Artificial Intelligence for Technology Enhanced Learning

The integration of Artificial Intelligence (AI) in Technology-Enhanced Learning (TEL) has transformed education through personalized learning, intelligent tutoring systems, automated assessment, and adaptive mobile learning. It also supports educators and instructional designers by analyzing learner data to improve content and pedagogy. Furthermore, AI enhances gamification and game-based learning by personalizing challenges and feedback, increasing student engagement and skill development. As AI advances, it continues to shape TEL into a more adaptive, inclusive, and intelligent educational ecosystem.

This Research Topic aims to explore and critically examine the transformative role of AI in TEL. As AI continues to evolve and integrate deeply into educational contexts, it presents new opportunities and challenges for learners, educators, and instructional designers alike. The article collection seeks to showcase innovative research, theoretical perspectives, and practical applications that highlight how AI-driven technologies—such as personalized learning systems, intelligent tutoring, adaptive mobile platforms, learning analytics, and gamified learning environments—are reshaping pedagogical practices and learning experiences. By bringing together interdisciplinary contributions, this Research Topic aspires to deepen understanding of AI’s potential to enhance engagement, accessibility, and learning outcomes, while also addressing ethical, technical, and pedagogical implications. Ultimately, the goal is to advance the discourse on how AI can be harnessed to create more intelligent, inclusive, and data-informed educational ecosystems.

This Research Topic seeks high-quality research articles, case studies, and review papers that explore how AI technologies can enhance teaching and learning processes across different educational contexts. We welcome contributions that address, but are not limited to, the following topics:
- AI-driven personalized learning environments
- Intelligent tutoring systems
- Recommender systems for education
- AI-driven game-based learning
- Challenges and deployment models for LLMs in mobile learning
- AI-based pervasive learning environments
- Adaptive assessment and feedback mechanisms
- Natural Language Processing (NLP) in educational contexts
- Learning analytics and educational data mining
- AI for collaborative and social learning
- AI in informal and lifelong learning settings
- Human-AI collaboration in educational design
- AI-enhanced augmented and virtual reality in learning
- Adaptive HCI/UX and generative AI for TEL
- Case studies and practical implementations of AI-based TEL systems
- Ethical considerations and fairness of AI in education

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Community Case Study
• Conceptual Analysis
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• FAIR² Data
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Case Report
• Clinical Trial
• Community Case Study
• Conceptual Analysis
• Curriculum, Instruction, and Pedagogy
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Registered Report
• Review
• Study Protocol
• Systematic Review
• Technology and Code

Keywords: technology enhanced leaning (TEL), intelligent tutoring systems (ITSs), artificial intelligence, generative AI (GenAI), deep learning (DL), large language models (LLMs)

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