A comprehensive index of artificial intelligence and machine-learning research with AI-generated summaries, citation metrics, and direct links to papers and code.
Sarkar Siddique, James C. L. Chow
This topical review highlights how machine learning and AI applications in healthcare communication, including chatbots for COVID-19 education, cancer therapy, and medical imaging, can benefit humans.
Ben Williamson, Rebecca Eynon
This paper provides a critical review of AI in education, tracing its historical roots, identifying gaps in current research, and proposing future directions for more equitable and ethical AIED.
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This paper defines agentic AI in education, reviews the current state of the art, and outlines future directions for autonomous learning systems.
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This paper investigates whether small language models with retrieval-augmented generation can match or replace large language models in computer science education.
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This paper discusses the strengths and future prospects of foundation models in education, envisioning a transformative impact on the field.
J. Clusmann, F. Kolbinger, H. Muti, et al.
This paper reviews the current and future applications of large language models in medicine, discussing their potential to transform clinical practice, education, and research while highlighting challenges and limitations.
Stanislav Ivanov, Mohammad Soliman, Aarni Tuomi, et al.
This paper applies the Theory of Planned Behaviour to model how perceived benefits, risks, and TPB factors drive generative AI adoption among lecturers and students in higher education.
Di Wu, Shuling Zhang, Zhiyuan Ma, et al.
This study identifies key factors—teacher support, learning strategies, and technology acceptance—that shape undergraduate self-directed learning in generative AI-enhanced environments, mediated by self-efficacy and motivation.
Zongxi Li, Zijian Wang, Weiming Wang, et al.
A systematic survey of Retrieval-Augmented Generation (RAG) in education, covering workflow, retrievers, generation optimization, and applications.
Jakub Swacha, Michał Gracel
A survey of 47 papers on RAG chatbots in education, analyzing their character, target support, knowledge scope, LLM, and evaluation.
Xuesong Zhai, Xiaoyan Chu, Ching Sing Chai, et al.
A content analysis of 100 papers from 2010-2020 reveals how AI has been applied to education across development, application, and integration layers, identifying trends and challenges.
Ştefan Popenici, Sharon Kerr
This paper explores the emergence of AI in higher education, examining its impact on teaching, learning, and institutional evolution.