AI innovations in education: adaptive learning and beyond

The digital transformation of education requires the development of innovative artificial intelligence tools that enable personalized and adaptive learning. Despite advances such as large language models (LLM) and search assisted generation (RAG) systems that offer tailored learning experiences, there is an urgent need to address the complex interplay of emotions, motivation, personality and sociocultural factors that influence learning pathways myself. Intelligent learning systems (ITS) exemplify advances in the use of artificial intelligence to dynamically analyze and respond to individual student performance, thereby promoting enriched engagement and understanding.

The aim of this Research Topic is to highlight significant AI-based advances and methodologies in the educational sphere, focusing on their practical applications and theoretical foundations. The emphasis is on systems such as ITS and multimodal learning environments that not only adapt to the diverse needs of students, but also enrich learning through tailored feedback and content adjustments based on real-time analysis, taking into account individual student profiles, also in terms of personality, emotions and cognitive abilities. Additionally, basic research on AI’s ability to recognize and adapt to individual learning motivations will also be explored to inform future technological improvements.

To gather further information on improving educational practices with AI, please visit our articles on topics including:

● Development and effectiveness of adaptive learning systems based on artificial intelligence.
● The use of artificial intelligence in multimodal educational settings covering various types of media.
● Innovations in artificial intelligence enabling real-time assessment and feedback in educational contexts.
● Ethical considerations and implications of artificial intelligence in education.
● Applications of artificial intelligence in special education and their role in supporting inclusive learning environments.
● Predictive AI tools to identify at-risk students and improve retention rates.
● Case studies of AI-based interventions that adapt to students’ psychological and emotional needs.
● Research and theoretical contributions on the psychological factors (e.g. personality, emotions, cognitive abilities) of students and how they should be analyzed in the context of artificial intelligence in education to promote personalized learning
● Theoretical research into the potential impact of artificial intelligence on educational outcomes and processes.

For this call for papers, we are seeking contributions that combine theoretical concepts with practical implementations, thereby advancing our understanding of how artificial intelligence can be used to create more inclusive, adaptive, and engaging learning experiences.

Keywords: Artificial intelligence in education, personalized learning, adaptive learning systems, multimodal artificial intelligence, intelligent learning systems, human-AI collaboration

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they were submitted, as defined in their mission statement. Frontiers reserves the right to refer an out-of-scope manuscript to a more appropriate section or journal at any stage of review.

The digital transformation of education requires the development of innovative artificial intelligence tools that enable personalized and adaptive learning. Despite advances such as large language models (LLM) and search assisted generation (RAG) systems that offer tailored learning experiences, there is an urgent need to address the complex interplay of emotions, motivation, personality and sociocultural factors that influence learning pathways myself. Intelligent learning systems (ITS) exemplify advances in the use of artificial intelligence to dynamically analyze and respond to individual student performance, thereby promoting enriched engagement and understanding.

The aim of this Research Topic is to highlight significant AI-based advances and methodologies in the educational sphere, focusing on their practical applications and theoretical foundations. The emphasis is on systems such as ITS and multimodal learning environments that not only adapt to the diverse needs of students, but also enrich learning through tailored feedback and content adjustments based on real-time analysis, taking into account individual student profiles, also in terms of personality, emotions and cognitive abilities. Additionally, basic research on AI’s ability to recognize and adapt to individual learning motivations will also be explored to inform future technological improvements.

To gather further information on improving educational practices with AI, please visit our articles on topics including:

● Development and effectiveness of adaptive learning systems based on artificial intelligence.
● The use of artificial intelligence in multimodal educational settings covering various types of media.
● Innovations in artificial intelligence enabling real-time assessment and feedback in educational contexts.
● Ethical considerations and implications of artificial intelligence in education.
● Applications of artificial intelligence in special education and their role in supporting inclusive learning environments.
● Predictive AI tools to identify at-risk students and improve retention rates.
● Case studies of AI-based interventions that adapt to students’ psychological and emotional needs.
● Research and theoretical contributions on the psychological factors (e.g. personality, emotions, cognitive abilities) of students and how they should be analyzed in the context of artificial intelligence in education to promote personalized learning
● Theoretical research into the potential impact of artificial intelligence on educational outcomes and processes.

For this call for papers, we are seeking contributions that combine theoretical concepts with practical implementations, thereby advancing our understanding of how artificial intelligence can be used to create more inclusive, adaptive, and engaging learning experiences.

Keywords: Artificial intelligence in education, personalized learning, adaptive learning systems, multimodal artificial intelligence, intelligent learning systems, human-AI collaboration

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they were submitted, as defined in their mission statement. Frontiers reserves the right to refer an out-of-scope manuscript to a more appropriate section or journal at any stage of review.