efficiencies, as wellas expanding the types of jobs and sectors available in the workforce. However, as with anytechnological revolution, there will also be challenges, particularly regarding the ethical use ofAI, job displacement, and ensuring that the benefits of AI are accessible to all. By understandingand preparing for these shifts, society can maximize the potential of AI for positivetransformation in the coming decades. II. AI: PAST, PRESENT & FUTURE Artificial Intelligence (AI) has various definitions. To many, AI refers to machines that think,understand language, and solve problems, and gaining popularity with ChatGPT. Scientifically,AI is a computer system capable of tasks associated with intelligence. John McCarthy and Marvin
outputs from recently developed AI tools is a quite newchallenge that research communities are just now forming to address [23]. An investigation ofAI accuracy found that ChatGPT 3.5 proved, “…generally good at writing concepttopics…”[24]. One reasonably classifies a literature survey task as a concept topic, suggestingthe potential for accurate results from AI. However, this work uses Gemini 1.5 Flash, notChatGPT 3.5. Verhulsdonck and coauthors introduce a subjective means of evaluating theaccuracy of AI generated content independent of the particular tool [24]. Their HEAT method,an acronym formed from Human experience, Expertise, Accuracy and Trust, attempts tosubjectively gage AI output credibility. In this work’s contents, the H and E terms
; Computer ScienceEngineering conducts a workshop on using ChatGPT to optimize household tasks and searchfor job opportunities; Automation and Robotics Engineering provides a workshop on homeautomation, teaching the implementation of smart technologies; finally Social Work leads awomen’s empowerment workshop, addressing strategies to enhance self-confidence anddecision-making skills.The project’s evolution has been guided by a continuous improvement approach based onsatisfaction surveys administered to program participants and the government counterpart.This feedback has allowed for adjustments and enhancements to each workshop's content,ensuring that the training effectively addresses the real needs of the women beneficiaries.This growth has
promising an opportunity to participate in the raffle for a gift card. As oursurvey and recruited participants were limited to our institution and targeted populations, itshould be noted that our findings may not be applicable or generalizable to other institutions. An area for future consideration would be to include more survey questions related tostudents’ understanding and use of artificial intelligence (AI). While the survey did have onequestion related to their use of ChatGPT specifically, any future studies of students’ informationliteracy skills should include the use of AI in information retrieval and citation. This wouldhighlight a gap in understanding how students engage with AI and the ethical and practicalchallenges they might
® Fundamentals tutorial book. When the site designcourse was first developed in 2019, the Civil 3D® tutorial book was 658 pages and 12 chaptersin length [2]. The 2024 tutorial has now grown to 986 pages, 18 chapters in length [3]. As firstyear students navigate the challenges of college life, implementing an effective lesson methodcan assist in facing challenges in time management [4], anxiety, and their overall wellbeing [5].However, not having a structured lesson approach can lead to students feeling overwhelmed andhelpless. As a result, students may turn to external resources such as ChatGPT, Chegg and onlinesearch engines. These programs can be effective as a supplemental tool for learning but shouldnot be the primary source of information for a
time.Holly mentions “doing research” a few times throughout her interview but is vague aboutwhat this entails. When pushed for details, she describes relying primarily on Google andGoogle Scholar. She sees Google as most helpful for finding what she terms as “hard facts,”such as how an air-based cooling system works. She uses Google Scholar to find morescholarly sources to supplement her work, but finds that the language is often “veryscientific” and difficult to understand. She also mentions using ChatGPT to help explainthings in simpler terms if her tutor is not available to answer questions. She seems generallyhappy to ask questions of her lecturers and her classmates, but is reluctant to admit shedoesn’t know something in front of people she
. Inparticular, natural language processing (NLP) a subset of gen-AI, enables computers to quicklyparse and understand text by identifying the meaningful parts of sentences [34]. Since the releaseof ChatGPT and similar chatbots, engineering education researchers have explored diverse usecases of NLP, including for analyzing student writing and assignments, examining curriculums,research data processing, student support, and assessment [35], [36], [37]. Recent work by ourresearch group [38] has also demonstrated the potential for NLP to aid qualitative thematicanalysis by expediting the codebook generation process. Importantly, these efforts takeadvantage of how NLP handles semantically and syntactically different text by identifyingpatterns between word
