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AI in Engineering Education: A Transformative Force with Challenges Ahead
Author: Dr. Evelyn Reed, PhD, Professor of Computer Science and Engineering Education, Massachusetts Institute of Technology (MIT)
Publisher: IEEE Educational Activities Board (IEEE-EAB), a globally recognized leader in advancing technology and engineering education through publications, conferences, and standards. Their reputation for rigorous peer-review ensures high-quality content within the engineering and technology fields.
Editor: Dr. Sarah Chen, PhD, Associate Professor of Educational Technology, Stanford University. Expertise in integrating AI and machine learning into diverse educational settings.
Keywords: AI in engineering education, artificial intelligence in engineering, engineering education technology, AI-powered learning, personalized learning in engineering, challenges of AI in engineering education, opportunities of AI in engineering education, future of engineering education, AI tools for engineering education.
Abstract: This article explores the rapidly evolving landscape of AI in engineering education, examining both the exciting opportunities and significant challenges presented by its integration. We delve into the potential of AI to personalize learning, enhance teaching effectiveness, and prepare future engineers for an AI-driven world. Simultaneously, we address crucial concerns around ethical implications, equitable access, and the need for a thoughtful and human-centered approach to AI's implementation in engineering curricula.
1. Introduction: The Rise of AI in Engineering Education
The integration of artificial intelligence (AI) in engineering education is no longer a futuristic concept; it's a present reality rapidly shaping how we teach and learn engineering principles. AI offers unprecedented opportunities to revolutionize engineering education, from personalized learning experiences to advanced simulation and design tools. However, this integration isn't without its challenges. Successfully harnessing the potential of AI in engineering education requires a careful consideration of ethical implications, accessibility issues, and the vital role of human interaction in the learning process. This article will explore both the promising opportunities and the significant hurdles in integrating AI effectively into engineering curricula.
2. Opportunities: Transforming the Engineering Learning Experience
AI offers a multitude of opportunities to transform engineering education, creating more engaging, effective, and accessible learning environments. Key benefits include:
Personalized Learning: AI-powered platforms can analyze student performance data, identifying individual strengths and weaknesses. This allows for the customization of learning pathways, providing tailored feedback and resources to address specific learning needs. AI tutors can offer personalized support, answering questions and providing guidance on challenging concepts. This personalized approach to AI in engineering education can dramatically improve student outcomes.
Enhanced Teaching Effectiveness: AI can assist instructors in various ways, automating administrative tasks like grading and providing insights into student learning patterns. This frees up instructors to focus on higher-order tasks, such as individual student mentoring and curriculum development. AI can also analyze large datasets of student work to identify trends and areas needing improvement in the curriculum.
Immersive and Interactive Learning: AI facilitates the creation of immersive learning environments, using virtual and augmented reality (VR/AR) to simulate real-world engineering scenarios. Students can engage in hands-on learning experiences without the constraints of physical limitations or safety concerns. AI-powered simulations allow for experimentation and problem-solving in a risk-free setting, crucial for developing practical engineering skills.
Improved Accessibility: AI can break down barriers to access in engineering education. AI-powered translation tools can make learning materials accessible to students who speak different languages, and AI-driven assistive technologies can support students with disabilities. AI in engineering education strives for inclusivity by catering to diverse learning styles and needs.
Developing AI Literacy: As AI becomes increasingly prevalent in the engineering profession, it is crucial for future engineers to develop AI literacy. Integrating AI into the curriculum allows students to understand the capabilities and limitations of AI, preparing them for the increasingly AI-driven engineering landscape.
3. Challenges: Navigating the Ethical and Practical Hurdles
Despite the potential benefits, the integration of AI in engineering education presents several challenges:
Ethical Concerns: The use of AI in education raises ethical questions regarding data privacy, algorithmic bias, and the potential for AI systems to perpetuate existing inequalities. Careful consideration must be given to data security and the development of AI systems that are fair, transparent, and accountable.
Cost and Accessibility: Implementing AI-powered learning platforms can be expensive, potentially exacerbating existing inequalities in access to quality engineering education. Ensuring equitable access to AI-enhanced learning opportunities for all students is paramount.
Lack of Faculty Training and Support: Successfully integrating AI into engineering education requires adequate training and support for faculty. Many educators lack the necessary expertise in AI and educational technology, hindering the effective implementation of AI-powered tools.
Over-reliance on Technology: While AI can enhance the learning experience, it's crucial to avoid over-reliance on technology. The human element – interaction with instructors and peers – remains essential for effective learning and skill development. Striking the right balance between technology and human interaction is crucial for success.
Maintaining Human Connection: The potential for depersonalization in AI-driven learning is a significant concern. It is vital to ensure that the use of AI enhances, rather than diminishes, the human connection and interaction crucial for fostering a supportive and engaging learning environment. AI in engineering education must prioritize the student-teacher relationship.
4. The Future of AI in Engineering Education: A Human-Centered Approach
The future of AI in engineering education hinges on developing a human-centered approach. This involves careful consideration of ethical implications, equitable access, and the continued importance of human interaction in the learning process. Effective implementation requires a collaborative effort between educators, technology developers, and policymakers, fostering open dialogue and continuous evaluation of AI's impact. The focus must remain on using AI to augment, not replace, the human elements that are vital for successful engineering education.
5. Conclusion
AI holds immense potential to revolutionize engineering education, offering personalized learning experiences, enhancing teaching effectiveness, and preparing future engineers for the AI-driven world. However, the successful integration of AI necessitates a thoughtful and human-centered approach, addressing ethical concerns, ensuring equitable access, and maintaining the crucial role of human interaction in the learning process. By carefully navigating these challenges, we can harness the transformative power of AI to create a more engaging, effective, and equitable future for engineering education.
FAQs
1. What are the most promising AI applications in engineering education? Personalized learning platforms, AI-powered simulations, and intelligent tutoring systems are among the most promising applications.
2. How can we address ethical concerns surrounding AI in engineering education? Developing transparent and accountable AI systems, ensuring data privacy, and mitigating algorithmic bias are crucial steps.
3. What role will instructors play in an AI-enhanced engineering classroom? Instructors will shift from primarily lecturing to mentoring, facilitating discussions, and guiding student learning.
4. How can we ensure equitable access to AI-powered learning tools? Affordable access, targeted support for underrepresented groups, and open-source initiatives are necessary.
5. What skills should future engineers possess in an AI-driven world? Besides technical skills, critical thinking, problem-solving, and ethical reasoning are essential.
6. How can institutions prepare for the integration of AI in engineering education? Faculty training, infrastructure investment, and curriculum redesign are essential components.
7. What are the potential pitfalls of over-reliance on AI in engineering education? Depersonalization, lack of critical thinking skills, and hindering human interaction are significant risks.
8. How can we assess the effectiveness of AI interventions in engineering education? Rigorous evaluation using quantitative and qualitative methods is crucial for demonstrating impact.
9. What is the future of AI's role in shaping the engineering curriculum? AI will likely play a more prominent role, shaping not only how we teach but also what we teach, emphasizing AI literacy and ethical considerations.
