course are as follows: • Develop the governing equation for a mechanical system. • Represent the transfer function for a system. • Describe the analogy between mechanical and electrical systems. • Represent a system in state space. • Predict a system’s response by solving its governing differential equation. • Describe the effect of mass, stiffness, and damping on a mechanical system response. • Predict the behavior of a vibratory system. • Perform simulation of the behavior of a system with computer software.To enhance students’ achievement of the course learning outcomes, a course project wasincorporated into the class. This project consists of two parts, part 1: system identification andpart 2: system
, where the facultymember as a ‘sage on the stage’ and students primarily (often passively) listen to the coursecontent being presented, promotes a lower level of learning and low attention span (withattention level dropping after 10 minutes in a typical 50-minute lecture) and low knowledgeretention [1], [2]. In contrast, active learning techniques, where the instructor is more of a ‘guideon the side’ have been shown to foster a positive learning environment, increase studentengagement, promote communication skills, make the overall learning experience more effectiveand appealing, and improve student grades on summative assessments [3]-[5]. Particularly forindividuals from underrepresented groups, active learning can help close the achievement
down complexsteps and promote critical thinking when teaching numerical methods. To understand this better, wefocused on the following research questions. 1. How might concept maps help undergraduate students connect knowledge in numerical methods? 2. How might concept maps help undergraduate students connect knowledge about entrepreneurial mindset?BackgroundThroughout the history of education, the use of visual aids and pedagogical tools has been crucial inhelping convey the complex process, making it engaging and accessible for learners. In today's world ofacademics visual tools are used to show thought process, designs and also convey various types of data.As engineering students grapple with abstract concepts and complex
research also involves autonomous motivation, self-regulated learning, technology adoption, and learning analytics adoption. ©American Society for Engineering Education, 2024Introduction Humans have a long history of striving to better understand the natural world. Theknowledge accumulated is then frequently leveraged to develop new ideas yet to be tested andnew mechanisms for the benefit of human welfare. Humans accomplish extraordinary feats butsolving today’s complex problems require specialized learning and time. In the modern world,these types of problems are increasingly common and solving them quickly is becomingincreasingly important [1]. Artificial intelligence (AI) has been increasingly
(Institute of Electrical and Electronics Engineers, AmericanSociety for Engineering Education, American Society of Civil Engineers, AmericanSociety of Mechanical Engineers, American Institute of Chemical Engineers, AmericanInstitute of Mining, Metallurgical, and Petroleum Engineers) and National Council ofExaminers for Engineering and Surveying. ABET’s mission is to set standards againstwhich professional engineers in the United States were held for licensure and focus onstudent experience (1). The National Society of Professional Engineers describeslicensure as the credentials to earn client’s trust and states that only engineers withProfessional Engineer (PE) license have the authority to sign and seal engineeringplans. (2). While engineers earn
’ related matters and policies. He is also the Academic Coordinator of the first year engineering program (Schulich Studio) since June 2023. Dr. Ghasemloonia is a registered Professional Engineer (P.Eng.) in Alberta. ©American Society for Engineering Education, 2024 Classification of alternative grading approaches: review and reflections from practiceAbstractThe purpose of this paper is to review and categorize how alternative grading has been practicedin higher education and reflect on how we, as instructors in a university, apply it in their courses.In this paper, the potential issues of traditional grading are characterized in three aspects: (1)judgemental, (2) high
Paper ID #42774Work in Progress: The Roles of Design and Fabrication in Upper-DivisionMechanical Design CoursesLeah Mendelson, Harvey Mudd College Leah Mendelson is an Associate Professor of Engineering at Harvey Mudd College.Drew Price, Harvey Mudd College Drew Price is the Machine Shop Manager at Harvey Mudd College. ©American Society for Engineering Education, 2024 Work in Progress: The Roles of Design and Fabrication in Upper-Division Mechanical Design CoursesAbstractThis work in progress (WIP) paper focuses on two aspects of upper-division undergraduatemechanical design courses: (1
dynamics. By comparing ChatGPT’s entirereasoning process and individual steps with human reasoning, this investigation unveils both itsconstraints and capacities. The results show that ChatGPT’s limited capability to understand theprofound implications of text. It addresses the need for caution when employing it in reasoningtasks within the context of mechanical engineering education.Key words: mechanical engineering education, ChatGPT-4, engineering reasoning.1. IntroductionReasoning skill, often denoted as logical reasoning, constitutes the cognitive ability to engage inclear, structured thinking, analyze information, and logically derive valid conclusions on thefoundation of evidence and facts [1]. Within the domain of mechanical engineering
