Paper ID #45510AI-Human Transference Learning and Assessment: Optimizing KnowledgeTransfer and Understanding through AI-Generated ContextualizationDr. Razvan Cristian Voicu, Robotics and Mechatronics Engineering, Kennesaw State University, Marietta,GA Dr. Razvan Cristian Voicu is a faculty member in the Department of Robotics and Mechatronics Engineering at Kennesaw State University. His research interests include artificial intelligence, robotics, and the development of AI-driven systems for knowledge transfer and adaptive learning. Dr. Voicu is dedicated to exploring innovative applications of AI to enhance learning and problem
Paper ID #45562Empowering Undergraduates with NLP: Integrative Methods for DeepeningUnderstanding through Visualization and Case StudiesNilanjana Raychawdhary, Auburn UniversityChaohui Ren, Auburn University [1] Mohamed, Abdallah. ”Designing a CS1 programming course for a mixed-ability class.” Proceedings of the western Canadian conference on computing education. 2019. [2] Shettleworth, Sara J. Cognition, evolution, and behavior. Oxford university press, 2009.Dr. Cheryl Seals, Auburn University Dr. Cheryl Denise Seals is a professor in Auburn University’s Department of Computer Science and Software Engineering. She
preparedness, compromising theirability to succeed and progress.This study introduces a new strategy to enhance retention by implementing a structured,proactive advising model that emphasizes early, personalized engagement between students andfaculty advisors. This advising framework prioritizes frequent and clear communicationregarding placement and academic progress through personalized emails, one-on-one Zoommeetings, and in-person advising sessions. Mathematics placement, given its foundational role inengineering curricula, serves as the centerpiece of this advising model. The framework providesstudents with academic planning support, fosters meaningful student-faculty interactions, andcultivates student ownership of their educational
engineering education, including a project introducing the humanities into environmental engineering education through a National Endowment for the Humanities grant. She has worked on projects to develop activities for K-12 students, and is the founder and director of the SWEET (Society of Women Engineers: Engineers in Training) Outreach Program at Mercer University, funded by the Engineering Information Foundation (EiF). Her research and educational work have most recently been funded by the NSF, U.S. EPA, and the EiF. She currently serves as the Co-Faculty Advisor for Mercer University’s Student Chapter of the Society of Women Engineers (SWE).Halley Elizabeth Smith, Mercer University ©American
Paper ID #45595Call to Action!Dr. Anna K. T. Howard, North Carolina State University at Raleigh Anna Howard is a Teaching Professor at NC State University in Mechanical and Aerospace Engineering where she has led the course redesign effort for Engineering Statics. She received her Ph.D. from the Rotorcraft Center of Excellence at Penn State University and is one of the campus leaders of Wolfpack Engineering Unleashed. She has launched and is currently chairing the College Teaching Committee for the NC State College of Engineering.Dr. Sally J. Pardue, Tennessee Technological University Sally Pardue, Ph.D., is an
skills. Overall, a well-executed senior project course notonly offers a significant learning experience but also an invaluable one.To ensure that senior project courses remain practical and enriching, faculty have incorporated varioustechniques and approaches over the years. Recognizing the importance of community engagement, manyinstitutions have integrated a service-learning component into their senior project courses [1, 2]. Thisapproach encourages students to consider the broader societal impact of their work. Beyond societalawareness, educators have also aimed to use the senior project as a platform to foster lifelong, self-directed learning skills [3-5].Over the years, educators incorporated activities to foster and encourage development
future research as institutions are looking to use multiple assessment methods to moreprecisely evaluate their ABET SOs [10].Research GoalsThis study aims to examine (1) how students’ self-efficacy relates to their academic performanceas measured by GPA and FE exam scores, and (2) how academic performance may influencestudents’ perceptions of their abilities. Specifically, the study assesses the validity of indirectstudent assessments, using a survey given to outgoing senior students, to predict their mastery ofa subject through direct student assessments (i.e., FE exam data and cumulative GPA values).The study monitors how frequently students underrate or overrate their understanding of ABETSOs based on their measured performance. The goal is
was to score based on low,medium and high participation across all peer led team learning activities because participationdropped later in the course when students recognized the score in the class was high enough notto be impacted by reduced participation in the peer groups.Problem-solving through peer learning and group work allowed for an increase in engagement ofstudents with peers compared to simply memorizing and taking tests. Presenting students withchallenges that had to be solved through a small group systematic process helped studentsdevelop peer relationships beyond the instructor-student relationship. This was particularlyinsightful for best practices to support Veterans and active military adult learners that aretraditionally
