Author:
(1) Mohammad AL-Smad, Qatar University, Qatar and (e-mail: malsmadi@qu.edu.qa). Table of Links Abstract and Introduction History of Using AI in Education Research Methodology Literature Review Summary Conclusion and References Abstract The wide adoption and usage of generative artificial intelligence (AI) models, particularly ChatGPT, has sparked a surge in research exploring their potential applications in the educational landscape. This survey examines academic literature published between November, 2022, and July, 2023, specifically targeting high-impact research from Scopus-indexed Q1 and Q2 journals. This survey delves into the practical applications and implications of generative AI models across a diverse range of educational contexts. Through a comprehensive and rigorous evaluation of recent academic literature, this survey seeks to illuminate the evolving role of generative AI models, particularly ChatGPT, in education. By shedding light on the potential benefits, challenges, and emerging trends in this dynamic field, the survey endeavors to contribute to the understanding of the nexus between artificial intelligence and education. The findings of this review will empower educators, researchers, and policymakers to make informed decisions about the integration of AI technologies into learning environments. Keywords: Artificial Intelligence, Education, ChatGPT, Generative AI, Technology-enhanced Learning. 1. Introduction Generative artificial intelligence (AI) is developing rapidly with a great potential to revolutionize education. ChatGPT, a large language model (LLM), is a particularly promising generative AI model that can be applied in education. One of the key advantages of using generative AI in education is that it can help to personalize learning (Farrokhnia et al., 2023). Generative AI models can be used to create personalized learning materials, such as practice problems, study guides, and feedback, tailored for each student (Cotton et al., 2023). This can help students learn in a way that is tailored to their individual needs and interests and at their own pace. Another advantage of using generative AI in education is that it can provide students with feedback and support outside of the classroom. For example, generative AI can be used to create chatbots that can answer students’ questions and provide them with support (Keng-Boon Ooi & Wong, 2023). Using Chatbots in education can be especially helpful for students who are struggling with learning or who need support outside of class time. Finally, generative AI can be used to automate tasks such as grading and creating reports. This can free up teachers’ time to focus on more important tasks, such as interacting with students and providing them with personalized support. While generative AI has the potential to revolutionize education, there are also some challenges that need to be addressed. One challenge is ensuring the accuracy and reliability of generated content (Glaser, 2023). Generative AI models can produce realistic but inaccurate content. It is important to develop mechanisms to ensure the accuracy and reliability of generated content, especially when it is used for educational purposes. Another challenge is addressing ethical concerns. The integration of generative AI in education raises ethical concerns and challenges, such as the potential for cheating and plagiarism, and teacher displacement (Dwivedi et al., 2023) . It is important to develop ethical guidelines for the use of generative AI in education and to educate students about these guidelines (Susarla et al., 2023). By addressing the challenges and conducting further research, we can ensure that generative AI is used to improve learning for all students. In this survey paper, we will explain the history and evolution of generative AI models and their application in education (Section 2). Moreover, we will review the current state of research on the use of generative AI and ChatGPT in education (Section 4), and provide specific examples of how ChatGPT is being used in educational settings today (Section 4.2). We will also discuss the potential benefits and challenges of using generative AI in education (Section 4.3). We will conclude by discussing the survey findings and providing recommendations for future research (Section 5, 6). This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. Author: (1) Mohammad AL-Smad, Qatar University, Qatar and (e-mail: malsmadi@qu.edu.qa). Author: Author: (1) Mohammad AL-Smad, Qatar University, Qatar and (e-mail: malsmadi@qu.edu.qa). Table of Links Abstract and Introduction Abstract and Introduction History of Using AI in Education History of Using AI in Education Research Methodology Research Methodology Literature Review Literature Review Summary Summary Conclusion and References Conclusion and References Abstract The wide adoption and usage of generative artificial intelligence (AI) models, particularly ChatGPT, has sparked a surge in research exploring their potential applications in the educational landscape. This survey examines academic literature published between