Ai And Education Conference

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The Transformative Power of AI in Education: Insights from the AI and Education Conference



Author: Dr. Anya Sharma, PhD, Associate Professor of Educational Technology at Stanford University. Dr. Sharma's research focuses on the intersection of artificial intelligence and personalized learning, with a particular emphasis on the ethical implications of AI in education. She has been a keynote speaker at numerous international conferences, including several prominent AI and education conferences.

Publisher: EduTech Insights, a leading publisher of peer-reviewed research and analysis in the field of educational technology. EduTech Insights maintains a rigorous editorial process and is widely respected for its unbiased and data-driven reporting on emerging trends in education.

Editor: Mr. David Chen, experienced editor with over 15 years of experience in publishing educational research. He has edited numerous publications on educational technology, including several reports on previous AI and education conferences. His expertise ensures the accuracy and clarity of the presented information.


Keywords: AI and education conference, artificial intelligence in education, personalized learning, AI-powered education, educational technology, future of education, AI ethics in education, AI in classrooms, AI assessment, AI tutoring


1. Introduction: The Growing Influence of AI and Education Conferences



The rapid advancement of artificial intelligence (AI) has significantly impacted various sectors, and education is no exception. Dedicated AI and education conferences have become crucial platforms for researchers, educators, policymakers, and technology developers to discuss the transformative potential and inherent challenges of integrating AI into educational practices. This report summarizes key findings and discussions from a recent prominent AI and education conference, analyzing the current state of AI in education and offering insights into future trends.


2. Key Themes Emerging from the AI and Education Conference



The conference highlighted several overarching themes:

2.1 Personalized Learning and Adaptive Education: A major focus at the AI and education conference was the potential of AI to personalize the learning experience. Research presented demonstrated that AI-powered systems can adapt to individual student needs, providing customized learning pathways, targeted feedback, and differentiated instruction. Studies showed significant improvements in student engagement and learning outcomes when personalized learning platforms incorporating AI were implemented. One study, presented by Dr. Lee from MIT, showed a 25% increase in student achievement in math using an AI-powered tutoring system compared to traditional methods. This finding underscores the potential for AI to address the diverse learning styles and paces of individual students, a significant challenge in traditional classroom settings.

2.2 AI-Powered Assessment and Feedback: The conference also explored the role of AI in revolutionizing assessment practices. Presentations showcased AI systems capable of automatically grading assignments, providing detailed feedback to students, and identifying areas where students struggle. This automated feedback can free up educators' time, allowing them to focus on individual student needs and higher-order teaching tasks. However, ethical concerns regarding bias in AI algorithms and the potential for over-reliance on automated assessment were also discussed. Data presented by Dr. Ramirez from Stanford highlighted the need for careful algorithm design and ongoing human oversight to ensure fairness and accuracy in AI-powered assessment.

2.3 AI-Driven Teacher Support and Professional Development: The AI and education conference emphasized the importance of supporting educators in effectively integrating AI into their teaching practices. Presentations explored the use of AI tools to assist teachers with lesson planning, curriculum development, and classroom management. Furthermore, the conference highlighted the need for ongoing professional development programs to equip educators with the necessary skills and knowledge to effectively utilize AI in their classrooms. A survey conducted among conference attendees revealed a significant demand for more accessible and tailored professional development opportunities focusing on AI integration in education.


2.4 Addressing Ethical Considerations and Bias: A significant portion of the AI and education conference was dedicated to addressing the ethical implications of using AI in education. Discussions centered on issues such as data privacy, algorithmic bias, and the potential for AI to exacerbate existing inequalities. Experts stressed the importance of developing ethical guidelines and regulations to ensure responsible AI implementation in education. The lack of diversity in AI development teams was also highlighted as a contributing factor to potential bias in algorithms. The conference called for increased efforts to promote diversity and inclusion within the AI education sector.


3. Research Findings and Data from the AI and Education Conference



Quantitative and qualitative data presented at the conference strongly supported the potential benefits of AI in education. Studies using randomized controlled trials showed significant improvements in student learning outcomes, particularly in personalized learning environments. However, the conference also acknowledged the need for further research to address the long-term effects of AI integration and to fully understand the ethical and societal implications. The data collected indicated a strong correlation between the quality of AI implementation and positive learning outcomes, highlighting the importance of well-designed systems and appropriate teacher training. However, the lack of robust longitudinal studies was identified as a gap in the current research landscape.


4. Future Directions and Challenges in AI and Education



The AI and education conference concluded with a discussion on future directions and challenges. Experts identified the need for more robust research on the long-term impact of AI on student learning, teacher development, and educational equity. Furthermore, the conference highlighted the importance of developing interdisciplinary collaborations between AI researchers, educators, policymakers, and ethicists to ensure responsible and effective AI implementation in education. Challenges such as addressing the digital divide, ensuring data privacy and security, and mitigating algorithmic bias were also emphasized as critical areas requiring attention.