critical thinking abilities they needto responsibly navigate and contribute to an AI-driven world.1. IntroductionArtificial Intelligence (AI) has become a transformative force across industries, redefining theworkforce and global problem-solving approaches, from healthcare innovations to environmentalsustainability efforts [1], [2]. Just like integrating computer science understanding and skills intothe curriculum has gained momentum in recent years, so is true for AI. Students need to betterunderstand how the technology works and how to use it properly. Despite the need for studentsto understand how AI works, disparities in Kindergarten through 12th grade (K-12) AI educationpersist. This leaves many students unprepared to navigate an AI
challenge traditionaluniversity experiences and feedback mechanisms, potentially depriving students of the practicalwisdom gained through these experiences [1]. These concerns reflect a general fear andconfusion surrounding the implications of ChatGPT in education, researchers have highlightedthe need to understand how students may use ChatGPT, as many will use it regardless of itsadoption by the instructor. To address the transformative effects of ChatGPT on the learningenvironment, it is crucial to educate both teachers and students about the capabilities andlimitations of the tool. Academic regulations and evaluation practices used in educationalinstitutions need to be updated to accommodate the use of ChatGPT and other AI tools.Educators should
Learning in Cornerstone through Capstone Programs,” ASME International Design Engineering Technical Conferences and Computer in Engineering Conference, p. 143467, 2024.[16] G. P. Abbas Elamin, N. J. Washuta, James Righter, and K. Skenes, “Assigning Individualized Grades on a Team Capstone Project,” ASEE Southeast Section Conference Proceedings, 2024, doi: 10.18260/1-2--45507.[17] M. Leary and C. Burvill, “Enhancing the quality function deployment conceptual design tool,” Journal of Mechanical Design, vol. 129, no. 7, pp. 701–708, 2007, doi: 10.1115/1.2722787.[18] K. J. Ostergaard and J. D. Summers, “Development of a systematic classification and taxonomy of collaborative design activities,” Journal
Industry Academia ModelAbstractThis paper describes a collaborative industry-academia model for teaching medical devicedesign, which combines active learning with input from industry experts. The course coversinterdisciplinary topics such as biological testing, human factors, usability engineering, riskmanagement, and regulations, areas that go beyond the expertise of a single instructor. Industryprofessionals contribute through guest lectures, mentorship, and real-world case studies, ensuringthat students gain practical, industry-relevant knowledge. Students work on hands-on projectsthat simulate real-world scenarios, helping them develop critical thinking, teamwork, andproblem-solving skills. Active learning activities like sensor-based labs and
ethicalissues, for fostering AI literacy based on the adaptation of classic literacies. We use similarcompetency targets in our study as well, focusing specifically on learning. Furthermore, Dai etal. [2] discusses student confidence in learning AI concepts and recognizing the relevance of AIknowledge in their lives, with results indicating that AI literacy was not predictive of AIreadiness, which in this paper we explore in terms of actual implementation at a practicallearning level of AI usage versus standard methods. Beyond this, Lim [9] underscores thebenefits of fostering a sense of ownership over student educational experiences, with autonomyplaying a crucial role for motivation and engagement.Chiu and Chai [3] discuss the importance of
students'confidence in their ability to solve complex problems, collaborate with their peers, and developan understanding of computer science principles. In an effort to move beyond a solely screen-based experience, the camp incorporated "papercraft" activities, such as a printable binaryincrement Turing machine, logic gate “mazes” and paper versions of half and full adder circuits.These tangible tools provided a bridge between abstract concepts and concrete understanding,reinforcing key computational principles through literal hands-on learning.This paper examines the implementation and outcomes of the coding camp, focusing on theefforts made to enhance the virtual learning experience and their impact on student confidenceand skill development. By analyzing
her doctorate in Mechanical Engineering from North Carolina State University specializing in thermal sciences where her dissertation research spanned three colleges and focused on Engineering Education. Her passions include but are not limited to Engineering Education, Energy Engineering and Conservation, and K-20 STEM Outreach. Prior to matriculating at NCSU, she worked at the North Carolina Solar Center developing a passion for wind and solar energy research while learning renewable energy policy. She combined these passions with K-20 STEM Outreach while a National Science Foundation Fellow with the GK-12 Outreach Program at NCSU where she began Energy Clubs, an out-of-school-time program for third, fourth and