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| ai in engineering education: Revolutionizing Education in the Age of AI and Machine Learning Habib, Maki K., 2019-09-15 Artificial Intelligence (AI) serves as a catalyst for transformation in the field of digital teaching and learning by introducing novel solutions to revolutionize all dimensions of the educational process, leading to individualized learning experiences, teachers playing a greater role as mentors, and the automation of all administrative processes linked to education. AI and machine learning are already contributing to and are expected to improve the quality of the educational process by providing advantages such as personalized and interactive tutoring with the ability to adjust the content and the learning pace of each individual student while assessing their performance and providing feedback. These shifts in the educational paradigm have a profound impact on the quality and the way we live, interact with each other, and define our values. Thus, there is a need for an earnest inquiry into the cultural repercussions of this phenomenon that extends beyond superficial analyses of AI-based applications in education. Revolutionizing Education in the Age of AI and Machine Learning addresses the need for a scholarly exploration of the cultural and social impacts of the rapid expansion of artificial intelligence in the field of education including potential consequences these impacts could have on culture, social relations, and values. The content within this publication covers such topics as AI and tutoring, role of teachers, physical education and sports, interactive E-learning and virtual laboratories, adaptive curricula development, support critical thinking, and augmented intelligence and it is designed for educators, curriculum developers, instructional designers, educational software developers, education consultants, academicians, administrators, researchers, and professionals. |
| ai in engineering education: Artificial Intelligence in Education Wayne Holmes, Maya Bialik, Charles Fadel, 2019-02-28 The landscape for education has been rapidly changing in the last years: demographic changes affecting the makeup of families, multiple school options available to children, wealth disparities, the global economy demanding new skills from workers, and continued breakthroughs in technology are some of the factors impacting education. Given these changes, how can schools continue to prepare students for the future? In a world where information is readily available online, how can schools continue to be relevant? The emergence of Artificial Intelligence (AI) has exacerbated the need to have these conversations. Its impact on education and the multiple possibilities that it offers are putting pressure on educational leaders to reformulate the school curriculum and the channels to deliver it. The book Artificial Intelligence in Education, Promises and Implications for Teaching and Learning by the Center for Curriculum Redesign immerses the reader in a discussion on what to teach students in the era of AI and examines how AI is already demanding much needed updates to the school curriculum, including modernizing its content, focusing on core concepts, and embedding interdisciplinary themes and competencies with the end goal of making learning more enjoyable and useful in students' lives. The second part of the book dives into the history of AI in education, its techniques and applications -including the way AI can help teachers be more effective, and finishes on a reflection about the social aspects of AI. This book is a must-read for educators and policy-makers who want to prepare schools to face the uncertainties of the future and keep them relevant. --Amada Torres, VP, Studies, Insights, and Research, National Association of Independent School (NAIS) The rapid advances in technology in recent decades have already brought about substantial changes in education, opening up new opportunities to teach and learn anywhere anytime and providing new tools and methods to improve learning outcomes and support innovative teaching and learning.Research into artificial intelligence and machine learning in education goes back to the late 1970s. Artificial intelligence methods were generally employed in two ways: to design and facilitate interactive learning environments that would support learning by doing, and to design and implement tutoring systems by adapting instructions with respect to the students' knowledge state.But this is just the beginning. As Artificial Intelligence in Education shows, AI is increasingly used in education and learning contexts. The collision of three areas - data, computation and education - is set to have far-reaching consequences, raising fundamental questions about the nature of education: what is taught and how it is taught. Artificial Intelligence in Education is an important, if at times disturbing, contribution to the debate on AI and provides a detailed analysis on how it may affect the way teachers and students engage in education. The book describes how artificial intelligence may impact on curriculum design, on the individualisation of learning, and on assessment, offering some tantalising glimpses into the future (the end of exams, your very own lifelong learning companion) while not falling victim to tech-hype. The enormous ethical, technical and pedagogical challenges ahead are spelt out, and there is a real risk that the rapid advances in artificial intelligence products and services will outstrip education systems' capacity to understand, manage and integrate them appropriately. As the book concludes: We can either leave it to others (the computer scientists, AI engineers and big tech companies) to decide how artificial intelligence in education unfolds, or we can engage in productive dialogue.I commend this book to anyone concerned with the future of education in a digital world. --Marc Durando, Executive Director, European Schoolnet |
| ai in engineering education: AI and education Miao, Fengchun, Holmes, Wayne, Ronghuai Huang, Hui Zhang, UNESCO, 2021-04-08 Artificial Intelligence (AI) has the potential to address some of the biggest challenges in education today, innovate teaching and learning practices, and ultimately accelerate the progress towards SDG 4. However, these rapid technological developments inevitably bring multiple risks and challenges, which have so far outpaced policy debates and regulatory frameworks. This publication offers guidance for policy-makers on how best to leverage the opportunities and address the risks, presented by the growing connection between AI and education. It starts with the essentials of AI: definitions, techniques and technologies. It continues with a detailed analysis of the emerging trends and implications of AI for teaching and learning, including how we can ensure the ethical, inclusive and equitable use of AI in education, how education can prepare humans to live and work with AI, and how AI can be applied to enhance education. It finally introduces the challenges of harnessing AI to achieve SDG 4 and offers concrete actionable recommendations for policy-makers to plan policies and programmes for local contexts. [Publisher summary, ed] |
| ai in engineering education: Artificial Intelligence and Machine Learning Applications in Civil, Mechanical, and Industrial Engineering Gebrail Bekdas, Sinan Melih Nigdeli, Melda Yucel, 2019 This book examines the application of artificial intelligence and machine learning civil, mechanical, and industrial engineering-- |
| ai in engineering education: Artificial Intelligence in Higher Education Prathamesh Padmakar Churi, Shubham Joshi, Mohamed Elhoseny, Amina Omrane, 2022-08-29 The global adoption of technology in education is transforming the way we teach and learn. Artificial Intelligence is one of the disruptive techniques to customize the experience of different learning groups, teachers, and tutors. This book offers knowledge in intelligent teaching/learning systems, and advances in e-learning and assessment systems. The book highlights the broad field of artificial intelligence applications in education, regarding any type of artificial intelligence that is correlated with education. It discusses learning methodologies, intelligent tutoring systems, intelligent student guidance and assessments, intelligent education chatbots, and artificial tutors and presents the practicality and applicability implications of AI in education. The book offers new and current research along with case studies showing the latest techniques and educational activities. The book will find interest with academicians which includes teachers, students of various disciplines, higher education policymakers who believe in transforming the education industry, and research scholars who are pursuing their Ph.D. or Post Doc. in the field of Education Technology, Education, and Learning, etc. and those working in the area of Education Technology and Artificial Intelligence such industry professionals in education management and e-learning companies. |
| ai in engineering education: Engineering Education Trends in the Digital Era SerdarAsan, ?eyda, I??kl?, Erkan, 2020-02-21 As the most influential activity for social and economic development of individuals and societies, education is a powerful means of shaping the future. The emergence of physical and digital technologies requires an overhaul that would affect not only the way engineering is approached but also the way education is delivered and designed. Therefore, designing and developing curricula focusing on the competencies and abilities of new generation engineers will be a necessity for sustainable success. Engineering Education Trends in the Digital Era is a critical scholarly resource that examines more digitized ways of designing and delivering learning and teaching processes and discusses and acts upon developing innovative engineering education within global, societal, economic, and environmental contexts. Highlighting a wide range of topics such as academic integrity, gamification, and professional development, this book is essential for teachers, researchers, educational policymakers, curriculum designers, educational software developers, administrators, and academicians. |