5. Conclusion



The AI and education conference provided valuable insights into the transformative potential of AI in education, highlighting both its opportunities and challenges. While AI offers significant potential for personalizing learning, improving assessment, and supporting teachers, it is crucial to address ethical concerns and ensure equitable access to AI-powered educational tools. Ongoing research and interdisciplinary collaborations are vital to harness the full potential of AI while mitigating its risks. The conference served as a powerful catalyst for dialogue and collaboration, fostering a shared commitment to responsibly shaping the future of education through AI.


FAQs



1. What are the major benefits of using AI in education? AI can personalize learning, provide targeted feedback, automate assessment, and support teachers, leading to improved student outcomes.

2. What are the ethical concerns surrounding AI in education? Concerns include data privacy, algorithmic bias, and the potential for exacerbating existing inequalities.

3. How can educators prepare for the integration of AI in education? Through professional development programs focused on AI literacy and effective integration strategies.

4. What is the role of policymakers in the development and implementation of AI in education? Policymakers need to establish ethical guidelines, ensure equitable access, and support research and development in this area.

5. What are the limitations of current AI technologies in education? Current AI systems may lack the nuanced understanding of human learning and may not fully account for individual differences in learning styles and needs.

6. How can we ensure that AI benefits all students equitably? By addressing the digital divide, mitigating algorithmic bias, and ensuring culturally relevant AI applications.

7. What is the future of AI in education? AI is likely to become increasingly integrated into all aspects of education, transforming teaching, learning, and assessment.

8. What are the key takeaways from recent AI and education conferences? The importance of ethical considerations, personalized learning, teacher support, and ongoing research.

9. Where can I find more information about AI in education? Through reputable research institutions, educational technology organizations, and professional journals.


Related Articles



1. "The Impact of AI on Personalized Learning: A Meta-Analysis": This article presents a comprehensive review of research on the effectiveness of AI-powered personalized learning platforms.

2. "Ethical Frameworks for AI in Education: A Comparative Study": This article explores different ethical frameworks for guiding the responsible development and implementation of AI in education.

3. "AI-Powered Assessment Tools: A Review of Current Technologies and Future Trends": This article provides an overview of existing AI-powered assessment tools and explores future directions for AI in assessment.

4. "Teacher Perceptions and Attitudes Towards AI in Education: A Qualitative Study": This article explores teachers' perspectives on the use of AI in education and identifies factors influencing their adoption of AI tools.

5. "Addressing Algorithmic Bias in AI-Powered Educational Systems": This article discusses the issue of algorithmic bias in AI educational systems and proposes methods for mitigating bias.

6. "The Role of AI in Supporting Students with Learning Disabilities": This article explores the potential of AI to personalize learning for students with diverse learning needs.

7. "AI and the Future of Teacher Professional Development": This article explores how AI can transform teacher professional development and enhance teacher capabilities.

8. "Data Privacy and Security in AI-Powered Educational Platforms": This article discusses the importance of data privacy and security in AI-powered educational platforms and proposes strategies for ensuring data protection.

9. "The Economic Impact of AI in Education: A Cost-Benefit Analysis": This article examines the economic implications of widespread AI adoption in the education sector, considering both costs and benefits.