more accessible, with complex software becomingless of a barrier through tools such as Canva, Figma, Adobe Color, and Adobe Express. Thesetools provide well-designed templates, graphics, and AI features geared toward non-designers.Even if educators themselves grasp the importance of applying thoughtful graphic design tomultimedia instruction to prevent cognitive overload in students, how do they impress uponstudents to follow suit, especially if educators have no formal training or expertise in thefundamental principles of visual design? Importantly, how do educators then assess visual designelements if the topic is far outside their area of expertise?This work-in-progress paper describes electrical and computer engineering
, 2024. Retrieved from https://orchard-prod.azurewebsites.net/media/Framework/KEEN_ Framework_v5.pdf. 2. National Academy of Engineering. “Engineering of the future: Annual report,” 2019. Retrieved from https://www.nae.edu/File.aspx?id=237788. 3. The Lemelson Foundation. “The Engineering for One Planet Framework: Essential Sustainability-focused Learning Outcomes for Engineering Education,” 2022. Retrieved from https://engineeringforoneplanet.org/wp- content/uploads/2022_EOP_Framework_110922.pdf 4. D. Grasso, and M. Burkins. Holistic Engineering Education: Beyond Technology. Springer, 2010. 5. P. E. Arce, J. R. Sanders, A. Arce-Trigatti, L. Loggins, J. Biernacki, M. Geist, J. Pascal, and K. Wiant
: Curiosity, Connections, and Creating Value.We emphasize how these three components play a vital role in enhancing communication andcollaboration across disciplines, particularly within Foundry-guided activities. The secondcomponent describes preliminary work of student teams from a required second-year course in aNational Science Foundation National Research Traineeship (NSF-NRT) graduate levelprogram, which included 11 trainees. As part of this work, we showcase the outcomes of theirprojects, drawing connections to the three C's of the KEEN Mindset, with a specific focus onhow "Creating Value" is achieved through effective communication strategies.KeywordsRenaissance Foundry Model, KEEN Entrepreneurial Mindset, Holistic Professional, Foundry
as competent professionals, innovativethinkers, and problem solvers who can contribute more to the world while also succeeding intheir future endeavors. To aid this we have created a simple hands-on experiment that can beimplemented in the classroom: https://github.com/Hsuya01/Hands_On_CV_Exp.References1. Jesiek, B. K. (2013). The Origins and Early History of Computer Engineering in the United States. IEEE Annals of the History of Computing, 35(3), 6-18. https://doi.org/10.1109/MAHC.2013.22. Montoya, A. (2017). Computer Science for All: Opportunities Through a Diverse Teaching Workforce. Harvard Journal of Hispanic Policy, 29, 47-62. https://www.proquest.com/docview/1924502808?pq-origsite=gscholar&fromopenview=true&
Development of Engineering Skills Using Online ToolsAbstractEngineering education extends beyond mere knowledge acquisition and encompasses thedevelopment of a comprehensive skill set valued in the industry. A novel approach to fosteringengineering skills using online tools is presented in this paper, addressing the limitations oftraditional teaching methods. The alignment between ABET student outcomes and industry-desired skills was analyzed, and the need for improved skill development methodologies inengineering curricula was identified. Five key elements of skill development are focused on:personal investment, practice, feedback, realistic expectations, and supportive environments. Aninnovative educational tool utilizing online platforms was
Education Department andthe Louis Stokes Alliance for Minority Participation (LSAMP) funded by the National ScienceFoundation. The goal of AC2 is to increase the number of underrepresented students pursuingcareers in science, technology, engineering, and mathematics (STEM). Through a variety of bestpractices, the program provides students with the necessary support to gain STEM experienceand complete degrees in STEM. The program serves approximately 125 students from freshmanyear through graduation and beyond. On average, students graduate within 4.5 years with aSTEM degree and roughly 60-65% of students graduate with at least one internship or researchexperience.Since 1998, the AC2 Program at SUNY New Paltz has hosted a five-week Summer
-awareness, social skills, self-regulation, empathy, andmotivation is seen as art and lived out through practice [3], [5], [13]. The ability for aspiringproject engineers to hone EI, project management competencies, and understanding teamdevelopment can better equip them for the workplace and meet technical and interpersonal skillexpectations of employers.References[1] De Campos, D. B., de Resende, L. M., & Fagundes, A. “The importance of soft skills for the engineering,” Creative Education, 11, pp.1504-1520. 2020. https://doi.org.10.4236/ce.2020.118109[2] Kastberg, E., Buchko, A., & Buchko, K. “Developing emotional intelligence: The role of higher education,” Journal of Organizational Psychology 20(3), 2020. pp.64-72. https
civilinfrastructure workforce (either through a university or from any other educational background);and 2) the perception and base knowledge of civil infrastructure within the public at large. Thispaper summarizes these videos while accomplishing the following objectives: 1) assessing theireffectiveness relative to the two potential impact categories; and 2) describing ongoing videoplans that make use of the assessment’s findings.An abbreviated review of literature, with associated author commentary, related to the use ofvideos in education is provided in the next section. Thereafter, the videos themselves aredescribed before presenting the assessments. These assessments were in the form of fourquestionnaires/surveys given over a few year period beginning
