In the field of education, there is a growing interest in the use of Generative Artificial Intelligence to reshape the educational landscape. Led by our esteemed Associate Editors (Dr. Zapata-Rivera & Prof. Torre) and Review Editors (Profs. Lee, Sarasa-Cabezuelo & Libbrecht & Dr. Ghergulescu), this editorial initiative aims to investigate the transformative potential of Generative AI in various aspects of education.
By leveraging machine learning models, these intelligent systems extract useful insights from vast amounts of data, making them capable of delivering highly individualized content. They can analyze a learner's proficiency level, learning style, and pace, and then tailor the study material accordingly. Whether a learner prefers visual aids, textual content, or interactive modules, Generative AI can adapt its content generation strategies to meet distinct preferences and learners’ needs. This ensures an elevated engagement level and enhanced comprehension, highlighting its potential to transform traditional teaching methodologies.
This Research Topic also explores the use of Generative AI as a smart tutor, capable of tailoring instructions and feedback dynamically based on each learner's progress. Acting as an ever-present mentor, Generative AI can offer learning aids beyond class hours, facilitating continuous learning and immediate doubt clarification. This can be crucial for learners encountering obstacles outside the typical school hours or during self-study periods. Whether a student is a visual, auditory, reading-writing, or kinesthetic learner, AI tutors can incorporate suitable strategies, from offering explainer videos and interactive simulations to providing additional reading materials or hands-on exercises.
The goal of this Research Topic is to shed light on the latest discoveries, new insights, novel developments, and future challenges in this advancing field. Topics of interest include but are not limited to:
• Prompting engineering for education
• Proposals for including Generative AI in the teaching-learning process
• Ethics of the use of Generative AI in education
• Proposals for using Generative AI for knowledge evaluation.
• Proposals for the use of Generative AI for the creation of educational content
• Scalable and valid assessment using Generative AI
• Innovative learning and assessment tasks using Generative AI
• Interpretability and explainability of Generative AI approaches in learning and assessment
• Embedded, embodied and distributed cognition
• Proposals for conversational AI tutors
• Proposals for conversational AI tutor assistants
• Proposals for using generative AI in computer science education
• Studies on how generative AI can adaptively respond to the affective needs of learners
In the field of education, there is a growing interest in the use of Generative Artificial Intelligence to reshape the educational landscape. Led by our esteemed Associate Editors (Dr. Zapata-Rivera & Prof. Torre) and Review Editors (Profs. Lee, Sarasa-Cabezuelo & Libbrecht & Dr. Ghergulescu), this editorial initiative aims to investigate the transformative potential of Generative AI in various aspects of education.
By leveraging machine learning models, these intelligent systems extract useful insights from vast amounts of data, making them capable of delivering highly individualized content. They can analyze a learner's proficiency level, learning style, and pace, and then tailor the study material accordingly. Whether a learner prefers visual aids, textual content, or interactive modules, Generative AI can adapt its content generation strategies to meet distinct preferences and learners’ needs. This ensures an elevated engagement level and enhanced comprehension, highlighting its potential to transform traditional teaching methodologies.
This Research Topic also explores the use of Generative AI as a smart tutor, capable of tailoring instructions and feedback dynamically based on each learner's progress. Acting as an ever-present mentor, Generative AI can offer learning aids beyond class hours, facilitating continuous learning and immediate doubt clarification. This can be crucial for learners encountering obstacles outside the typical school hours or during self-study periods. Whether a student is a visual, auditory, reading-writing, or kinesthetic learner, AI tutors can incorporate suitable strategies, from offering explainer videos and interactive simulations to providing additional reading materials or hands-on exercises.
The goal of this Research Topic is to shed light on the latest discoveries, new insights, novel developments, and future challenges in this advancing field. Topics of interest include but are not limited to:
• Prompting engineering for education
• Proposals for including Generative AI in the teaching-learning process
• Ethics of the use of Generative AI in education
• Proposals for using Generative AI for knowledge evaluation.
• Proposals for the use of Generative AI for the creation of educational content
• Scalable and valid assessment using Generative AI
• Innovative learning and assessment tasks using Generative AI
• Interpretability and explainability of Generative AI approaches in learning and assessment
• Embedded, embodied and distributed cognition
• Proposals for conversational AI tutors
• Proposals for conversational AI tutor assistants
• Proposals for using generative AI in computer science education
• Studies on how generative AI can adaptively respond to the affective needs of learners