  ai and education conference: Artificial Intelligence in Education Carolyn Penstein Rosé, Roberto Martínez-Maldonado, H. Ulrich Hoppe, Rose Luckin, Manolis Mavrikis, Kaska Porayska-Pomsta, Bruce McLaren, Benedict du Boulay, 2018-06-20 This two volume set LNAI 10947 and LNAI 10948 constitutes the proceedings of the 19th International Conference on Artificial Intelligence in Education, AIED 2018, held in London, UK, in June 2018.The 45 full papers presented in this book together with 76 poster papers, 11 young researchers tracks, 14 industry papers and 10 workshop papers were carefully reviewed and selected from 192 submissions. The conference provides opportunities for the cross-fertilization of approaches, techniques and ideas from the many fields that comprise AIED, including computer science, cognitive and learning sciences, education, game design, psychology, sociology, linguistics as well as many domain-specific areas.
  ai and education conference: Artificial Intelligence in Education Carolyn Penstein Rosé, Roberto Martínez-Maldonado, H. Ulrich Hoppe, Rose Luckin, Manolis Mavrikis, Kaska Porayska-Pomsta, Bruce McLaren, Benedict du Boulay, 2018-06-20 This two volume set LNAI 10947 and LNAI 10948 constitutes the proceedings of the 19th International Conference on Artificial Intelligence in Education, AIED 2018, held in London, UK, in June 2018.The 45 full papers presented in this book together with 76 poster papers, 11 young researchers tracks, 14 industry papers and 10 workshop papers were carefully reviewed and selected from 192 submissions. The conference provides opportunities for the cross-fertilization of approaches, techniques and ideas from the many fields that comprise AIED, including computer science, cognitive and learning sciences, education, game design, psychology, sociology, linguistics as well as many domain-specific areas.
  ai and education conference: Artificial Intelligence and Machine Learning Bart Bogaerts, Gianluca Bontempi, Pierre Geurts, Nick Harley, Bertrand Lebichot, Tom Lenaerts, Gilles Louppe, 2021-01-04 This book contains a selection of the best papers of the 31st Benelux Conference on Artificial Intelligence, BNAIC 2019, and 28th Belgian Dutch Machine Learning Conference, BENELEARN 2019, held in Brussels, Belgium in November 2019. The 11 papers presented in this volume were carefully reviewed and selected from 50 regular submissions. They address various aspects of artificial intelligence such as natural language processing, agent technology, game theory, problem solving, machine learning, human-agent interaction, AI and education, and data analysis.
  ai and education conference: 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 and education conference: The Economics of Artificial Intelligence Ajay Agrawal, Joshua Gans, Avi Goldfarb, Catherine Tucker, 2024-03-05 A timely investigation of the potential economic effects, both realized and unrealized, of artificial intelligence within the United States healthcare system. In sweeping conversations about the impact of artificial intelligence on many sectors of the economy, healthcare has received relatively little attention. Yet it seems unlikely that an industry that represents nearly one-fifth of the economy could escape the efficiency and cost-driven disruptions of AI. The Economics of Artificial Intelligence: Health Care Challenges brings together contributions from health economists, physicians, philosophers, and scholars in law, public health, and machine learning to identify the primary barriers to entry of AI in the healthcare sector. Across original papers and in wide-ranging responses, the contributors analyze barriers of four types: incentives, management, data availability, and regulation. They also suggest that AI has the potential to improve outcomes and lower costs. Understanding both the benefits of and barriers to AI adoption is essential for designing policies that will affect the evolution of the healthcare system.
  ai and education conference: Artificial Intelligence in Education Ig Ibert Bittencourt, Mutlu Cukurova, Kasia Muldner, Rose Luckin, Eva Millán, 2020-07-04 This two-volume set LNAI 12163 and 12164 constitutes the refereed proceedings of the 21th International Conference on Artificial Intelligence in Education, AIED 2020, held in Ifrane, Morocco, in July 2020.* The 49 full papers presented together with 66 short, 4 industry & innovation, 4 doctoral consortium, and 4 workshop papers were carefully reviewed and selected from 214 submissions. The conference provides opportunities for the cross-fertilization of approaches, techniques and ideas from the many fields that comprise AIED, including computer science, cognitive and learning sciences, education, game design, psychology, sociology, linguistics as well as many domain-specific areas. ​*The conference was held virtually due to the COVID-19 pandemic.
  ai and education conference: Artificial Intelligence in Education Ning Wang, Genaro Rebolledo-Mendez, Noboru Matsuda, Olga C. Santos, Vania Dimitrova, 2023-06-25 This book constitutes the refereed proceedings of the 24th International Conference on Artificial Intelligence in Education, AIED 2023, held in Tokyo, Japan, during July 3-7, 2023. This event took place in hybrid mode. The 53 full papers and 26 short papers presented in this book were carefully reviewed and selected from 311 submissions. The papers present result in high-quality research on intelligent systems and the cognitive sciences for the improvement and advancement of education. The conference was hosted by the prestigious International Artificial Intelligence in Education Society, a global association of researchers and academics specializing in the many fields that comprise AIED, including, but not limited to, computer science, learning sciences, and education.
