He holds a Ph.D. in Materials Science and Engineering from the University of Michigan, specializing in the solid-state processing of metallic alloys. Dr. Mansoor’s research advances processing methods for novel alloys and material architectures, with two primary goals: (1) uncovering the intricate relationships between microstructure and environmental factors, and (2) designing lightweight, strong, and corrosion-resistant alloys. His work explores how
to computational speeds have made it more powerful [1, 2].Machine learning (ML) generally refers to algorithms (e.g., linear regression, non-linearregression, random forest) that turn input data into output data, and in doing so, achieve AIgoals. ML algorithms typically require tens to hundreds of data points. Deep learning can beconsidered a part of ML, and both fit in the broader term of AI. Deep learning algorithms(e.g., neural networks) typically work on thousands of data points and are, as such, used in‘big data’ engineering applications.AI-powered technologies are becoming more prevalent in daily life and the workforce,making it crucial to understand and adapt to using new large language model (LLM) tools,such as Chat Generative Pre
. Ahmed5,7, Raymond B. Bako6,7, Akinlolu Akande2,3 1 Department of Mechanical Engineering, Ahmadu Bello University, Zaria, 810222, Nigeria2 Mathematical Modelling and Intelligent Systems for Health and Environment Research Group, School of Science, Atlantic Technological University, Sligo, F91 YW50, Ireland. 3 Modelling and Computation for Health and Society, Atlantic Technological University, Sligo, F91 YW50, Ireland. 4 Department of Civil Engineering, Ahmadu Bello University, Zaria, 810222, Nigeria 5 Department of Chemical Engineering, Ahmadu Bello University, Zaria, 810222, Nigeria 6 Department of Educational
education and development. These courses are typicallypositioned in the later stages of the curriculum, offering students an opportunity to applyfundamental knowledge from previous courses, develop technical skills necessary within theirdiscipline, and work collaboratively to accomplish complex tasks that increasingly explorebroader societal impacts [1-3]. In total, many in engineering (and in several other STEMdisciplines) describe the collection of these learning outcomes as “hands-on” learning, anessential component of the curriculum for students to learn by doing in both authentic andsimulated environments [4-6].Recently, leaders in science and engineering education have suggested that these laboratory,design, and capstone courses should
) includingenvironmental impacts, social impacts, and economics.” The teaching methods includedassigning the textbook chapter on environmental and societal issues during the first week of thesemester, integrating sustainability topics into lectures consistently throughout the semester, andrequiring students to consider social and environmental issues as part of two open endedprojects. Sustainability-related topics were worth about 6% of the overall course grade. Teachingand assessment methods in the course were intentionally selected to provide students choice andflexibility, aligned with Universal Design for Learning (UDL) principles which are intended tocreate a neuroinclusive environment. Examples of UDL practices included: (1) allowing studentsthe choice of
interact with the phenomenon of the technology gap to producemarginalization in the highly technology-dependent discipline of engineering education.Therefore, there is a need for an evaluation of how extensive the impact of marginalization onapplications of constructive alignment has been, and subsequently the development of anupdated model of constructive alignment that addresses issues of marginalization.1. IntroductionConstructive alignment is the pedagogical concept that students learn better when the learningoutcomes, learning activities, and assessments in an educational offering are designed holisticallyto support one another and allow students to demonstrate their understanding as directly aspossible [1]. Introduced by Biggs in 1996 [1], a
science research may contribute (or not) to larger social justice aims. Here, we presentthree such written assignments along with student outcomes, our lessons learned through thiscurricular reform, and suggestions for anyone interested in implementing similar changes in theircourses.Introduction: A long-running challenge in engineering education is the need to successfully bridge thegap between what students learn in the classroom and what they may need to know when theybegin work as professional engineers [1]. Educators have approached this challenge from avariety of angles and with differing purposes. In some cases, we aim to better equip students toanalyze and understand how social contexts (like politics, culture, and media) might