| ai in engineering education: Teaching AI Michelle Zimmerman, 2018-12-15 Get the tools, resources and insights you need to explore artificial intelligence in the classroom and explore what students need to know about living in a world with AI. For many, artificial intelligence, or AI, may seem like science fiction, or inherently overwhelming. The reality is that AI is already being applied in industry and, for many of us, in our daily lives as well. A better understanding of AI can help you make informed decisions in the classroom that will impact the future of your students. Drawing from a broad variety of expert voices from countries including Australia, Japan, and South Africa, as well as educators from around the world and underrepresented student voices, this book explores some of the ways AI can improve education. These include educating learners about AI, teaching them about living in a world where they will be surrounded by AI and helping educators understand how they can use AI to augment human ability. Each chapter offers activities and questions to help you deepen your understanding, try out new concepts and reflect on the information presented. Links to media artifacts from trusted sources will help make your learning experience more dynamic while also providing additional resources to use in your classroom. This book: • Offers a unique approach to the topic, with chapter opening scenes, case studies, and featured student voices. • Discusses a variety of ways to teach students about AI, through design thinking, project-based learning and STEM connections. • Includes lesson ideas, activities and tools for exploring AI with your students. • Includes references to films and other media you can use in class to start discussions on AI or inspire design thinking and STEM projects. In Teaching AI, you’ll learn what AI is, how it works and how to use it to better prepare students in a world with increased human-computer interaction. |
| ai in engineering education: The Journal of Engineering Education , 1927 |
| ai in engineering education: A Whole New Engineer: The Coming Revolution in Engineering Education Mark Somerville, David E. Goldberg, 2019-09-18 A Revolution Is Coming. It Isn't What You Think.This book tells the improbable stories of Franklin W. Olin College of Engineering, a small startup in Needham, Massachusetts, with aspirations to be a beacon to engineering education everywhere, and the iFoundry incubator at the University of Illinois, an unfunded pilot program with aspirations to change engineering at a large public university that wasn't particularly interested in changing. That either one survived is story enough, but what they found out together changes the course of education transformation forever: - How joy, trust, openness, and connec- tion are the keys to unleashing young, courageous engineers.- How engineers educated in narrow technical terms with a fixed mindset need an education that actively engages six minds-analytical, design, people, linguistic, body, and mindful- using a growth mindset.- How emotion and culture are the crucial elements of change, not content, curriculum, and pedagogy.- How four technologies of trust are well established and widely available to promote more rapid academic change.- How all stakeholders can join together in a movement of open innovation to accelerate collaborative disruption of the status quo.Read this book and get a glimpse inside the coming revolution in engineering. Feel the engaging stories in this book and understand the depth of change that is coming. Use this book to help select, shape, demand, and create educational experiences aligned with the creative imperative of the twenty-first century. |
| ai in engineering education: Engineering Justice Jon A. Leydens, Juan C. Lucena, 2017-12-18 Shows how the engineering curriculum can be a site for rendering social justice visible in engineering, for exploring complex socio-technical interplays inherent in engineering practice, and for enhancing teaching and learning Using social justice as a catalyst for curricular transformation, Engineering Justice presents an examination of how politics, culture, and other social issues are inherent in the practice of engineering. It aims to align engineering curricula with socially just outcomes, increase enrollment among underrepresented groups, and lessen lingering gender, class, and ethnicity gaps by showing how the power of engineering knowledge can be explicitly harnessed to serve the underserved and address social inequalities. This book is meant to transform the way educators think about engineering curricula through creating or transforming existing courses to attract, retain, and motivate engineering students to become professionals who enact engineering for social justice. Engineering Justice offers thought-provoking chapters on: why social justice is inherent yet often invisible in engineering education and practice; engineering design for social justice; social justice in the engineering sciences; social justice in humanities and social science courses for engineers; and transforming engineering education and practice. In addition, this book: Provides a transformative framework for engineering educators in service learning, professional communication, humanitarian engineering, community service, social entrepreneurship, and social responsibility Includes strategies that engineers on the job can use to advocate for social justice issues and explain their importance to employers, clients, and supervisors Discusses diversity in engineering educational contexts and how it affects the way students learn and develop Engineering Justice is an important book for today’s professors, administrators, and curriculum specialists who seek to produce the best engineers of today and tomorrow. |
| ai in engineering education: AI-Enhanced Teaching Methods Ahmed, Zeinab E., Hassan, Aisha A., Saeed, Rashid A., 2024-04-22 The digital age has ushered in an era where students must be equipped not only with traditional knowledge but also with the skills to navigate an increasingly interconnected and technologically driven world. As traditional teaching methods encounter the complexities of the 21st century, the demand for innovation becomes more apparent. This paves the way for the era of artificial intelligence (AI), a technological frontier that carries the potential to reshape education fundamentally. AI-Enhanced Teaching Methods recognizes the urgency of the ongoing technological shift and delves into an exploration of how AI can be effectively harnessed to redefine the learning experience. The book serves as a guide for educators, offering insights into navigating between conventional teaching methodologies and the possibilities presented by AI. It provides an understanding of AI's role in education, covering topics from machine learning to natural language processing. Ethical considerations, including privacy and bias, are thoroughly addressed with thoughtful solutions as well. Additionally, the book provides valuable support for administrators, aiding in the integration of these technologies into existing curricula. |
| ai in engineering education: Manufacturing Engineering Education J. Paulo Davim, J Paulo Davim, 2018-09-19 Manufacturing Engineering Education includes original and unpublished chapters that develop the applications of the manufacturing engineering education field. Chapters convey innovative research ideas that have a prodigious significance in the life of academics, engineers, researchers and professionals involved with manufacturing engineering. Today, the interest in this subject is shown in many prominent global institutes and universities, and the robust momentum of manufacturing has helped the U.S. economy continue to grow throughout 2014. This book covers manufacturing engineering education, with a special emphasis on curriculum development, and didactic aspects. - Includes original and unpublished chapters that develop the applications of the manufacturing engineering education principle - Applies manufacturing engineering education to curriculum development - Offers research ideas that can be applied to the work of academics, engineers, researchers and professionals |
| ai in engineering education: Handbook of Research on Teaching with Virtual Environments and AI Gianni Panconesi, Maria Guida, 2021 In a world where where online and offline overlap and coincide, this book presents how digital intelligence is a key competence for the future of education and looks at how AI and other digital tools are improving the world of education-- |
| ai in engineering education: Artificial Intelligence in Mechanical and Industrial Engineering Kaushik Kumar, Divya Zindani, J. Paulo Davim, 2021-06-20 Artificial Intelligence in Mechanical and Industrial Engineering offers a unified platform for the dissemination of basic and applied knowledge on the integration of artificial intelligence within the realm of mechanical and industrial engineering. The book covers the tools and information needed to build successful careers and a source of knowledge for those working with AI within these domains. The book offers a systematic approach to explicate fundamentals as well as recent advances. It incorporates various case studies for major topics as well as numerous examples. It will also include real-time intelligent automation and associated supporting methodologies and techniques, and cover decision-support systems, as well as applications of Chaos Theory and Fractals. The book will give scientists, researchers, instructors, students, and practitioners the tools and information needed to build successful careers and to be an impetus to advancements in next-generation mechanical and industrial engineering domains. |