  ai and education conference: Lee Kuan Yew School of Public Policy Kishore Mahbubani, 2013 In an industry of higher education that measures the longevity of its leading institutions in decades and centuries, the establishment and rapid growth of the eight-year-old Lee Kuan Yew School of Public Policy (LKY School), National University of Singapore, is a remarkable story that deserves to be told. The five co-authors, all of whom were involved in guiding the School during its formative years, provide unique perspectives of key events and the thinking behind major decisions that helped place the School on its current trajectory. They also provide insights into the challenges faced along the way as well as their own motivations in becoming part of this enterprise. Finally, each author provides his or her own thoughts as to the challenges and opportunities that could emerge for the LKY School in years to come.Read the chapters authored by dynamic, key founding and management personnel of the LKY School and discover for yourselves: the relevance of an Asian policy school what will make the LKY School''s curriculum OC one of the most innovativeOCO what sets global policy studies apart from all other academic disciplines why executive education at the LKY School is one of the largest in the world why the LKY School is the third best-endowed policy school in the world a view of high-profile participating OC student officialsOC
  ai and education conference: 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 and education conference: 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 and education conference: Artificial Intelligence in Education Andrew M. Olney,
  ai and education conference: Artificial Intelligence in Education Ido Roll, Danielle McNamara, Sergey Sosnovsky, Rose Luckin, Vania Dimitrova, 2021-06-11 This two-volume set LNAI 12748 and 12749 constitutes the refereed proceedings of the 22nd International Conference on Artificial Intelligence in Education, AIED 2021, held in Utrecht, The Netherlands, in June 2021.* The 40 full papers presented together with 76 short papers, 2 panels papers, 4 industry papers, 4 doctoral consortium, and 6 workshop papers were carefully reviewed and selected from 209 submissions. The conference provides opportunities for the cross-fertilization of approaches, techniques and ideas from the many fields that comprise AIED, including computer science, cognitive and learning sciences, education, game design, psychology, sociology, linguistics as well as many domain-specific areas. ​*The conference was held virtually due to the COVID-19 pandemic.
  ai and education conference: OECD Digital Education Outlook 2021 Pushing the Frontiers with Artificial Intelligence, Blockchain and Robots OECD, 2021-06-08 How might digital technology and notably smart technologies based on artificial intelligence (AI), learning analytics, robotics, and others transform education? This book explores such question. It focuses on how smart technologies currently change education in the classroom and the management of educational organisations and systems.
  ai and education conference: Artificial Intelligence for Education Mario Allegra, Manuel Gentile, Giuseppe Città, Frank Dignum, Iza Marfisi-Schottman, 2023-11-27 What learning, teaching, and education will be in the next future is an open question. Nevertheless, believing that an increasing prevalence of AI may not influence the education field seems objectively unlikely. In recent years, the new renaissance of AI has stimulated discussion on how advances in AI can influence the educational sector and the future educational policies and the impact of AI on Technology-Enhanced Learning (TEL). On the other side, the attention of the education sector in artificial intelligence is complemented by the consideration that, since the early days of AI, researchers have shown for the education sector, which has often seen education as one of the preferred application areas. The interaction between the AI and TEL research fields led to the investigation of how the advance in AI could support the development of flexible, inclusive, personalized, engaging, and effective learning tools. Besides, research in this area could be a powerful tool to open the learning black box by providing a deeper understanding of how learning occurs. The proposed Research Topic aims to gather contributions that provide a comprehensive picture of how AI is changing educational practices and how the key stakeholders in the educational community (i.e., students, teachers, faculty, and families) perceive this ongoing change. Relevant topics include (but are not limited to): ● AI applications in real-world educational settings ● Intelligent Tutoring Systems ● Adaptive learning environments ● Learning design and AI ● Students profiling: definition of the student model and ethical implications ● Intelligent techniques for objective and integrated students evaluation in TEL ● Teachers' competencies for effective integration of AI into Education ● Teachers’ perceptions of AI: prejudices and attitudes ● The role of cognitive architectures in Education ● Serious games and AI ● Social robotics in Education
  ai and education conference: KI 2020: Advances in Artificial Intelligence Ute Schmid, Franziska Klügl, Diedrich Wolter, 2020-09-08 This book constitutes the refereed proceedings of the 43rd German Conference on Artificial Intelligence, KI 2020, held in Bamberg, Germany, in September 2020. The 16 full and 12 short papers presented together with 6 extended abstracts in this volume were carefully reviewed and selected from 62 submissions. As well-established annual conference series KI is dedicated to research on theory and applications across all methods and topic areas of AI research. KI 2020 had a special focus on human-centered AI with highlights on AI and education and explainable machine learning. Due to the Corona pandemic KI 2020 was held as a virtual event.
  ai and education conference: National Educational Technology Standards for Students International Society for Technology in Education, 2007 This booklet includes the full text of the ISTE Standards for Students, along with the Essential Conditions, profiles and scenarios.