of the new course based on the experiencegained and the assessment data collected in the previous offering. Also, several examples of thesmart products designed by student teams are discussed. The course contains active learning andproject-based learning components. A smart flowerpot device was integrated into the lectures asan active learning platform. For project management, students are introduced to the Agilemethod, which is widely used in software development companies and is the leading softwareengineering methodology for IoT development.1. IntroductionPhysical objects (things), such as thermostats and doorbell cameras, connected to the Internetallow remote network access to these devices creating the so called Internet of Things
structures to later carry outexperimental work.e. Experimental tests that can correlate to the finite element analyses mentioned above. Inaddition, damping properties are also determined.Hands-on laboratories including finite element analyses and experimental tests are highlyencouraged by ABET [1] and are commonly performed by R&D departments in the industry todevelop new products. In the past there have been other ASEE works related to the topicspresented here [2],[3].2. Classification of composite materialsA composite material is produced combining two different constituent materials with the purposeof creating a material that will have some advantages over readily available materials. There areseveral types of composite materials.o Single
ME 4010 System Dynamics II. Equations (1) and (2) present the governing equation and its corresponding transfer function of the temperature control system. y (t ) + y (t ) = Ku (t − td ) (1) 𝐾 (2) G(s) = 𝜏𝑠+1 𝑒 −𝑡𝑑 𝑠 Where y(t) is the output and u(t) is the input. K is steady state gain, τ is the time constant and td is the time delay of the input. Fig.1 presents a comparison between the experimental and simulated step responses for K=0.752, τ=211 s, and 𝑡𝑑 = 30 s. Fig. 1 Comparison of experimental
PDMsoftware into small engineering design teams may produce different benefits than its use in largeteams and long-term projects. Further, a need exists to bring PLM concepts and tools earlier intothe curriculum to encourage student development.1. IntroductionThroughout the early 21st century, the engineering industry has experienced dramatic changesacross business units due to the digital revolution. For example, product lifecycle management(PLM) software has pushed companies to improve collaboration among their divisions toincrease design, manufacturing, and business efficiency. PLM software can fall into manycategories, including computer-aided design (CAD), computer-aided engineering (CAE),computer-aided manufacturing (CAM) and product data
commuters. The University has a high percentage of low-income (33%) and first-generation (37%) students. Among degree-seeking students, there is a high number of non-traditional students (30%), students with spouses (37%) and students with children under age 12(19%). While tuition is low, part-time attendance is high at 36% of students. These factors affectthe overall graduation rate, which is low at 35% (nationally standardized IPEDS rate forcompletions in 150% time) and the overall 1-year retention rate of 68% for baccalaureate-degreeseeking students. Institutionally, Utah Valley University receives by far the greatest amount ofPell grants awarded to students at any public institution of higher education in its state (NCES2020/21).The Mechanical
Engineering at The University of Delaware. He gained his Ph.D. in Mechanical Engineering from The Pennsylvania State University in 2015, where he worked on experimental combustion research applied to gas turbine engines, and his M.Eng. in Mechanical Engineering from Imperial College London in 2010. Alex’s research focuses on the transfer of learning between various courses and contexts and the professional formation of engineers. ©American Society for Engineering Education, 2025 Reinforcement of First-Year Technical Communications Skills in Middle Years Courses Jenni M. Buckley PhD1-3, Amy Trauth PhD1,4, David Burris PhD1, Alex DeRosa PhD1 1 University
thickness, students canexplore Ultimate Tensile Strength (UTS). Additionally, using a torque wrench and anarrangement of gears mounted on shafts enables students to measure the angle of twist. Thesehands-on experiments foster an engaging, accessible learning environment that is directlyapplicable to their coursework.Literature ReviewMechanics of materials courses are widely recognized as challenging for both instructors andstudents due to the highly analytical and theoretical nature of the content. According to Wang etal. [1], this difficulty arises from the complex concepts involved and the disconnect betweentheoretical material behavior and students' practical experiences.In response to these challenges, several studies have highlighted the