| ai in engineering education: AI Injected e-Learning Matthew Montebello, 2017-10-27 This book reviews a blend of artificial intelligence (AI) approaches that can take e-learning to the next level by adding value through customization. It investigates three methods: crowdsourcing via social networks; user profiling through machine learning techniques, and personal learning portfolios using learning analytics. Technology and education have drawn closer together over the years as they complement each other within the domain of e-learning, and different generations of online education reflect the evolution of new technologies as researcher and developers continuously seek to optimize the electronic medium to enhance the effectiveness of e-learning. Artificial intelligence (AI) for e-learning promises personalized online education through a combination of different intelligent techniques that are grounded in established learning theories while at the same time addressing a number of common e-learning issues. This book is intended for education technologists and e-learning researchers as well as for a general readership interested in the evolution of online education based on techniques like machine learning, crowdsourcing, and learner profiling that can be merged to characterize the future of personalized e-learning. |
| ai in engineering education: Deep Learning for Coders with fastai and PyTorch Jeremy Howard, Sylvain Gugger, 2020-06-29 Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala |
| ai in engineering education: Transforming Education With Generative AI: Prompt Engineering and Synthetic Content Creation Sharma, Ramesh C., Bozkurt, Aras, 2024-02-07 The rise of generative Artificial Intelligence (AI) signifies a momentous stride in the evolution of Large Language Models (LLMs) within the expansive sphere of Natural Language Processing (NLP). This groundbreaking advancement ripples through numerous facets of our existence, with education, AI literacy, and curriculum enhancement emerging as focal points of transformation. Within the pages of Transforming Education With Generative AI: Prompt Engineering and Synthetic Content Creation, readers embark on a journey into the heart of this transformative phenomenon. Generative AI's influence extends deeply into education, touching the lives of educators, administrators, policymakers, and learners alike. Within the pages of this book, we explore the intricate art of prompt engineering, a skill that shapes the quality of AI-generated educational content. As generative AI becomes increasingly accessible, this comprehensive volume empowers its audience, by providing them with the knowledge needed to navigate and harness the potential of this powerful tool. |
| ai in engineering education: Insights Into Global Engineering Education After the Birth of Industry 5.0 Montaha Bouezzeddine, 2022-04-20 Insights Into Global Engineering Education After the Birth of Industry 5.0 presents a comprehensive overview of recent developments in the fields of engineering and technology. The book comprises single chapters authored by various researchers and edited by an expert active in the engineering education research area. It provides a thorough overview of the latest research efforts by international authors on engineering education and opens potential new research paths for further novel developments. |
| ai in engineering education: The Impact of Innovative ICT Education and AI on the Pedagogical Paradigm Boris Aberšek, 2019-04-25 To be a good teacher, one must acquire a large set of different kinds of interdisciplinary knowledge. Education for teachers and trainers consists, in part, of learning the language of education and the appropriate associated skills. A deeper understanding of judgments and choices also requires a richer vocabulary than is available in everyday language. On a systemic level, the education system needs to consider the individual as the basic building block of society, and further take into consideration the individual’s consciousness related to their emotional intelligence. Because a person’s consciousness is something entirely singular and inherent to the individual, some kind of generalization will have to be constructed, which will contribute enough in terms of novelty and progress, to make it innovative enough for the purposes of teaching and learning. This volume will serve to provoke cognitive dissonance and intellectual unease, as it explores cognitive theories and inspires researchers and teachers to update and invigorate some of the theories that have been embedded in their minds since their own school years. In order for this to happen, the book provides readers with many valuable insights and introduces new experiences resulting from alternative teaching practices. |
| ai in engineering education: Teaching and Learning STEM Richard M. Felder, Rebecca Brent, 2024-03-19 The widely used STEM education book, updated Teaching and Learning STEM: A Practical Guide covers teaching and learning issues unique to teaching in the science, technology, engineering, and math (STEM) disciplines. Secondary and postsecondary instructors in STEM areas need to master specific skills, such as teaching problem-solving, which are not regularly addressed in other teaching and learning books. This book fills the gap, addressing, topics like learning objectives, course design, choosing a text, effective instruction, active learning, teaching with technology, and assessment—all from a STEM perspective. You’ll also gain the knowledge to implement learner-centered instruction, which has been shown to improve learning outcomes across disciplines. For this edition, chapters have been updated to reflect recent cognitive science and empirical educational research findings that inform STEM pedagogy. You’ll also find a new section on actively engaging students in synchronous and asynchronous online courses, and content has been substantially revised to reflect recent developments in instructional technology and online course development and delivery. Plan and deliver lessons that actively engage students—in person or online Assess students’ progress and help ensure retention of all concepts learned Help students develop skills in problem-solving, self-directed learning, critical thinking, teamwork, and communication Meet the learning needs of STEM students with diverse backgrounds and identities The strategies presented in Teaching and Learning STEM don’t require revolutionary time-intensive changes in your teaching, but rather a gradual integration of traditional and new methods. The result will be a marked improvement in your teaching and your students’ learning. |
| ai in engineering education: An Introduction to Artificial Intelligence in Education Shengquan Yu, Yu Lu, 2021-11-29 This book systematically reviews a broad range of cases in education that utilize cutting-edge AI technologies. Furthermore, it introduces readers to the latest findings on the scope of AI in education, so as to inspire researchers from non-technological fields (e.g. education, psychology and neuroscience) to solve education problems using the latest AI techniques. It also showcases a number of established AI systems and products that have been employed for education. Lastly, the book discusses how AI can offer an enabling technology for critical aspects of education, typically including the learner, content, strategy, tools and environment, and what breakthroughs and advances the future holds. The book provides an essential resource for researchers, students and industrial practitioners interested and engaged in the fields of AI and education. It also offers a convenient handbook for non-professional readers who need a primer on AI in education, and who want to gain a deeper understanding of emerging trends in this domain. |
| ai in engineering education: Engineering in K-12 Education National Research Council, National Academy of Engineering, Committee on K-12 Engineering Education, 2009-09-08 Engineering education in K-12 classrooms is a small but growing phenomenon that may have implications for engineering and also for the other STEM subjects-science, technology, and mathematics. Specifically, engineering education may improve student learning and achievement in science and mathematics, increase awareness of engineering and the work of engineers, boost youth interest in pursuing engineering as a career, and increase the technological literacy of all students. The teaching of STEM subjects in U.S. schools must be improved in order to retain U.S. competitiveness in the global economy and to develop a workforce with the knowledge and skills to address technical and technological issues. Engineering in K-12 Education reviews the scope and impact of engineering education today and makes several recommendations to address curriculum, policy, and funding issues. The book also analyzes a number of K-12 engineering curricula in depth and discusses what is known from the cognitive sciences about how children learn engineering-related concepts and skills. Engineering in K-12 Education will serve as a reference for science, technology, engineering, and math educators, policy makers, employers, and others concerned about the development of the country's technical workforce. The book will also prove useful to educational researchers, cognitive scientists, advocates for greater public understanding of engineering, and those working to boost technological and scientific literacy. |
