Paper ID #48417BOARD # 99: Work in Progress: AI in online laboratory teaching - A SystematicLiterature ReviewMr. Johannes Kubasch, University of Wuppertal Johannes Kubasch is a mechanical engineer and research associate at the Chair of Technical and Engineering Education at the University of Wuppertal. As a engineer in automotive engineering, he initially worked in the automotive supply industry in the development of airbag systems before moving to the University of Wuppertal to work in the field of engineering education. In the past, he worked on the AdeLeBk.nrw project to digitize the university training of prospective
Paper ID #47781BOARD #476: Work in Progress: Combining Python and Simulation to OfferEasy Visualization in Early Years TeachingDr. Susannah Cooke, ANSYS, Inc. Susannah Cooke is a Senior Product Manager at Ansys, managing Ansys Academic software. She works with universities to ensure that Ansys tools can be deployed to best effect in teaching and research. She holds an MEng and DPhil in Mechanical Engineering from the University of Oxford, where her doctoral thesis focused on fluid flow around tidal turbine arrays. She is excited by the overlap between industry engineering and pedagogical practices, especially where these
adaptability [1]. In these settings, students frequentlyturn to teaching assistants (TAs) for assistance with lab procedures, equipment setup, andtroubleshooting. This dynamic creates a dependency that, while helpful in the moment, can leadto challenges for both students and TAs. The repetitive nature of these inquiries significantlyburdens TAs, who usually cannot answer everyone’s questions throughout the laboratory classtimes. Furthermore, certain student questions need consistent answers that the lead instructorproves correct. Another challenge is establishing a structured support diagnostic meant to answerstudent problems in a way that guides students to their answers rather than revealing themimmediately. This allows students to engage in
work.Previous Work Practical laboratory experiences including engineering labs and projects represent essentialelements of learning [1], [2]. As part of intensive laboratory experiences, robots have had alongstanding positive impact on education of students at all levels. Small, wheeled, programablemobile robots like LEGO Mindstorm series have been used as motivational tools to attract studentsto STEM fields in general [3], as well as to help students (and teachers) learn how to program [4]- [6]. However, at the practical level of industrial robot programming, the use of industrialmanipulators for teaching programming robotic tasks was often the only option. Expensivehardware, proprietary software, and required safety measures made programming of
a growth in academic integrityfilings since the advent of ChatGPT. In fact, [2] points to a Stanford University survey where1/6th of students said they had used ChatGPT on assignments or exams. This article [2] alsopoints towards the issues of hallucinations, where AI focuses on generating text that sounds goodbut may not be scientifically accurate. However, [1] also points to potential efficiencies andutility of AI in higher education, such as teaching ethical use of AI, growth of tutoring/teachingassistants and for operational efficiencies. Auon [3] discussed the impact of AI on the humanexperience in physical (personalized medicine/drug delivery and disease identification),cognitive (increased workplace productivity, focused effort on
sequential coursework, especially until the senior year. The use of AI to help solve engineering problems as a collaboration tool is being used inengineering classrooms at increased frequency, hence the motivation of this paper to look at theuse of AI in developing professional skills in engineering undergraduate education. Using AI asprompts to help students draft papers or laboratory reports is starting to emerge in undergraduateengineering programs, although using AI to teach or enhance professional skills seems to be anew area of research [5]. One paper found that the typical use and extent of using generative AIin engineering classes based on student surveys [6] and the general impact of AI incommunication skills training has been
Paper ID #46417BOARD # 94: WIP: Shaping the Future of Learning: The rAIder Strategyfor Applied AI-Driven Education at MSOEDr. Nadya Shalamova, Milwaukee School of Engineering Nadya Shalamova is an Assistant Professor and the Director of the Technical Communication Program at the Milwaukee School of Engineering. Her research interests include interdisciplinary collaboration in engineering, science, and technical communication.Dr. Olga Imas, Milwaukee School of Engineering Olga Imas, Ph.D., is a professor of biomedical engineering at the Milwaukee School of Engineering, where she teaches a variety of courses in biomedical