November, 2022, and July, 2023, specifically targeting high-impact research from Scopus-indexed Q1 and Q2 journals. This survey delves into the practical applications and implications of generative AI models across a diverse range of educational contexts. Through a comprehensive and rigorous evaluation of recent academic literature, this survey seeks to illuminate the evolving role of generative AI models, particularly ChatGPT, in education. By shedding light on the potential benefits, challenges, and emerging trends in this dynamic field, the survey endeavors to contribute to the understanding of the nexus between artificial intelligence and education. The findings of this review will empower educators, researchers, and policymakers to make informed decisions about the integration of AI technologies into learning environments. Keywords: Artificial Intelligence, Education, ChatGPT, Generative AI, Technology-enhanced Learning. 1. Introduction Generative artificial intelligence (AI) is developing rapidly with a great potential to revolutionize education. ChatGPT, a large language model (LLM), is a particularly promising generative AI model that can be applied in education. One of the key advantages of using generative AI in education is that it can help to personalize learning (Farrokhnia et al., 2023). Generative AI models can be used to create personalized learning materials, such as practice problems, study guides, and feedback, tailored for each student (Cotton et al., 2023). This can help students learn in a way that is tailored to their individual needs and interests and at their own pace. Another advantage of using generative AI in education is that it can provide students with feedback and support outside of the classroom. For example, generative AI can be used to create chatbots that can answer students’ questions and provide them with support (Keng-Boon Ooi & Wong, 2023). Using Chatbots in education can be especially helpful for students who are struggling with learning or who need support outside of class time. Finally, generative AI can be used to automate tasks such as grading and creating reports. This can free up teachers’ time to focus on more important tasks, such as interacting with students and providing them with personalized support. While generative AI has the potential to revolutionize education, there are also some challenges that need to be addressed. One challenge is ensuring the accuracy and reliability of generated content (Glaser, 2023). Generative AI models can produce realistic but inaccurate content. It is important to develop mechanisms to ensure the accuracy and reliability of generated content, especially when it is used for educational purposes. Another challenge is addressing ethical concerns. The integration of generative AI in education raises ethical concerns and challenges, such as the potential for cheating and plagiarism, and teacher displacement (Dwivedi et al., 2023) . It is important to develop ethical guidelines for the use of generative AI in education and to educate students about these guidelines (Susarla et al., 2023). By addressing the challenges and conducting further research, we can ensure that generative AI is used to improve learning for all students. In this survey paper, we will explain the history and evolution of generative AI models and their application in education (Section 2). Moreover, we will review the current state of research on the use of generative AI and ChatGPT in education (Section 4), and provide specific examples of how ChatGPT is being used in educational settings today (Section 4.2). We will also discuss the potential benefits and challenges of using generative AI in education (Section 4.3). We will conclude by discussing the survey findings and providing recommendations for future research (Section 5, 6). This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. This paper is available on arxiv under CC BY-NC-ND 4.0 DEED license. available on arxiv

Part of HackerNoon's growing list of open-source research papers, promoting free access to academic material.

History of Using AI in Education

Out of One, Many: Using Language Models to Simulate Human Samples

EScholar Technologies

Too Long; Didn't Read

Get Free Unlimited IP Geo Data With IPinfo Lite

ChatGPT and Beyond: The Generative AI Revolution in Education

About Author

Comments

TOPICS

THIS ARTICLE WAS FEATURED IN

Related Stories

Untitled Story

5 Ways to Measure Privacy Risks in Text Data

Adopting AI in Sales and Marketing

Ai Adoption: What You Need to Know About Anomaly Detection and Unsupervised Learning

Biden Charges Federal Government Agencies to Adopt AI

Exploring the Impact of AI on the Future of Content Writing for Writers and Editors

5 Ways to Measure Privacy Risks in Text Data

Adopting AI in Sales and Marketing

Ai Adoption: What You Need to Know About Anomaly Detection and Unsupervised Learning

Biden Charges Federal Government Agencies to Adopt AI

Exploring the Impact of AI on the Future of Content Writing for Writers and Editors

Light-Mode

Classic

Newspaper

Dark-Mode

Neon Noir

Minty

HN StartUps