| ai in engineering education: Innovative Learning Environments in STEM Higher Education Jungwoo Ryoo, Kurt Winkelmann, 2021-03-11 As explored in this open access book, higher education in STEM fields is influenced by many factors, including education research, government and school policies, financial considerations, technology limitations, and acceptance of innovations by faculty and students. In 2018, Drs. Ryoo and Winkelmann explored the opportunities, challenges, and future research initiatives of innovative learning environments (ILEs) in higher education STEM disciplines in their pioneering project: eXploring the Future of Innovative Learning Environments (X-FILEs). Workshop participants evaluated four main ILE categories: personalized and adaptive learning, multimodal learning formats, cross/extended reality (XR), and artificial intelligence (AI) and machine learning (ML). This open access book gathers the perspectives expressed during the X-FILEs workshop and its follow-up activities. It is designed to help inform education policy makers, researchers, developers, and practitioners about the adoption and implementation of ILEs in higher education. |
| ai in engineering education: STEM Education for the 21st Century Bryan Edward Penprase, 2020-04-07 This book chronicles the revolution in STEM teaching and learning that has arisen from a convergence of educational research, emerging technologies, and innovative ways of structuring both the physical space and classroom activities in STEM higher education. Beginning with a historical overview of US higher education and an overview of diversity in STEM in the US, the book sets a context in which our present-day innovation in science and technology urgently needs to provide more diversity and inclusion within STEM fields. Research-validated pedagogies using active learning and new types of research-based curriculum is transforming how physics, biology and other fields are taught in leading universities, and the book gives profiles of leading innovators in science education and examples of exciting new research-based courses taking root in US institutions. The book includes interviews with leading scientists and educators, case studies of new courses and new institutions, and descriptions of site visits where new trends in 21st STEM education are being developed. The book also takes the reader into innovative learning environments in engineering where students are empowered by emerging technologies to develop new creative capacity in their STEM education, through new centers for design thinking and liberal arts-based engineering. Equally innovative are new conceptual frameworks for course design and learning, and the book explores the concepts of Scientific Teaching, Backward Course Design, Threshold Concepts and Learning Taxonomies in a systematic way with examples from diverse scientific fields. Finally, the book takes the reader inside the leading centers for online education, including Udacity, Coursera and EdX, interviews the leaders and founders of MOOC technology, and gives a sense of how online education is evolving and what this means for STEM education. This book provides a broad and deep exploration into the historical context of science education and into some of the cutting-edge innovations that are reshaping how leading universities teach science and engineering. The emergence of exponentially advancing technologies such as synthetic biology, artificial intelligence and materials sciences has been described as the Fourth Industrial Revolution, and the book explores how these technologies will shape our future will bring a transformation of STEM curriculum that can help students solve many the most urgent problems facing our world and society. |
| ai in engineering education: Integrating Engineering Education and Humanities for Global Intercultural Perspectives Zhanna Anikina, 2020-05-06 This book presents papers from the International Conference on Integrating Engineering Education and Humanities for Global Intercultural Perspectives (IEEHGIP 2020), held on 25–27 March 2020. The conference brought together researchers and practitioners from various disciplines within engineering and humanities to offer a range of perspectives. Focusing on, but not limited to, Content and Language Integrated Learning (CLIL) in Russian education the book will appeal to a wide academic audience seeking ways to initiate positive changes in education. |
| ai in engineering education: Robot-Proof, revised and updated edition Joseph E. Aoun, 2024-10-15 A fresh look at a “robot-proof” education in the new age of generative AI. In 2017, Robot-Proof, the first edition, foresaw the advent of the AI economy and called for a new model of higher education designed to help human beings flourish alongside smart machines. That economy has arrived. Creative tasks that, seven years ago, seemed resistant to automation can now be performed with a simple prompt. As a result, we must now learn not only to be conversant with these technologies, but also to comprehend and deploy their outputs. In this revised and updated edition, Joseph Aoun rethinks the university’s mission for a world transformed by AI, advocating for the lifelong endeavor of a “robot-proof” education. Aoun puts forth a framework for a new curriculum, humanics, which integrates technological, data, and human literacies in an experiential setting, and he renews the call for universities to embrace lifelong learning through a social compact with government, employers, and learners themselves. Drawing on the latest developments and debates around generative AI, Robot-Proof is a blueprint for the university as a force for human reinvention in an era of technological change—an era in which we must constantly renegotiate the shifting boundaries between artificial intelligence and the capacities that remain uniquely human. |
| ai in engineering education: Deep Learning in Gaming and Animations Moolchand Sharma, Deevyankar Agarwal, Vikas Chaudhary, Prerna Sharma, 2024-10-04 The text discusses the core concepts and principles of deep learning in gaming and animation with applications in a single volume. It will be a useful reference text for graduate students, and professionals in diverse areas such as electrical engineering, electronics and communication engineering, computer science, gaming and animation. |
| ai in engineering education: Engineering Education , 1913 |
| ai in engineering education: Integration of Engineering Education and the Humanities: Global Intercultural Perspectives Zhanna Anikina, 2022-07-25 This book tackles the problems of engineering students and teachers while developing language skills through language education, transforming students’ mind-set through cultural studies, developing students’ intellectual abilities and personal qualities, and the use of information technologies in order to enhance the educational process. The International Conference Integration of Engineering Education and the Humanities: Global Intercultural Perspectives will take place 20–22 April 2022. It will be organized by Peter the Great Saint Petersburg Polytechnic University (Saint Petersburg, Russia) in collaboration with Research Centre Kairos (Tomsk, Russia). The event aims to raise discussions around a variety of aspects related to the integration of the humanities into engineering education. As such, the book will be of interest to the teachers, researchers and institutional leaders looking for the latest insights, experiences and research results on the topic. |
| ai in engineering education: Artificial Intelligence in Construction Engineering and Management Limao Zhang, Yue Pan, Xianguo Wu, Mirosław J. Skibniewski, 2021-06-18 This book highlights the latest technologies and applications of Artificial Intelligence (AI) in the domain of construction engineering and management. The construction industry worldwide has been a late bloomer to adopting digital technology, where construction projects are predominantly managed with a heavy reliance on the knowledge and experience of construction professionals. AI works by combining large amounts of data with fast, iterative processing, and intelligent algorithms (e.g., neural networks, process mining, and deep learning), allowing the computer to learn automatically from patterns or features in the data. It provides a wide range of solutions to address many challenging construction problems, such as knowledge discovery, risk estimates, root cause analysis, damage assessment and prediction, and defect detection. A tremendous transformation has taken place in the past years with the emerging applications of AI. This enables industrial participants to operate projects more efficiently and safely, not only increasing the automation and productivity in construction but also enhancing the competitiveness globally. |
| ai in engineering education: Facilitating Global Collaboration and Knowledge Sharing in Higher Education With Generative AI Yu, Poshan, Mulli, James, Syed, Zain Ali Shah, Umme, Laila, 2023-12-29 Chatbots powered by artificial intelligence (AI) have captivated the academic world as tools for human-like interaction across various settings. Within the realm of education, AI-powered chatbots, such as ChatGPT, hold the potential to revolutionize teaching, learning, and research processes. By simulating human conversation through vast data and machine learning algorithms, generative AI has unveiled new opportunities for personalized and adaptive learning experiences. Facilitating Global Collaboration and Knowledge Sharing in Higher Education With Generative AI delves into the promising prospects and challenges of applying generative AI in education while employing a critical interdisciplinary perspective. The book offers comprehensive insights into the transformative effects of generative AI on teaching, learning, and research. However, the application of generative AI in education also brings ethical, pedagogical, and technical challenges to the forefront. Concerns over privacy, data protection, and the impact of automation on human interaction and creativity demand thorough examination and practical solutions. Intended for educators, researchers, and administrators in higher education institutions, as well as policymakers and industry professionals at the intersection of AI and higher education. The book encompasses a wide range of themes, including the impact of AI-generated content on student engagement and performance in online learning environments, ethical implications of automating education through AI-powered chatbots, personalization of learning experiences for diverse student populations, and the challenges of integrating generative AI into traditional classroom settings. |