  ai and education conference: Artificial Intelligence in Education Seiji Isotani, Eva Millán, Amy Ogan, Peter Hastings, Bruce McLaren, Rose Luckin, 2019-06-20 This two-volume set LNCS 11625 and 11626 constitutes the refereed proceedings of the 20th International Conference on Artificial Intelligence in Education, AIED 2019, held in Chicago, IL, USA, in June 2019. The 45 full papers presented together with 41 short, 10 doctoral consortium, 6 industry, and 10 workshop papers were carefully reviewed and selected from 177 submissions. AIED 2019 solicits empirical and theoretical papers particularly in the following lines of research and application: Intelligent and interactive technologies in an educational context; Modelling and representation; Models of teaching and learning; Learning contexts and informal learning; Evaluation; Innovative applications; Intelligent techniques to support disadvantaged schools and students, inequity and inequality in education.​
  ai and education conference: Artificial Intelligence in Education Maria Mercedes Rodrigo, Noburu Matsuda, Alexandra I. Cristea, Vania Dimitrova, 2022-07-26 This two-volume set LNAI 13355 and 13356 constitutes the refereed proceedings of the 23rd International Conference on Artificial Intelligence in Education, AIED 2022, held in Durham, UK, in July 2022. The 40 full papers and 40 short papers presented together with 2 keynotes, 6 industry papers, 12 DC papers, 6 Workshop papers, 10 Practitioner papers, 97 Posters and Late-Breaking Results were carefully reviewed and selected from 243 submissions. The conference presents topics such as intelligent systems and the cognitive sciences for the improvement and advancement of education, the science and engineering of intelligent interactive learning systems. The theme for the AIED 2022 conference was „AI in Education: Bridging the gap between academia, business, and non-pro t in preparing future-proof generations towards ubiquitous AI.
  ai and education conference: 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 and education conference: Artificial Intelligence in Education V. Dimitrova, R. Mizoguchi, B. du Boulay, 2009-06-25 This publication covers papers presented at AIED2009, part of an ongoing series of biennial international conferences for top quality research in intelligent systems and cognitive science for educational computing applications. The conference provides opportunities for the cross-fertilization of techniques from many fields that make up this interdisciplinary research area, including: artificial intelligence, computer science, cognitive and learning sciences, education, educational technology, psychology, philosophy, sociology, anthropology, linguistics, and the many domain-specific areas for which AIED systems have been designed and evaluated. AIED2009 focuses on the theme Building learning systems that care: from knowledge representation to affective modelling. The key research question is how to tackle the complex issues related to building learning systems that care, ranging from representing knowledge and context to modelling social, cognitive, metacognitive, and affective dimensions. This requires multidisciplinary research that links theory and technology from artificial intelligence, cognitive science, and computer science with theory and practice from education and the social sciences.
  ai and education conference: Artificial Intelligence in Education Matthew N.O. Sadiku, Sarhan M. Musa, Uwakwe C. Chukwu, 2022-01-27 The quest for building an artificial brain developed in the fields of computer science and psychology. Artificial intelligence (AI), sometimes called machine intelligence, refers to intelligence demonstrated by machines, while the natural intelligence is the intelligence displayed by humans and animals. Typically, AI systems demonstrate at least some of the following human behaviors: planning, learning, reasoning, problem solving, knowledge representation, perception, speech recognition, decision-making, language translation, motion, manipulation, intelligence, and creativity. Artificial intelligence is an emerging technology which the educational sector can benefit from. In this book, we consider the applications of AI in key areas of education. Artificial intelligence in education (AIED) refers to the application of AI technologies in educational settings to facilitate teaching, learning, or decision making. AI will impact the education field in the areas of administration, instruction, and personalized, and individualized learning applications. In this book, AI is specifically applied in the following key educational sectors: education, natural sciences, social sciences, computer science, engineering, business, and medicine.
  ai and education conference: 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 and education conference: Artificial Intelligence in Education Ido Roll, Danielle McNamara, Sergey Sosnovsky, Rose Luckin, Vania Dimitrova, 2021-06-10 This two-volume set LNAI 12748 and 12749 constitutes the refereed proceedings of the 22nd International Conference on Artificial Intelligence in Education, AIED 2021, held in Utrecht, The Netherlands, in June 2021.* The 40 full papers presented together with 76 short papers, 2 panels papers, 4 industry papers, 4 doctoral consortium, and 6 workshop papers were carefully reviewed and selected from 209 submissions. The conference provides opportunities for the cross-fertilization of approaches, techniques and ideas from the many fields that comprise AIED, including computer science, cognitive and learning sciences, education, game design, psychology, sociology, linguistics as well as many domain-specific areas. ​*The conference was held virtually due to the COVID-19 pandemic.