setting for teaching the undergraduate course,moving away from the traditional approach that primarily emphasizes the fundamental theory ofthe finite element method [8]. Baker from the University of Kentucky took a similar approach in hisfinite element course, offering a balanced curriculum that covered both static and dynamicstructural system analysis, including nonlinear systems. Students used commercial software likeANSYS and MATLAB and were required to write programs for analyzing small systems. Through thiscourse, students gained familiarity with numerical methods and appreciated how they could beapplied to more complex real-world systems [9].Project-based pedagogy seems to be the predominant teaching method for finite element analysisused
too early to discernif there will be a complete paradigm shift, but there is certainly a need for greater exploration.References[1] N. Chomsky, I. Roberts, and J. Watumull. “The False Promise of ChatGPT.” The New York Times. March 8,2023. [Online][2] E. Mollick. Co-Intelligence: Living and Working with AI. Portfolio/Penguin, 2024.[3] K. A. Neeley and H. C. Leugenbiehl. “Beyond Inevitability: Emphasizing the Role of Intention and Ethical Responsibility in Engineering Design,” Philosophy and Design. Springer 2008.[4] K. Shelton and D. Lanier. The Promises and Perils of AI in Education: Ethics and Equity Have Entered the Chat. Lanier Learning, 2024.[5] B. McMurtrie. “Cheating Has Become Normal: Faculty members are
for thediscussions. Required standard academic qualifications to teach engineering courses will bebriefly stated through a review of current practices at colleges and universities in the US and insome other parts of the world in conjunction with personal observations and interviews madesporadically over the years by the author. As will be shown later, despite proven and numerousreal advantages of such a practice, legitimate concerns and possible fundamental flaws exist aswell.Connection between Mathematics and Science; and Engineering:Engineering is highly intertwined with science and mathematics. The connection betweenengineering with science and mathematics manifests itself in so many ways and at variousdomains [1]. It starts with K-12
achieved significant improvements in project quality,depth, and originality. However, the paper also highlights ethical concerns, particularly regardingplagiarism, algorithmic bias, and data privacy. Through a comprehensive analysis, the study un-derscores the transformative potential of Generative AI while advocating for ethical guidelines toensure responsible usage in engineering education. Future work will focus on developing robustplagiarism detection tools and refining the ethical frameworks for AI integration in educationalsettings.Keywords: Generative AI, Engineering Education, Project-based Learning, Ethical Considera-tions1. Introduction1.1 Transformative potential of Generative AI in various sectorsGenerative Artificial Intelligence (AI
the literature that students have only a 17% chance of taking a course related toclimate change. Through the introduction of course modules 100% of the students that passthrough the Civil Engineering program are exposed to climate change and its impacts and theresults support that this structure is effective and has achieved the desired results of betterpreparing students to be able to address the future challenges that climate change will present.Future WorkThe results presented in this research effort represent a mid-course assessment and thus theresults may improve beyond those at present. As part of the course design, practical applicationprojects are included that will expose students to real-life problems that incorporate
supportive environment.Our methodology involves four key elements: 1. Structured Lab Sessions: Students participate in 50-minute lab sessions that complement lecture topics. 2. Project-Based Learning: Projects such as LinkedSet are designed to reinforce concepts like interfaces, generics, and OOP. 3. Interactive Guidance: Instructors demonstrate key coding techniques and guide students through implementation challenges. 4. Learning Cycles: To maintain student engagement and balance stress levels in teacher- guided project-based labs, we implemented a learning cycle mechanism. This cycle consists of teacher-guided learning, self-paced code review, flipped classroom practices [3], and quiz- based
. (2012). Engagement in classroom learning: Creating temporal participation incentives for extrinsically motivated students through bonus credits. Journal of Education for Business, 87(2), 86-93. https://doi.org/10.1080/08832323.2011.570808[15] Guerrero, M., & Rod, A. B. (2013). Engaging in office hours: A study of student-faculty interaction and academic performance. Journal of Political Science Education, 9(4), 403-416. https://doi.org/10.1080/15512169.2013.835554[16] Trowler, V. (2010). Student engagement literature review. The higher education academy, 11(1), 1-15.[17] Schinske, J., & Tanner, K. (2014). Teaching more by grading less (or differently). CBE—Life Sciences Education, 13(2), 159-166. https://doi.org