| ai in engineering education: The Journal of Engineering Education , 1925 |
| ai in engineering education: Using Educational Robots to Enhance Learning Dejian Liu, |
| ai in engineering education: Generative AI in Teaching and Learning Hai-Jew, Shalin, 2023-12-05 Generative AI in Teaching and Learning delves into the revolutionary field of generative artificial intelligence and its impact on education. This comprehensive guide explores the multifaceted applications of generative AI in both formal and informal learning environments, shedding light on the ethical considerations and immense opportunities that arise from its implementation. From the early approaches of utilizing generative AI in teaching to its integration into various facets of learning, this book offers a profound analysis of its potential. Teachers, researchers, instructional designers, developers, data analysts, programmers, and learners alike will find valuable insights into harnessing the power of generative AI for educational purposes. |
| ai in engineering education: Utilizing AI for Assessment, Grading, and Feedback in Higher Education Al Harrasi, Nasser Hamed, Salah El Din, Mohamed, 2024-05-06 As artificial intelligence (AI) continues to increase, its impact on higher education presents immense opportunities and daunting challenges. Across campuses worldwide, educators grapple with integrating AI into academic practices, from grading to teaching methodologies. However, the widespread adoption of AI, fueled by models like ChatGPT and Google Bard, raises concerns about its potential to undermine the learning process and compromise academic integrity. This disruptive force demands urgent attention and informed strategies to navigate its complexities effectively. With contributions from leading experts across diverse disciplines, this book catalyzes interdisciplinary collaboration and innovation. By bridging the gap between AI specialists and higher education professionals, the publication has paved the way for a nuanced understanding of AI's implications and opportunities. Utilizing AI for Assessment, Grading, and Feedback in Higher Education is an indispensable resource for those seeking to navigate the AI revolution in academia with confidence and foresight, offering actionable recommendations and a roadmap for leveraging AI to enhance teaching, learning, and research in higher education. |
| ai in engineering education: Reshaping Engineering Education Fawwaz Habbal, Anette Kolmos, Roger G. Hadgraft, Jette Egelund Holgaard, Kamar Reda, 2023-12-30 This open access book is dedicated to exploring methods and charting the course for enhancing engineering education in and beyond 2023. It delves into the idea that education, coupled with social connections, is indispensable for a more profound comprehension of the world and the creation of an improved quality of life. The book serves as a conduit for incorporating complex problem-solving into engineering education across various formats. It offers a structured approach for tackling complex issues, comparing an array of techniques for managing complexity within the realm of engineering education. Moreover, the book scrutinizes several complex case studies derived from the United Nation's Sustainable Development Goals. Additionally, it explores intricate problem-solving and curriculum change case studies specific to engineering education from Harvard University, the University of Technology Sydney, and Aalborg University. |
| ai in engineering education: General Aspects of Applying Generative AI in Higher Education Mohamed Lahby, |
| ai in engineering education: Technology and Tools in Engineering Education Prathamesh P. Churi, Vishal Kumar, Utku Kose, N. T. Rao, 2021-10-28 This book explores the innovative and research methods of the teaching-learning process in Engineering field. It focuses on the use of technology in the field of education. It also provides a platform to academicians and educationalists to share their ideas and best practices. The book includes specific pedagogy used in engineering education. It offers case studies and classroom practices which also include those used in distance mode and during the COVID-19 pandemic. It provides comparisons of national and international accreditation bodies, directions on cost-effective technology, and it discusses advanced technologies such as VR and augmented reality used in education. This book is intended for research scholars who are pursuing their masters and doctoral studies in the engineering education field as well as teachers who teach undergraduate and postgraduate courses to engineering students. |
| ai in engineering education: Artificial Intelligence with Python Prateek Joshi, 2017-01-27 Build real-world Artificial Intelligence applications with Python to intelligently interact with the world around you About This Book Step into the amazing world of intelligent apps using this comprehensive guide Enter the world of Artificial Intelligence, explore it, and create your own applications Work through simple yet insightful examples that will get you up and running with Artificial Intelligence in no time Who This Book Is For This book is for Python developers who want to build real-world Artificial Intelligence applications. This book is friendly to Python beginners, but being familiar with Python would be useful to play around with the code. It will also be useful for experienced Python programmers who are looking to use Artificial Intelligence techniques in their existing technology stacks. What You Will Learn Realize different classification and regression techniques Understand the concept of clustering and how to use it to automatically segment data See how to build an intelligent recommender system Understand logic programming and how to use it Build automatic speech recognition systems Understand the basics of heuristic search and genetic programming Develop games using Artificial Intelligence Learn how reinforcement learning works Discover how to build intelligent applications centered on images, text, and time series data See how to use deep learning algorithms and build applications based on it In Detail Artificial Intelligence is becoming increasingly relevant in the modern world where everything is driven by technology and data. It is used extensively across many fields such as search engines, image recognition, robotics, finance, and so on. We will explore various real-world scenarios in this book and you'll learn about various algorithms that can be used to build Artificial Intelligence applications. During the course of this book, you will find out how to make informed decisions about what algorithms to use in a given context. Starting from the basics of Artificial Intelligence, you will learn how to develop various building blocks using different data mining techniques. You will see how to implement different algorithms to get the best possible results, and will understand how to apply them to real-world scenarios. If you want to add an intelligence layer to any application that's based on images, text, stock market, or some other form of data, this exciting book on Artificial Intelligence will definitely be your guide! Style and approach This highly practical book will show you how to implement Artificial Intelligence. The book provides multiple examples enabling you to create smart applications to meet the needs of your organization. In every chapter, we explain an algorithm, implement it, and then build a smart application. |
| ai in engineering education: Rewiring Education John D. Couch, 2023-01-03 What if we could unlock the potential in every child? As it turns out, we can. Apple's iconic cofounder Steve Jobs had a powerful vision for education: employing technology to make an enormous impact on the lives of millions of students. To realize this vision, Jobs tapped John D. Couch, a trusted engineer and executive with a passion for education. Couch believed the real purpose of education was to help children discover their unique potential and empower them to reach beyond their perceived limitations. Today, technology is increasingly integrated into every aspect of our lives, rewiring our homes, our jobs, and even our brains. Most important, it presents an opportunity to rewire education to enrich and strengthen our schools, children, and society In Rewiring Education, Couch shares the professional lessons he's learned during his 50-plus years in education and technology. He takes us behind Apple's major research study, Apple Classrooms of Tomorrow (ACOT), and its follow-up (ACOT 2), highlighting the powerful effects of the Challenge-Based Learning framework. Going beyond Apple's walls, he also introduces us to some of the most extraordinary parents, educators, and entrepreneurs from around the world who have ignored the failed promises of memorization and, instead, utilize new science-backed methods and technologies that benefit all children, from those who struggle to honor students. Rewiring Education presents a bold vision for the future of education, looking at promising emerging technologies and how we—as parents, teachers, and voters—can ensure children are provided with opportunities and access to the relevant, creative, collaborative, and challenging learning environments they need to succeed. |
Artificial Intelligence Aided Engineering Education: State of the …
In this study, we concentrate on how AI techniques can support the teaching-learning process in engineering and we describe how AI can be swiftly introduced into any engineering programme.