  ai and education conference: 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 and education conference: Artificial Intelligence in Education C.-K. Looi, G. McCalla, B. Bredeweg, 2005-07-14 The field of Artificial Intelligence in Education has continued to broaden and now includes research and researchers from many areas of technology and social science. This study opens opportunities for the cross-fertilization of information and ideas from researchers in the many fields that make up this interdisciplinary research area, including artificial intelligence, other areas of computer science, cognitive science, education, learning sciences, educational technology, psychology, philosophy, sociology, anthropology, linguistics, and the many domain-specific areas for which Artificial Intelligence in Education systems have been designed and built. An explicit goal is to appeal to those researchers who share the perspective that true progress in learning technology requires both deep insight into technology and also deep insight into learners, learning, and the context of learning. The theme reflects this basic duality.
  ai and education conference: ARTIFICIAL INTELLIGENCE IN EDUCATION: REVOLUTIONIZING LEARNING AND TEACHING Prof. (Dr.) Mita Banerjee, Prof. (Dr.) Sridipa Sinha, Dr. Pranay Pandey, 2024-08-25
  ai and education conference: Innovations in Learning and Technology for the Workplace and Higher Education David Guralnick, Michael E. Auer, Antonella Poce, 2021-11-12 This book covers the topics such as online learning methodologies, case studies, new technologies in learning (such as virtual reality, augmented reality, holograms, and artificial intelligence), adaptive learning, and project-based learning. New technologies provide us with new opportunities to create new learning experiences, leveraging research from a variety of disciplines along with imagination and creativity. The Learning Ideas Conference was created to bring researchers, practitioners, and others together to discuss, innovate, and create. The Learning Ideas Conference 2021 was the 14th annual conference and the first under its new name (following on its predecessors, the International Conference on E-Learning in the Workplace and the International Conference on Interactive Collaborative and Blended Learning). The conference was held online from June 14-18, 2021, and included two special tracks: The ALICE (Adaptive Learning via Interactive, Collaborative and Emotional Approaches) Special Track and a track entitled Building a University of Tomorrow, from the Xi'an Jiaotong-Liverpool University (XJTLU) in China. The papers included in this book may be of interest to researchers in pedagogy and learning theory, university faculty members and administrators, learning and development specialists, user experience designers, and others.
  ai and education conference: ECIAIR 2019 European Conference on the Impact of Artificial Intelligence and Robotics   Dr Paul Griffiths , Dr. Mitt Nowshade Kabir , 2019-10-31
  ai and education conference: Artificial Intelligence and Education - Shaping the Future of Learning , 2024-10-02 The book discusses the impact of artificial intelligence (AI) on education, exploring both the opportunities and challenges it brings. It aims to provide a comprehensive understanding of how AI is reshaping the educational environment, from personalized learning experiences and intelligent tutoring systems to administrative efficiencies and ethical considerations. The book also addresses the implications of AI on traditional educational models and the broader societal context, sparking a dialogue about AI’s potential for enhancing learning outcomes and preparing students for an AI-driven world. Overall, it aims to inspire innovation and critical thinking in the field of education.
  ai and education conference: Artificial Intelligence in Education. Posters and Late Breaking Results, Workshops and Tutorials, Industry and Innovation Tracks, Practitioners, Doctoral Consortium and Blue Sky Ning Wang, Genaro Rebolledo-Mendez, Vania Dimitrova, Noboru Matsuda, Olga C. Santos, 2023-06-29 This volume constitutes poster papers and late breaking results presented during the 24th International Conference on Artificial Intelligence in Education, AIED 2023, Tokyo, Japan, July 3–7, 2023. The 65 poster papers presented were carefully reviewed and selected from 311 submissions. This set of posters was complemented with the other poster contributions submitted for the Poster and Late Breaking results track of the AIED 2023 conference.
  ai and education conference: The ABCs of How We Learn: 26 Scientifically Proven Approaches, How They Work, and When to Use Them Daniel L. Schwartz, Jessica M. Tsang, Kristen P. Blair, 2016-07-26 Selected as one of NPR's Best Books of 2016, this book offers superior learning tools for teachers and students, from A to Z. An explosive growth in research on how people learn has revealed many ways to improve teaching and catalyze learning at all ages. The purpose of this book is to present this new science of learning so that educators can creatively translate the science into exceptional practice. The book is highly appropriate for the preparation and professional development of teachers and college faculty, but also parents, trainers, instructional designers, psychology students, and simply curious folks interested in improving their own learning. Based on a popular Stanford University course, The ABCs of How We Learn uses a novel format that is suitable as both a textbook and a popular read. With everyday language, engaging examples, a sense of humor, and solid evidence, it describes 26 unique ways that students learn. Each chapter offers a concise and approachable breakdown of one way people learn, how it works, how we know it works, how and when to use it, and what mistakes to avoid. The book presents learning research in a way that educators can creatively translate into exceptional lessons and classroom practice. The book covers field-defining learning theories ranging from behaviorism (R is for Reward) to cognitive psychology (S is for Self-Explanation) to social psychology (O is for Observation). The chapters also introduce lesser-known theories exceptionally relevant to practice, such as arousal theory (X is for eXcitement). Together the theories, evidence, and strategies from each chapter can be combined endlessly to create original and effective learning plans and the means to know if they succeed.
