Advances in Intelligent Learning Systems
A special issue of Future Internet (ISSN 1999-5903). This special issue belongs to the section "Smart System Infrastructure and Applications".
Deadline for manuscript submissions: 1 April 2027 | Viewed by 185
Editors
Interests: internet of things (IoT); smart cities; autonomous technologies; smart healthcare; artificial intelligence; computer visions; generative AI
Special Issue Information
Dear Colleagues,
The intelligent learning landscape is transforming how we learn and deliver knowledge across domains, including education, healthcare, manufacturing, and professional training. On the other hand, considerable advances have been made in artificial intelligence (AI) today, particularly in deep learning, natural language processing, computer vision, generative AI, and large language models (LLMs), enabling the development of adaptive, personalized, context-aware, and data-driven learning environments. Furthermore, today's knowledge comes from diverse sources, not just textbooks but also text, images, graphics, audio, and video. Processing these diverse sources in ways that support and benefit learning is possible with AI, which can process and understand multimodal complex data.
This Special Issue focuses on recent advances in intelligent learning systems across domains. It welcomes critical reviews, original research articles based on algorithms, frameworks, case studies, and real-world applications that leverage AI and emerging digital technologies. Contributions may address (but are not limited to) the following intelligent learning systems in diverse domains: education, online learning, healthcare education, industrial training, engineering education, business learning, smart classrooms, and professional development.
Scope for the Special Issue includes, but is not limited to, the following:
- AI systems for personalized learning and feedback.
- Generative AI and LLMs for content, Q&A, and summarization.
- ML/DL for performance, engagement, and dropout prediction.
- Smart classrooms via IoT, cloud, and edge AI.
- Computer vision and multimodal AI in learning.
- Simulation and skill-based training across domains.
- NLP for language learning, writing support, and chatbots.
- Human-centered learning via engagement, emotion, and accessibility.
- AI teaching assistants for individuals with special needs.
- AI for learner emotion and stress detection.
- AR/VR for learning and skill development.
- Explainable, fair, and privacy-preserving AI in education.
- Bias detection and mitigation in educational AI.
- Case studies of intelligent learning systems.
Dr. Furqan Alam
Dr. Saqib Qamar
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Future Internet is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- eLearning
- LLMs
- generative AI
- natural language processing (NLP)
- personalized learning
- human-centered learning
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