in preparing undergraduate students to conduct research, in-conversion for deployment to fulfill the first-year experience person as well as online when necessary, starting in the Excelcriterion was challenging given the setting of open admissions, environment with a gradual transformation to the standardthe newly graduated high school students with strong intentions Python framework. The Excel with Python by Microsoftin the programming career were found to be successful in thelearning of Python fundamentals. The recent Microsoft Office without third vendor subscription fee is only available to365
, https://www.openai.com.students’ fundamental abilities to write structured code is [13] Xingzhi Wang, Nabil Anwer, Yun Dai, Ang Liu, (2023) ChatGPT for design, manufacturing, and education.critically important. Moreover, this approach is not only http://dx.doi.org/10.13140/RG.2.2.35077.22244.restricted to Python but can be used to shuffle codes written in [14] Khan, R.A., Jawaid, M.,Khan,A.R., and Sajjad, M. (2023).ChatGPT -any programming languages, as exemplified by its application Reshaping medical education and clinical management. Pakistan Journalin evaluating foundational assembly
frequencies. This suggests that while AI is used for assisting with research, writing, and Fig.4. Frequency of Using AI (1 being Never, 5 being Always) communication, it is less commonly utilized in direct academic assessments. ChatGPT, developed by OpenAI, represents asignificant advancement in Conversational andGenerative AI. This model, a variant of the GPT-3.5series, is designed to interact in a dialogue format,enabling it to answer follow-up questions, admitmistakes, and handle a range of interactive tasks. Key toits development was the use of Reinforcement Learningfrom Human Feedback (RLHF), where
ethical design or implementation. It is crucialmanufacturing, big data management, machine to define what ethical AI means in the context ofoptimization, and material design all benefit from AI. As education [7]. AI is at the heart of debates on workplacea result, engineering educators must introduce students automation, algorithmic bias, data surveillance, privacyto the potential of AI, teach its fundamentals, and guide concerns, and corporate influence over society. Variousthem in applying AI algorithms to real engineering ethical frameworks and professional codes aim toprojects. This is crucial in modern engineering address AI-related risks, but concerns remain over
can assist with writing quality, reference formatting, andany notes when presenting, (2) concepts must be drawn from countless other configuration tasks, fundamental concerns havelinkable scholarly research, and (3) students were responsible forthe accuracy and quality of the seminar content and delivery been raised relating to originality, independent novel thought,based on HMS course principles. conceptual ownership, and user over-dependence [2, 3, 4, 5]. II. HUMAN
-align with the expectations of modern employers but also powered chatbot named ”Lola” has been implemented to assistdirectly influence engineers’ ability to collaborate, innovate, students with inquiries related to campus resources and aca-and contribute effectively to their organizations. demic services. By providing instant responses and structured guidance, allowing students to interact more effectively withA. Communication Competency institutional support systems[13]. Communication is a fundamental skill for engineers, as they These case studies highlight the growing role of AI in en-must
aeducational utility. Fourier transform through equations, writing explanations, and representing visual graphs [6]. This is more engaging and In engineering education, this evolution means that AI is personalized, which ultimately improves learning outcomes.moving from a background analytic tool to a foregroundcreative partner in the learning process. For instance, whereprevious systems might have evaluated a student’s answer on a B. Personalized Assessment and Feedbackproblem set, Gen AI can now generate personalized hints, Traditional assessments often fail to capture thedetailed solutions, or
GPTZero and TurnItIn claim to identify whether a student’s writing was One key aspect of this paper is the distinction betweenproprietary and open-source large language models. Proprietary produced by generative AI, but they are highly inaccurate.models, such as OpenAI’s ChatGPT, are often considered less They tend to flag simple or predictable writing as AI-secure and privacy-invasive compared to open-source generated. Studies show that such false positives occur morealternatives like Meta’s Llama. Educating students on the frequently among certain groups, including
• Assessment: Periodic Quizzes to check for • What are one or two suggestions to improve learning inunderstanding – open book open note quizzes that are assigned the class?to students individually to check for understanding Since these reflections also prepare student for the next • Assignment: Write a report - summarize an article class session, late reflection submissions will not be accepted.in project management and submit one page synthesis and Analysis: This activity focuses on communication andcritique of the article. critical thinking. It is obvious if the student is using generic • Assignment: Value Stream
channel was used? How were problems solved? were part ofdon’t share is their metric for success. Higher education their assessment when writing down the notes.defines success through mastering theories and passing exams.Industry values technical and practical knowledge, the ability The results of this case study offer insights for universities looking to implement interdisciplinary initiatives, fosteringto adapt and solve problems. This disparity in measuring collaboration and better preparing graduates for cross-success makes it harder to prepare graduates for
2025 ASEE Northeast Section Conference, March 22, 2025, University of Bridgeport, Bridgeport, CT, USA. Building and Growing a High School Computer Programming and AI Club Thomas C. McKinley Junior Student Boston College High School Boston, MA zcp8802@gmail.comAbstract — In today’s world, technology is everywhere, and it’s and Artificial Intelligence Club at Boston College High Schoolimportant for high school students to
@farmingdale.edu tatoglu@hartford.edu Abstract Self-directed learning (SDL) is essential for by various engineering education, resulting in less definitivestudents, graduate students, and mid-career professionals seeking descriptions of the relevant concepts [13] and shifting the focuscontinuous improvement. AI-powered tutors can enhance SDL by on who the self-directed learner is. A self-directed learner canguiding learners through the stages of learning readiness be anyone: an undergraduate student, a recent graduateassessment, goal setting, engagement, and evaluation. This paper preparing for the Fundamentals of Engineering (FE) or the
, lectures and problem sets. However, when students were particularly during disruptions like the COVID-19 taken outside and engaged in a tug-of-war experiment— pandemic. This review underscores PBL’s potential to one person pulling against a team of twenty using a bridge the gap between theory and practice, equipping pulley system—the practical demonstration made the students with skills crucial for navigating an innovation principles of mechanical advantage and force driven economy. Future research should focus on distribution clear. This ability to bridge theory with scalable integration models and refining assessment physical experience is fundamental in engineering strategies to
information such as body temperature, heart rate and sleepdesign concepts. stages, and even in the concept development stage designers are to be cautious the kind of data it is collected [15]. In concept development, text-to-image generative AI toolshave revolutionized the process by providing rapid, lifelike There are other concerns on the process of sequencingvisualizations based on expert prompts. These tools inspire writing prompts in AI, where the responses will vary largelyinnovative ideas and accelerate the development phase, depending on the contextualization and methodology
separately, is significant for examining changea very organized functional administration procedure. endeavors in the Saudi instructive setting [22]. According to The capacity of the experts taking part in the change cycle Rogers (2003), an innovation's internal factors are itshas likewise been noted as imperative. Teachers and characteristics that can either encourage change or elicitadministrators in charge of making the changes have found it opposition. Outer variables envelop the circumstances whereinchallenging to adjust to new methods and procedures. Moreover, an advancement is presented, reflected as the information andpartner investment is missing fundamentally. The education
outcomes, others express deep concerns about stu-education, understanding instructor perspectives is critical for dent over-reliance on AI-generated content, the difficulty ofits responsible integration. This study investigates instructor detecting AI-assisted academic dishonesty, and the ethicalperceptions of AI tools in education, focusing on their perceivedbenefits, challenges, and strategies for fostering trust in their use. implications of using AI-powered assessment tools [4][7]. ThisAn online survey was distributed to all instructors across various paper summarizes the findings of a recent survey conducteddisciplines at the University of Connecticut. The survey is used to at the University of Connecticut, which