senior years for mechanical engineeringprograms. This paper presents a comprehensive design project, the analysis of the bolted-flange-gasket design project based on API(American Petroleum Institute)-6A standard, whichconnects a high-pressure tank (5000 psi) to a piping system. In this project, students wererequired to study and understand the API 6A standard. Then, they were asked to use the API 6Astandard to design a bolted-flange-gasket assembly by creating models and selecting materials.Finally, they conducted the FEA simulation to prove that the design would satisfy the designrequirement of no oil leakage. This paper will present the implementation of this project, theclass survey results and student feedback in the 2023 spring semester.1
engineering and therefore itis crucial to understand any demographic discrepancies that may exist. This paper examines theconfidence of students in two second year Engineering classes by having them predict theirscores both before and after quizzes and then compares those predictions to their actualperformance. This is then broken down by student reported demographic data to supportprevious research and to determine any new emerging trends. The data suggested that studentswith lower grades tended to overestimate their performance, while higher achieving studentstended to underestimate their abilities. This lower confidence was particularly true for non-maleand older students.1. IntroductionConfidence and self-efficacy beliefs are linked to student’s
publications/presentations at technical and engineering education conferences. Areas of expertise and research interest include, Deformation & Failure Mechanisms, Materials Science, Fracture Mechanics, Process-Structure-Property Relationships, Finite Element Stress Analysis Modeling & Failure Analysis, ASME BPV Code Sec VIII Div. 1 & 2, API 579/ASME FFS-1 Code, Materials Testing and Engineering Education. Professionally registered engineer in the State of Texas (PE). ©American Society for Engineering Education, 2025 Teaching Conflict Management for TeamworkThis is a Work in Progress paper.IntroductionTeamwork ability, a highly recognized soft skill in the engineering
Education, 2025 Incorporating Industry-Sponsored Technical Writing into Engineering LaboratoriesIntroductionLaboratories are critical courses within engineering curricula because they allow students tobridge the gaps between conceptual knowledge and practical applications. For example, thematerials testing laboratories in mechanical engineering programs allow students to find materialproperties and safely test components before finalizing designs [1]. In 2022, ABET releasedupdated criteria for accredited programs from 2023-2024. Under criterion 3, ABET notes thatstudents should be able to solve complex problems, apply design to produce solutions,effectively communicate with a range of audiences
feedback.Overall, design review positively impacted their design work (80.8% positive response) andpositively changed the way the students view themselves as engineers (84% positive response).1 IntroductionME 347 is a third-year undergraduate design course for mechanical engineers which incorporatestheory and design with CAD (SolidWorks). The course gives them the most significant designexperience so far in the curriculum, and it is an important pre-requisite course for the firstsemester of senior design. Students take an earlier course, ME 250, which introduces the designprocess and the basics of CAD modeling (simple geometry and drawings) and incorporatesbuilding a physical model using traditional machine shop techniques and 3-D printers. While
, andapplication of theoretical knowledge. While ChatGPT-4o demonstrates the ability toprovide robust explanations, it often lacks the contextual depth required for higher-orderconcept mastery, especially when reasoning from diagrams. These findings align withexisting literature highlighting AI’s limitations in discipline-specific support. Futureresearch should refine AI responses to better align with engineering problem-solvingapproaches and explore hybrid models integrating AI assistance with human instruction,potentially leading to more effective AI-augmented learning platforms in mechanicalengineering education. 1. Introduction Generative AI tools are becoming increasingly prevalent in college assessment. Studentsuse AI tools for studying
endeavors [1], [2]. Educators have been finding ways of integrating EMLinto their courses such as online discussions [3] and e-modules [4] that do not require class time.The new assignments were created to encourage students to become more curious about thebroader world and hopefully retain knowledge for future courses, and they were all completedoutside of class [5].This research is the first part of a planned longitudinal study to determine the effects of thiscourse modification. Surveys and reflective statements are often used by researchers tounderstand student learning. Analysis of reflective narratives is discussed in Badenhorst, et al.[6] and Ilin [7]. For the first part of this research students were tasked with reflecting on theirown
a structured process that typically follows a series of well-defined steps to achieve optimal solutions for engineering problems.[1], [2] Thecommon steps in mechanical design include identifying the problem, establishingdesign requirements, generating concepts, analyzing and selecting the mostpromising concept, creating detailed designs, and finally prototyping and testing.Each step builds upon the previous one, ensuring that the final product meets thefunctional, economic, and safety requirements. Effective mechanical design ofteninvolves iterative refinement, where feedback from analysis and testing loopsback to earlier stages to improve the design further.The advent of AI tools like ChatGPT has introduced both opportunities andchallenges