  ai and education conference: Teaching Naked José Antonio Bowen, 2012-07-03 You've heard about flipping your classroom—now find out how to do it! Introducing a new way to think about higher education, learning, and technology that prioritizes the benefits of the human dimension. José Bowen recognizes that technology is profoundly changing education and that if students are going to continue to pay enormous sums for campus classes, colleges will need to provide more than what can be found online and maximize naked face-to-face contact with faculty. Here, he illustrates how technology is most powerfully used outside the classroom, and, when used effectively, how it can ensure that students arrive to class more prepared for meaningful interaction with faculty. Bowen offers practical advice for faculty and administrators on how to engage students with new technology while restructuring classes into more active learning environments.
  ai and education conference: Artificial Intelligence in Education Elisabeth André, Ryan Baker, Xiangen Hu, Ma. Mercedes T. Rodrigo, Benedict du Boulay, 2017-06-22 This book constitutes the refereed proceedings of the 18th International Conference on Artificial Intelligence in Education, AIED 2017, held in Wuhan, China, in June/July 2017. The 36 revised full papers presented together with 4 keynotes, 37 poster, presentations, 4 doctoral consortium papers, 5 industry papers, 4 workshop abstracts, and 2 tutorial abstracts were carefully reviewed and selected from 159 submissions. The conference provides opportunities for the cross-fertilization of approaches, techniques and ideas from the many fields that comprise AIED, including computer science, cognitive and learning sciences, education, game design, psychology, sociology, linguistics as well as many domain-specific areas.
  ai and education conference: Artificial Intelligence and Games Georgios N. Yannakakis, Julian Togelius, 2018-02-17 This is the first textbook dedicated to explaining how artificial intelligence (AI) techniques can be used in and for games. After introductory chapters that explain the background and key techniques in AI and games, the authors explain how to use AI to play games, to generate content for games and to model players. The book will be suitable for undergraduate and graduate courses in games, artificial intelligence, design, human-computer interaction, and computational intelligence, and also for self-study by industrial game developers and practitioners. The authors have developed a website (http://www.gameaibook.org) that complements the material covered in the book with up-to-date exercises, lecture slides and reading.
  ai and education conference: Artificial Intelligence in Education Technologies: New Development and Innovative Practices Tim Schlippe, Eric C. K. Cheng, Tianchong Wang, 2023-11-08 This book is a collection of selected research papers presented at the 2023 4th International Conference on Artificial Intelligence in Education Technology (AIET 2023), held in Berlin, Germany, on June 30 - July 2, 2023. AIET establishes a platform for AI in education researchers to present research, exchange innovative ideas, propose new models, as well as demonstrate advanced methodologies and novel systems. It is a timely and up-to-date publication responsive to the rapid development of AI technologies, practices and their increasingly complex interplay with the education domain. It promotes the cross-fertilisation of knowledge and ideas from researchers in various fields to construct the interdisciplinary research area of AI in Education. These subject areas include computer science, cognitive science, education, learning sciences, educational technology, psychology, philosophy, sociology, anthropology and linguistics. The feature of this book will contribute from diverse perspectives to form a dynamic picture of AI in Education. It also includes various domain-specific areas for which AI and other education technology systems have been designed or used in an attempt to address challenges and transform educational practice. This timely publication is in line with UNESCO’s Beijing Consensus on Artificial Intelligence and Education. It is committed to exploring how AI may play a role in bringing more innovative practices, transforming education, and triggering an exponential leap towards the achievement of the Education 2030 Agenda. Providing broad coverage of recent technology-driven advances and addressing a number of learning-centric themes, the book is an informative and useful resource for researchers, practitioners, education leaders and policy-makers who are involved or interested in AI and education.
  ai and education conference: Human Interaction, Emerging Technologies and Future Systems V Tareq Ahram, Redha Taiar, 2021-09-09 This book reports on research and developments in human–technology interaction. A special emphasis is given to human–computer interaction and its implementation for a wide range of purposes such as health care, aerospace, telecommunication, and education, among others. The human aspects are analyzed in detail. Timely studies on human-centered design, wearable technologies, social and affective computing, augmented, virtual and mixed reality simulation, human rehabilitation, and biomechanics represent the core of the book. Emerging technology applications in business, security, and infrastructure are also critically examined, thus offering a timely, scientifically grounded, but also professionally oriented snapshot of the current state of the field. The book gathers contributions presented at the 5th International Conference on Human Interaction and Emerging Technologies (IHIET 2021, August 27–29, 2021) and the 6th International Conference on Human Interaction and Emerging Technologies: Future Systems (IHIET-FS 2021, October 28–30, 2021), held virtually from France. It offers a timely survey and a practice-oriented reference guide to researchers and professionals dealing with design, systems engineering, and management of the next-generation technology and service systems.