solving, instructional material design, teacher training, and gender studies. She teaches undergraduate courses in environmental management, energy, and the fundamentals of industrial processes at the School of Engineering, UNAB. She currently coordinates the Educational and Academic Innovation Unit at the School of Engineering (UNAB). She is engaged in continuing teacher training in active learning methodologies at the three campuses of the School of Engineering (Concepci´on, Vi˜na del Mar, and Santiago, Chile). She authored several manuscripts in the science education area, joined several research projects, participated in international conferences with oral presentations and keynote lectures, and served as a referee
includes discovering how AIaffects students after they enter industry. The impact of AI on engineering students’ knowledgeof technical material taught in engineering education also continues to remain unknown. Alongitudinal study following students throughout their education and into industry could answersome of the unknowns about how AI impacts students as they enter industry.References[1] A. M. F. Yousef, A. M. A. El-Haleem, and M. M. Elmesalawy, “Determining Critical SuccessFactors for an Online Laboratory Learning System Using Delphi Method,” in 2022 InternationalConference on Intelligent Education and Intelligent Research (IEIR), Wuhan, China: IEEE, Dec.2022, pp. 86–93. doi: 10.1109/IEIR56323.2022.10050041.[2] E. Liao, “Research on Teaching
, Indiana. He received his PhD in 2007 from Virginia Tech in Engineering Mechanics where he studied the vestibular organs in the inner ear using finite element models and vibration analyses. After graduating, he spent a semester teaching at a local community college and then two years at University of Massachusetts (Amherst) studying the biomechanics of biting in bats and monkeys, also using finite element modeling techniques. In 2010, he started his career teaching in all areas of mechanical engineering at the University of Southern Indiana. He loves teaching all of the basic mechanics courses, and of course his Vibrations and Finite Element Analysis courses. ©American Society for Engineering
Paper ID #48675RISC-V System-on-Chip Design Textbook and CourseDr. Rose Thompson, Oklahoma State University Rose Thompson received her Ph.D. in Electrical Engineering from Oklahoma State University and two B.S. degrees in Electrical Engineering and Computer Engineering from the University of Washington. She has also designed chips at the Air Force Research Laboratory. Her professional interests include SoC design and verification, custom instruction set architectures, branch prediction, memory systems, and secure computing. Rose also enjoys biking, hiking, rock climbing, and playing the piano.Prof. David L Harris, Harvey
Paper ID #46287The Development of Concept-Space, a Digital Workspace that Mirrors Howthe Brain Organizes and Expands Knowledge, Reveals Positive Impacts forLearners, Teamwork and TeachersDr. Ing. David Foley, Universite de Sherbrooke David Foley, Dr. Ing. teaches engineering design at Universit´e de Sherbrooke where he supervises teams of students in realizing their capstone design projects. A majority of his time for the last 14 years have been invested in developing breakthrough technology to better support human thinking and learning processes. ©American Society for Engineering Education, 2025
-basedcollaborative tools 11 and virtual laboratories 12, are critical for its effectiveness. When thoughtfullyapplied to courses like tool design, where hands-on learning and collaboration are essential, theflipped classroom model has the potential to revolutionize engineering education 13.1.2. Balancing Traditional and Modern PedagogiesTraditional teaching methods in Tool Design courses, while effective for foundational theoreticallearning, often emphasize rote memorization and isolated problem-solving, limiting creativity andteamwork development. The rigid separation of theory from practical application further hindersstudents' ability to connect abstract concepts to real-world scenarios, particularly in diversesettings like HSIs, where traditional
, personalized online learning experiences. We evaluate the effectiveness of this methodthrough a series of case studies and provide guidelines for instructors to leverage these technologiesin their courses.1 IntroductionLarge Language Models (LLMs) and their emerging skills provide educators with new capabilitiesto improve our teaching and save time. LLMs like ChatGPT have emerged as powerful tools thatcan assist in creating educational content and interactive learning experiences [1].For digital system design and computer architecture, traditional education often relies on expen-sive hardware, specialized software, and physical laboratory spaces. These requirements can limitaccess to hands-on learning experiences, particularly for students in
Project. There are variousCornerstone Projects that have been used in this course: a Windmill System introducing powergeneration, a Water Filtration System based on a partnership with the Metropolitan Sewer District,and the most recent project added to the course was based on an autonomous robot. New projectsare typically tested as a proof of concept first with undergraduate teaching assistants, then in thesummer iteration of ENGR 111. The summer iteration of ENGR 111 is a smaller enrollment (tento fifteen 3-4 person teams total) to allow for quicker pivoting should a situation arise. The smallersummer enrollment allows the instructors to pilot the new project with the expectation of using thenew project the following spring semester. As