. Overall,the findings show it is feasible to radically redesign introductory MSE around computationalmodeling while maintaining positive student experiences.1. IntroductionThis paper reports on student perceptions of an introductory materials science and engineering(MSE) course redesigned to center around computational models and taught with a novelinteractive textbook with the computational models embedded. This redesign is in response totwo trends. First, computation is transforming MSE, and the curriculum should reflect that fact.Second, computation and computational representations can be harnessed to create powerfultools for learning. This paper is a continuation of the work presented in [1] which described theredesigned course without
[X material] good for [Y application]" or "why might [X conditions] lead to failure in [Ymaterial]"; the professor can read aloud some of the initial answers, provide input on these, andcontinue seeking further comments. This can include creating and adjusting questions in realtime during class. Examples of these activities with their associated participation rates inanonymous discussions will be presented.BackgroundPrior work has shown that active engagement in class, beyond simply attending class, leads toincreased academic performance [1]. However, some students face social anxiety or fear beingembarrassed if they were to make a mistake, which is prevalent especially in front of peers [2],[3]. This has been connected to student reluctance
modifications.IntroductionCapstone courses in engineering education denote critical milestones, with the overall goal toprovide students opportunities to apply their understanding of the overall curriculum in real-world challenges [1, 2]. A key component to have a successful capstone experience is the abilityof students to engage in both divergent and convergent thinking [3], as such, the overallcurriculum must provide design learning experiences that provide students with the fundamentalskills, knowledge, and opportunities to practice both divergent and convergent thinking.Oftentimes, these opportunities exist in explicit design courses. Additionally, design coursesmust engage students in design thinking processes, providing a framework for students tonavigate and
) ©American Society for Engineering Education, 2025 Teaching Mechanical Properties of Materials Through CrochetAbstractThe growth of the maker movement has led to a 14-fold increase in the number of makerspacesworldwide over the past decade [1], yet many institutions struggle to retain a gender-diverse userbase of these facilities [2]. Gendered ideas persist about who belongs in a makerspace, withmasculine-stereotyped environments setting a less-than-inclusive tone [3]. Yet women are thepredominant practitioners of fiber arts [4], one of humanity’s original engineering skills thatdates back to the Neolithic time period [5]. This work aims to challenge students’ preconceivednotions of which skills belong in a maker space by introducing
used in engineering,including natural materials. a b Figure 1. Microstructures of (a) stainless steel[1] and (b) aeolian sandstone.This paper reports on a geology-based laboratory module for an introductory MSE course. Thislab occurred at the beginning of the term, so it could only require minimal course content. Theaim was to introduce students to MSE concepts, such as quantifying microstructures, whilereinforcing measurement error principles taught in prerequisite courses. The learning goals forthe lab were to: • Calculate measurement errors, • Analyze feature sizes and size distributions, and • Evaluate sources of uncertainty in microstructural analysis.Geological
. The goalsof the activity are threefold: (1) give students an opportunity to meet each other and the lab TAsin a low-stakes setting, (2) familiarize students with the online system they will use throughoutthe semester for assignment submissions, and (3) model the format and expectations for the labreports they will prepare in the course.Studies have shown that working engineers typically devote 20-40% of their workday tocommunication (a percentage that increases with career advancement) but less than 5% ofengineering education is devoted to communication skills [1]. Engineering students are exposedto technical writing at various points during their academic careers. Because students in MASC310L are from a range of disciplines and at a range of
OutIntroductionThis paper is focused on the methodology to inspire students to have an earnest aspiration forexperiential learning [1] and to introduce them to new materials characterization techniques througha balanced combination of project-based learning (PBL)[2] and project-led education (PLE)[3]. ThePBL methodology is widely adopted, researched, assessed, and continuously adjusted to newrealities and societal inquiries [4-6]. The method was expanded and reviewed with an emphasis onthe development and acquisition of learning, experimental, and communication skills, practicaldimensions of learning, and relevance to the society in which the students live [7-9]. Here, theadoption of a balanced combination of PBL and PLE was motivated by challenges