towardsthe Society 5.0 global vision. Coupled with the use of conscious, ethical Artificial Intelligence tools (ChatGPT, JasperAI, Copilot, Gemini, etc.) and learning modalities (active/experiential/inquiry-driven, flipped-classroom, etc.) willempower students to individualize learning experiences/outcomes. However, e-learning must be supplemented byopen discussions [13], and project-based/textbook-based learning, especially for foundational subjects. Withinchemical engineering, core subjects and topics like calculus, transport phenomena, chemical thermodynamics,separation processes, and plant/process design (undergraduate capstone) must be taught through a mix of pedagogicalstrategies. Our results reveal an increase (especially since 2017
or health applications, on-device inference means datadoes not need to be transmitted to a server for processing, thus preserving user privacy. This alsosaves bandwidth and battery life [28], as transmitting and receiving are among the most energy-intensive tasks for IoT devices. Local ML models alleviate this burden, mitigate the risk of man-in-the-middle attacks, and enable customization, allowing the model to adapt to individual user needs.While highlighting the benefits of ML, we also addressed its challenges and limitations, suchas adversarial attacks, fairness concerns, and the need for explainable AI (XAI). Many students,having interacted with AI technologies like ChatGPT, were already familiar with AI’s potential forerror. However
and ChatGPT) models were used to help simplify the survey questionsto avoid complicated discipline specific jargon [32]. The LLM models were prompted torephrase the given question for target reader of an 8th grader. This level was selected based onrecommendations that 85% of a general audience understand information at an eighth gradereading level [32].The revised version was later edited by the research team to ensure alignment and consistencywith the involved disciplines (engineering, psychology) and the question intent. The studyprotocol is followed to administer the surveys to the target student population and to collect thatdata. Depending on the sample size, the proper analysis tools are used to gain insights.A. Study ProtocolThe IRB
with participants in my research and to acknowledge thebiases I bring. From my early struggles with homesickness in first year, to my passion foroutreach and advocacy developed through NSBE, to finally securing my first internship in theOil Sands during my master’s degree which I felt ultimately validated my identity as an engineer,my career pathway has been shaped and informed by the experiences in my undergraduatedegree. These reflections ground me in focus of my PhD research: to illuminate the factorsshaping diverse career paths in engineering and to foster environments where all students canthrive.1 The author identified she used ChatGPT as part of her writing process for this section to synthesize similar writingsshe had previously done
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
false information (“hallucination”) is usedto explore the principle of trustworthiness. First, a political campaign advertisement featuring avideo deepfake of former Pakistani prime minister Imran Khan—produced while Khan was injail—provides a counterexample to the notion that synthetic AI content is necessarily bad [23].Then, students are encouraged to try to ‘hack’ OpenAI’s large language model ChatGPT so that ithallucinates, malfunctions, or gives an inappropriate response.The first lecture concludes by asking students to subjectively rank the three highlightedprinciples—plus three others (transparency, justice and autonomy) which together summarizeFloridi and Cowl’s “Unified Framework for AI in Society” [24]—in terms of their
were reviewed using ChatGPT 4o as asupplementary tool. When minor discrepancies were identified, the first author revised theChinese translation and discussed the changes with the colleagues until all disagreementswere resolved.In addition to the original EBAPS items, four additional questions, shown in Table 4, wereincluded to explore students’ cognitive patterns under the influence of naïve dialecticism[17].The first two items regarding attitudes toward contradictions were adapted from theDialectical Self Scale[19], an instrument designed to measure dialectical thinking. The othertwo items were created by one of the authors to represent the remaining key components ofnaïve dialecticism: the “Principle of Relationship or Holism” (item iii
instance, a study by Escalante et al. (2023) [6] examined the learning outcomes ofuniversity students receiving feedback from ChatGPT (GPT-4) versus human tutors. Thecommon feature of these students was English is a New Language (ELN). The resultsindicated no significant difference in learning outcomes between the two groups, suggestingthat AI-generated feedback can be effectively incorporated into writing instruction. Otherstudies provide similar results within STEM learning environments. A recent systematicliterature review [7] identified 6 common categories of AI methods used in education from2011-2021. This work highlights the complexity and opportunities of the rapidly evolvingtechnology and how it can be integrated into learning environments