Artificial Intelligence and the Future of Teaching and Learning
This report describes opportunities for using AI to improve education, recognizes challenges that will arise, and develops recommendations to guide further policy development. Rising Interest in …
INTEGRATING AI EDUCATION IN DISCIPLINARY …
In this paper we build upon the three curriculum response strategies proposed by Kolmos, Hadgraft, and Holgaard (2016), the Academic Plan Model (Lattuca and Stark 2009), and perspectives from …
The impact of AI and generative technologies on the …
explores how AI and GenAI technologies have transformed engineering businesses and the workforce, and, importantly, how they will evolve. Generative artificial intelligence (GenAI) will be …
Engineering Education in the Era of Generative Artificial …
Gen AI enables new approaches to teaching and learning in engineering by providing on-demand, adaptive support. Gen AI tools are making education more learner-centered than ever before.
Embracing Computational Thinking as an Impetus for Artificial ...
development of AI and ML in engineering and technology education may, for example, help connect systems to solve a given design challenge or meet a need that students may relate to in the ever …
Artificial Intelligence (AI) and Engineering Education
voice-recognition systems before they become ordinary, an increasing range of AI-based activities that now seem incon-sequential will be embedded in engineering education practices with …
Post-pandemic Education Strategy: Framework for Artificial …
To fill this research gap, we developed an implementation strategy called AI-empowered Education in Engineer-ing (AIEd-Eng), which is composed of four stages, namely, processes, …
AN INTERDISCIPLINARY COMPETENCE PROFILE FOR AI IN …
Conference Key Areas: Artificial Intelligence in Education, Curriculum Development Keywords: AI Education, AI Literacy, Cross-Discipline Learning, Engineering Curricula, Future Skills ABSTRACT …
Integrating Artificial Intelligence into Electrical Engineering ...
Among these, the rise of Artificial Intelligence (AI) offers transformative potential. This study aims to comprehensively explore the integration of AI tools within EE courses, emphasizing its …
STUDENTS’ EXPERIENCES FROM USING AI IN ENGINEERING …
We want to find out the positives and negatives of AI in engineering education from the students’ perspective and discuss the opportunities of AI in engineering education.
Redefining Engineering Education: The Transformative Role of
Academics are interested in generative AI in conventional engineering education. Qadir, J. (2023) states that engineering education adapts to new technology and industrial demands.
Educational impacts of generative artificial intelligence on …
Generative AI significantly enhances engineering education by addressing gaps in traditional theory-driven teaching and meeting these three psychological needs through adaptive learning …
TEACHING AI COMPETENCIES IN ENGINEERING USING …
The use of Artificial Intelligence (AI) as a tool and assistance is growing and requires engineers to enhance their digital skills including data and AI competencies. Thus, higher education institutes …
Whole-Person Education for AI Engineers - arXiv.org
Our paper explores the need for a whole-person education approach in AI engineering education, drawing on autoethno-graphic reflections from diverse stakeholders, including stu-dents, …
Impact of AI Tools on Engineering Education
Balancing the advantages and challenges is essential for maximizing the benefits of integrating AI in engineering education. Artificial intelligence (AI) is known as a computer-controlled robot from …
Digital Transition Framework for Higher Education in AI …
It examines the digitalization of classrooms, expansion of teaching elements, and redesign of educational dynamics, while highlighting digital innovations in teaching methodologies and the …
Effects of a Prompt Engineering Intervention on Undergraduate …
Prompt engineering, or creating effective instructions to interact with LLMs, has become a crucial skill that students must acquire to succeed in both academic and workplace settings. However, …
Journal of Engineering Education: Special Issue Call for Papers
The editors of this special issue in the Journal of Engineering Education are interested in receiving manuscripts that showcase ways in which generative AI can be used to support engineering …
AI-Tutoring in Software Engineering Education - arXiv.org
In this paper, we conducted an exploratory case study by inte-grating the GPT-3.5-Turbo model as an AI-Tutor within the APAS Artemis. Through a combination of empirical data collection and an …
AI Education for K-12: Connecting AI Concepts to the High …
AI education in K-12 classrooms. In this paper, we discuss our pilot work on connecting the US high school math curriculum to AI concepts taught in higher education classrooms, in order to …
Government of Maharashtra State Common Entrance Test Cell
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Whole-Person Education for AI Engineers - arXiv.org
AI engineering education, a shift that prepares future engineers not just to build technology, but to ethically navigate it and arXiv:2506.09185v1 [cs.CY] 10 Jun 2025. Conference Proceedings …
DoD AI Education Strategy
DoD AI Education Strategy 2 delivery of AI capabilities into multidisciplinary groups of personnel who comprise Integrated Product Teams (IPTs).4 Third, DoD will prioritize establishing its …
Artificial intelligence and its scope in different areas with …
Fig 2: Factors included in AI 3. Scope of artificial intelligence in different areas 3.1. In the field of education 3.1.1. Artificial intelligence can automate basic activities in education, like grading …
National AI Engineering Initiative Scalable AI
The Pillars of AI Engineering 1. Human-Centered 2. Robust and Secure 3. Scalable The emergent discipline of AI Engineering is focused on three pillars: human- ... needs training and education …
Understanding the impact of artificial intelligence on skills ... - ed
AN EXPLORATION INTO CURRENT AI EDUCATION AND TRAINING PRACTICES 16 Planning and governance for the AI era 17 AI policy and strategy review 17 ... STEM Science, …
Enhancing Computer Programming Education with LLMs: A …
Jul 9, 2024 · In computer programming education, LLMs and prompt engineering hold promise for personalized instruction. By harnessing LLMs’ capability to comprehend and respond to …
An explanatory study of factors influencing engagement in AI …
1Department of Computer Information Engineering, Kunsan National University, Gunsan 54150, ... As K-12 AI education advances, the signicance and renement of related models and …
Computers and Education: Artificial Intelligence - University …
Oct 21, 2022 · gaps in AI education and integrate AI across the curriculum at a traditional research university. The University of Florida (UF) is infusing AI across the curriculum and …
Generative AI in education
There is appetite for government support to ensure GenAI adoption in education is safe, effective, and aligns with good pedagogy. There is little robust evidence on the impact of GenAI in …
Transforming Education With Generative AI - ResearchGate
Transforming Education With Generative AI: Prompt Engineering and Synthetic Content Creation Ramesh C. Sharma Ambedkar University, Delhi, India Aras Bozkurt
TEACHING AI COMPETENCIES IN ENGINEERING USING …
Conference Key Areas: Engineering Skills, Teaching Methods Keywords: AI Education, Project-based learning, Open Educational Resources, Engineering Curricula, Teaching Methods …
CS6659 ARTIFICIAL INTELLIGENCE - Jeppiaar Engineering …
III YEAR / VI SEM / AI QB JEPPIAAR ENGINEERING COLLEGE DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING CS6659 ARTIFICIAL INTELLIGENCE Question …
The application of AI technologies in STEM education: a …
the practice and research in the AI-STEM education. Literature review With the development of computer science and compu-tational technologies, automatic, adaptive, and ecient ...