  ai and education conference: Artificial Intelligence in Education and Teaching Assessment Wei Wang, Guangming Wang, Xiaoming Ding, Baoju Zhang, 2022-01-01 This book collects papers on education quality assessment based on AI technology and introduces the latest research direction and progress of AI technology in the field of education and teaching, including classroom teaching quality assessment, online education quality assessment, teaching reflection quality assessment, etc. This book promotes the application of artificial intelligence technology in the field of education and teaching, effectively improving the quality of education and teaching. Researchers in artificial intelligence technology, teachers, students, and others benefit from this book.
  ai and education conference: Artificial Intelligence and Education Dick Bierman, Joost Breuker, Jacobijn Sandberg, 1989
  ai and education conference: EDUCCON 2020 Empower Teaching Studies Mehmet Tekerek, 2020-12-30 In 2020, EDUCCON helded as a virtual conference with the theme Empowering Teaching. EDUCCON 2020 to energize and inspire the scientists and teachers whose job is to teach in new-normal. In the digital age, in terms of empowering teaching, it is aimed to address the points of discovery for success in teaching, evidence-based teaching, higher education and education in a life called “new normal” after COVID 19. Teaching in the digital age focuses on leading pedagogy and identifying educational technology tools that will help students achieve learning outcomes. The presence of teachers and humanization of the learning experience in distance and online learning environments will be included. In evidence-based education; the focus is on teaching and learning literature to explore the theory and practical applications of teaching strategies in courses. Presentations of studies that can demonstrate the development of a teaching philosophy and then how to apply evidence-based teaching in lessons will be presented. Conscious design of course content and evaluation is at the top of everything in higher education. The foundations of university education include the work for teaching staff at the center of higher education who have not received teacher training. It consists of studies about who the students are and how to help them be successful in the lessons. In addition, EDUCCON 2020 aims to discuss the basic elements for successful education a life called “new normal” after COVID 19 and to present studies that empower learning. The EDUCCON 2020 conference program consists of paper presentations and training sessions.
  ai and education conference: Artificial Intelligence in Education Seiji Isotani, Eva Millán, Amy Ogan, Peter Hastings, Bruce McLaren, Rose Luckin, 2019-06-20 This two-volume set LNCS 11625 and 11626 constitutes the refereed proceedings of the 20th International Conference on Artificial Intelligence in Education, AIED 2019, held in Chicago, IL, USA, in June 2019. The 45 full papers presented together with 41 short, 10 doctoral consortium, 6 industry, and 10 workshop papers were carefully reviewed and selected from 177 submissions. AIED 2019 solicits empirical and theoretical papers particularly in the following lines of research and application: Intelligent and interactive technologies in an educational context; Modelling and representation; Models of teaching and learning; Learning contexts and informal learning; Evaluation; Innovative applications; Intelligent techniques to support disadvantaged schools and students, inequity and inequality in education.​
OpenAI
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ISO - What is artificial intelligence (AI)?
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May 21, 2025 · ChatGPT for business just got better—with connectors to internal tools, MCP support, record mode & SSO to Team, and flexible pricing for Enterprise. We believe our …

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What is AI, and how does it enable machines to perform tasks requiring human intelligence, like speech recognition and decision-making? AI learns and adapts through new data, integrating …

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Artificial intelligence (AI) is the capability of computational systems to perform tasks typically associated with human intelligence, such as learning, reasoning, problem-solving, perception, …

ISO - What is artificial intelligence (AI)?
AI spans a wide spectrum of capabilities, but essentially, it falls into two broad categories: weak AI and strong AI. Weak AI, often referred to as artificial narrow intelligence (ANI) or narrow AI, …

Artificial intelligence (AI) | Definition, Examples, Types ...
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May 23, 2025 · Artificial intelligence (AI) is the theory and development of computer systems capable of performing tasks that historically required human intelligence, such as recognizing …

What is artificial intelligence (AI)? - IBM
Artificial intelligence (AI) is technology that enables computers and machines to simulate human learning, comprehension, problem solving, decision-making, creativity and autonomy.

What is Artificial Intelligence (AI)? - GeeksforGeeks
Apr 22, 2025 · Narrow AI (Weak AI): This type of AI is designed to perform a specific task or a narrow set of tasks, such as voice assistants or recommendation systems. It excels in one …

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