award a full score of 5 points for participation, with an extra1 bonus point given to students who ranked in the top 50% of the participants. The effectivenessof this rubric in fostering active participation and encouraging greater effort on the pollingquestions is also discussed in this paper.IntroductionStudent engagement has been recognized as an essential factor in promoting academicachievement [1] and has gained a lot of research interest [2]. Gamification is one of the popularapproaches to student engagement and can be described as the incorporation of game designelements into nongame environments to engage individuals and promote desired behaviors [3, 4].Computer-based technologies are widely involved to support gamification in education
workingwith peers in the makerspace. We anticipate the outcomes of this study will provide implicationsfor faculty and staff makerspaces at other postsecondary institutions who aim to build aninclusive and accessible learning environment for all students.IntroductionThe dominant culture in western engineering has been defined by White men from middle toupper class backgrounds [1]. While local and national efforts have been made on a large scale todiversify the engineering student population and change this culture, there is still a significantdisparity in the number of STEM degrees awarded to women and other underrepresentedminority (URM) groups [2-6]. Within postsecondary engineering programs of study, thepredominance of White, males has been
andlimited interest in the project beyond achieving a grade. In this work-in-progress study, studentschose their own project groups and then completed a guided brainstorming activity whichincorporated elements of story-telling, with the aim of increasing the emotional investment of thegroup members in successfully completing the project. Purpose: Research Question 1: To whatextent does allowing students to choose a system dynamics project based on personal/emotionalconnections to the project help them increase their self-efficacy in system dynamics? ResearchQuestion 2: To what extent does choosing their own emotionally invested project improve studentcompetency based on project and over all grades? Methodology/Approach: Students completedpre/post
, vibration analysis, and data acquisition. In addition to technical knowledge,the course emphasizes critical skills such as data analysis, error evaluation, and technicalcommunication, essential for engineering practice. The course accommodates approximately 30students, divided into two sections of 15 students each.ABET Criterion 3 states that "engineering programs must demonstrate that their graduates havean ability to design a system, component, or process to meet desired needs." However, designinstruction is typically limited to freshman and senior years, with little emphasis during thesophomore and junior years as students focus on engineering science courses [1-3].This fragmented approach limits opportunities for students to develop design
reality demonstration was successfully performed for all projects. Three examplesof these projects and their outcomes were analyzed and presented: 1 - A geodesic dome for Marshabitation; 2- Dynamic Dolly; 3- Exofit Biomedical Device.Students evaluated the course design, including the XR prototype demonstration, was moreengaging. The evaluation of projects was less subjective, and the course design was moreinclusive than lecture-based courses. However, 54.4% expressed that this course required moreworkload than the traditional lecture-based courses.Keywords: Extended Reality, Virtual Reality, Augmented Reality, Engineering Education,Mechanical Engineering, Design, Biomedical Engineering. Body of the
, ventilation and air purification. Filter standards andfilter testing technologies were discussed. ASHRAE and OSHA guidance concerning healthyindoor air quality (IAQ) was covered. A low-cost air quality sensor was installed in theclassroom that streamed data to the internet. Students were assigned projects utilizing this sensorand the neighboring outdoor sensors, which triggered interest in citizen science.1. IntroductionAir quality has been a subject of college education in engineering for many years, often includedin environmental engineering programs, which are frequently integrated with civil engineering.Civil and environmental engineering departments exist at leading institutions such as Berkeley(https://ce.berkeley.edu/), Stanford (https
workforce for the future. I. INTRODUCTION AND BACKGROUND In this era where fossil fuel usage continues to rise despite the growth of renewable energyoptions worldwide, the holistic need for reducing greenhouse emissions is more critical thanever [1]. It is a well-accepted scientific fact that climate change, global temperature rise, andCO2 emission levels are interconnected. Over the past century, the Earth's average surfacetemperature has steadily increased, primarily due to a surge in greenhouse gases, which is anoutcome of human activities such as the increased use of fossil fuels, deforestation, andindustrial processes. As an alternative to fossil fuels and to solve the problems of climatechange, crucial