STEM-based Artificial Intelligence Learning in General …
Since AI is an important scientific issue in this era, it has been regarded as a priority in higher education. For engineering students, AI is a kind of technology. However, for non-engineering …
Generative Artificial Intelligence for Education and Pedagogy
1. Evaluate the feasibility and benefits and limitations of using AI technologies in an educational setting and its impact on learning outcomes. 2. Assess the ethical implications of use of AI …
A Review to Artificial Intelligence in Education
A Research Paper submitted to the Department of Engineering and Society Presented to the Faculty of the School of Engineering and Applied Science University of Virginia • …
Data-Directed Education: The Future of AI in Education - NSF
NSF has funded three National AI Institutes that pertain to education and address basic AI research issues and are long term (~ five years) and involve large amounts of funding …
Artificial intelligence in mathematics education: A systematic ...
impact of AI and the use of robotics or software as well as machines from AI in the teaching and learning of mathematics to students at all levels of education. Research Questions 1. What AI …
Integration of artificial intelligence performance prediction and ...
Accuracy of AI prediction models: From the AI model perspective Online higher education has attracted extensive attention in the COVID-19 period with a goal to improving the quality of …
The Role of Artificial Intelligence in STEM Education - APSCE
Engineering design into middle school science curricula. Students learn simple heuristic search methods to find “optimal” solutions to a playground design problem. We have also used AI/ML …
Government of Maharashtra State Common Entrance Test Cell
27 1739 (95.7644211) 411524210 4115 - Shri Ramdeobaba College of Engineering and Management, Nagpur Computer Science and JEE(Main) AI to AI AI Engineering 3185 - …
Government of Maharashtra State Common Entrance Test Cell
12 1189 (96.8227216) 627324510 Computer Engineering JEE(Main) AI to AI AI 13 1251 (96.6949982) 321124510 3211 - S.I.E.S. Graduate School of Technology, Nerul, Navi Mumbai …
Generative Artificial Intelligence (AI) in K-12 Classrooms
engineering of making intelligent machines, especially intelligent computer programs. It is related to the similar task of using computers to understand ... Given the influx of AI in education, …
AI-Driven Learning Analytics in STEM Education
education. Ethical concerns and moral considerations should be discussed in school AI and STEM education. Keywords: Education; disciplines; AI in education; STEM education This is …
How will AI transform education? - California State University
Status of Higher Education 7 in high school grad start college Only ½ graduate on time Only 7.3% single parents get a degree in 6 years
Navigating the Landscape of Higher Engineering Education
Navigating the Landscape of Higher Engineering Education, Delft, April 2020 3 The Organisation for Economic Co-operation and Development, the World Economic Forum, the Global …
Government of Maharashtra State Common Entrance Test Cell
7 905 (97.4084446) 319924510 Computer Engineering JEE(Main) AI to AI AI 8 945 (97.3253072) 627124610 6271 - Pune Institute of Computer Technology, Dhankavdi, Pune Information …
Revolutionizing education: Artificial intelligence empowered …
intelligence (AI)-based tools in education. Since the role of AI is inevitable in future education, current research aims to identify the level of awareness of faculty members on the applicability …
Framework of Artificial Intelligence Learning Platform for …
education and estimate the framework’s suitability. The research is discussed into three phases: 1) synthesizing an intelligent learning platform by using Artificial Intelligence (AI), 2) developing …
Artificial Intelligence In Mathematics Education: A ... - IJCRT
1.1 Importance of AI in Mathematics Education Artificial Intelligence (AI) refers to the scientific and engineering discipline dedicated to imparting computers with the ability to undertake tasks that …
Perceptions of and Behavioral Intentions towards Learning …
Engineering and Architecture, Beijing, China // cschai@cuhk.edu.hk // pylin@nknu.edu.tw // ... With regard to AI education, however, TPB-based research has yet to be conducted despite …
B.Tech ROBOTICS AND ARTIFICIAL INTELLIGENCE …
and Engineering. R&AI programme introduces the leading technologies underlying the development of Robotic and Intelligent systems, including Machine Learning (ML) and AI, that …
AI in Civil Engineering - Springer
Zhao AI in Civil Engineering Page 2 of 2 manufacturing systems, the constrution sector has been transformed from labor-intensive to technology-inten- sive; (3) Intelligent facilities and disaster …
CTE Model Curriculum for - All India Council for Technical …
TE Model Curriculum for AIC UG Degree Course in Robotics & Artificial Intelligence Engineering . i . Model Curriculum for . UG Degree Course . in . Robotics and Artificial Intelligence …
Trends, Research Issues and Applications of Artificial
Among all the review studies we found on AI in education, five articles appear to be both the most representative and recent. Chen et al. (2020a), who analyzed the AIEd literature from 1999 to …
AI STRATEGIES AND ROADMAP - Massachusetts Institute …
AI STRATEGIES AND ROADMAP: SYSTEMS ENGINEERING APPROACH TO AI DEVELOPMENT AND DEPLOYMENT Participant takeaways REGISTER ONLINE AT …
The Cambridge Handbook of Artificial Intelligence
Electronics Engineers (IEEE) as one of the “10 to watch in AI.” Konstantine Arkoudas is an AI research scientist at Applied Communication Sciences, with a focus on reasoning and …
THE FUTURE OF ENGINEERING EDUCATION: A DATA …
Engineering education currently stands at a crossroads, facing both challenges and opportunities as it adapts to the demands of the 21st century. Traditional lecture-based pedagogies are …
Teaching AI Ethics to Engineering Students: Reflections on …
effectively. At the forefront of this progress are the AI researchers and engineers, so as a complementary approach, we should aim to foster a strong sense of professional ethics …
Engineering Education in the Era of ChatGPT: Promise and …
Dec 29, 2022 · Engineering Education in the Era of ChatGPT: Promise and Pitfalls of Generative AI for Education This paper was downloaded from TechRxiv (https://www.techrxiv.org).
Artificial Intelligence Technology Management of Teachers
perceive AI as a tool for instructional support and professional development, as well as how students respond to AI-driven learning environments in terms of engagement, interest, and …
Charting the Future of AI in Project-Based Learning: A Co …
Jan 29, 2024 · of commercial AI products like ChatGPT, many students may lack the necessary skills, such as prompt engineering [22, 93], to use AI in the way they want. Besides, many of …
Editorial Note: From Conventional AI to Modern AI in …
transformation and trends in AI in education, this special issue, including 12 research articles, aims to launch an in-depth discussion on re-examining AI and analytics techniques in teaching …
Generative AI and Prompt Engineering: The Art of
Asian Journal of Distance Education Bozkurt, A., & Sharma, R. C. ii Introduction: Another Day in the AI Paradise And nowadays, the idea of AI is not really science fiction anymore - it's just ...
Prompting Change: Exploring Prompt Engineering in Large …
Potential LLM AI Uses in Education LLM AI tools like OpenAI’s ChatGPT and Google’s Bard are entering educational contexts with diverse learning and ... in LLM AI Prompt engineering, in …
#LEARNAI
core business practices; and building AI engineering talents and capabilities to catalyse industry transformation. AISG is funded by the National Research Foundation and hosted by the …
DIGITAL NOTES ON ARTIFICIAL INTELLIGENCE - MRCET
AI is the study of the mental faculties through the use of computational models AI is the study of intellectual/mental processes as computational processes. AI program will demonstrate a high …