Professor of Educational Technology at the University of Florida. His interests focus on the design of technology-enhanced learning environments and rigorous mixed-method research on the effective conditions for tecDr. Christine Wusylko, University of Florida Christine a postdoctoral fellow at the University of Florida. She draws on over 10 years of experience teaching science and technology across grade levels K-16, to produce useful and usable knowledge, which is both driven by problems of practice and is theoretically grounded. Her research and development program is centered on helping young people develop AI and STEM literacy in authentic learning environments.STEPHANIE KILLINGSWORTH, University of FloridaBrian
product development lead at zyBooks. Joe is also an adjunct professor at the University of Rhode Island teaching software engineering. Prior to working at zyBooks, Joe was an award-winning career and technical educator, teaching computer and software engineering to high school students. He is President of the Computer Science Teachers Association (CSTA) of Rhode Island and is a member of the CS4RI (Computer Science for Rhode Island) board, where he serves as a voice for CS educators and the computing industry.Chelsea L Gordon, zyBooks, A Wiley Brand Chelsea Gordon received her PhD in Cognitive Science at University of California, Merced in 2019. Chelsea works as a research scientist for zyBooks, a Wiley company that
published an ASEE conference paper last year on the effects of ChatGPT on student learning in programming courses. With over seven years of experience teaching Computer Science courses, she is currently a faculty member at Embry-Riddle Aeronautical University’s Department of Computer, Electrical, and Software Engineering, where she teaches computer science courses.Dr. Luis Felipe Zapata-Rivera, Embry-Riddle Aeronautical University Dr. Luis Felipe Zapata-Rivera is an Assistant Professor at Embry Riddle Aeronautical University. He earned a Ph.D. in Computer Engineering at Florida Atlantic University, in the past worked as an assistant researcher in the group of educational Technologies at Eafit University in Medellin
Paper ID #49134WIP: Gen AI in Engineering Education and the Da Vinci CubeTammy Mackenzie, The Aula Fellowship EcoTech CEO, inventor, MBA, human rights activist, philosopher, and researcher of the intersections between strategic management, institutions, and systems theories.Dr. Lisa D. McNair, Virginia Tech Lisa D. McNair is Professor of Engineering Education and Director of Arts and Education at the Institute for Creativity, Arts and Technology (ICAT) at Virginia Tech. She is an executive committee member for a2ru and an editorial board member for Ground Works journal. Her research and teaching interests include
Northern University Dr. Hylton is an Assistant Professor of Mechanical Engineering and Coordinator of the First-Year Engineering experience for the T.J. Smull College of Engineering at Ohio Northern University. He previously completed his graduate studies in Mechanical EnginDr. Bryan Alan Lutz, Ohio Northern University Bryan A. Lutz (he/they) is an Assistant Professor of Rhetoric and Composition at Ohio Northern University. His research examines how activists, advocates, and public and private organizations use technology and writing to define an identity, argue, and act to solve (or make) problems. He teaches organizational communication, academic writing, and professional writing courses. Dr. Lutz has published with
system, to enhance engagement. 3. Providing real-time, individualized feedback to support self-regulated learning and metacognition.We evaluated the impact of these features on student engagement, performance, andmetacognition, first with a laboratory study, then in a classroom setting. Our findings provideinsights into how gamification and deliberate practice can address key challenges in teachingSQL and similar technical skills.2. BackgroundNumerous online SQL learning tools, such as SQLBolt, Khan Academy, and SQLZoo, offerstructured practice exercises, however they do not provide progress feedback to the instructor,nor do they permit an instructor to tailor the topics or topic order. The SQLBolt [2] tutorialprovides immediate, context
project, where he led data analysis efforts using advanced statistical and machine learning techniques.Gabriel Tomas Fierro, Colorado School of Mines Gabe Fierro is an Assistant Professor of Computer Science at Colorado School of Mines, with a joint appointment at the National Renewable Energy Laboratory. Dr. Fierro usually works at the intersection of databases, cyberphysical systems, and knowledge graphs where his research focuses on the design and development of data systems that enable sustainable practices at societal scale.Dr. C. Estelle Smith, Colorado School of Mines Dr. C. Estelle Smith is a Tenure-Track Assistant Professor in the Department of Computer Science at the Colorado School of Mines. Her research