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Bogdan Yamkovenko; Charlie A. R. Hogg; Maya Miller-Vedam; Phillip Grimaldi; Walt Wells – International Educational Data Mining Society, 2025
Knowledge tracing (KT) models predict how students will perform on future interactions, given a sequence of prior responses. Modern approaches to KT leverage "deep learning" techniques to produce more accurate predictions, potentially making personalized learning paths more efficacious for learners. Many papers on the topic of KT focus…
Descriptors: Algorithms, Artificial Intelligence, Models, Prediction
Yang Shi; Tiffany Barnes; Min Chi; Thomas Price – International Educational Data Mining Society, 2024
Knowledge tracing (KT) models have been a commonly used tool for tracking students' knowledge status. Recent advances in deep knowledge tracing (DKT) have demonstrated increased performance for knowledge tracing tasks in many datasets. However, interpreting students' states on single knowledge components (KCs) from DKT models could be challenging…
Descriptors: Algorithms, Artificial Intelligence, Models, Programming
Yang Yuan – International Journal of Web-Based Learning and Teaching Technologies, 2024
In order to explore the maturity of online concerts and the digital content of music resources, this article analyzes the role of artificial intelligence in music education, discusses the application of artificial intelligence in music education and the development trend of artificial intelligence in education, and studies the quality of vocal…
Descriptors: Music Education, Singing, Artificial Intelligence, Educational Technology
Andrew Kwok-Fai Lui; Sin-Chun Ng; Stella Wing-Nga Cheung – Interactive Learning Environments, 2024
The technology of automated short answer grading (ASAG) can efficiently process answers according to human-prepared grading examples. Computer-assisted acquisition of grading examples uses a computer algorithm to sample real student responses for potentially good examples. The process is critical for optimizing the grading accuracy of machine…
Descriptors: Grading, Computer Uses in Education, Educational Technology, Artificial Intelligence
Tanja Käser; Giora Alexandron – International Journal of Artificial Intelligence in Education, 2024
Simulation is a powerful approach that plays a significant role in science and technology. Computational models that simulate learner interactions and data hold great promise for educational technology as well. Amongst others, simulated learners can be used for teacher training, for generating and evaluating hypotheses on human learning, for…
Descriptors: Computer Simulation, Educational Technology, Artificial Intelligence, Algorithms
Ezequiel Aleman; Ricardo Martinez – Reading Research Quarterly, 2024
This study explores how youth engage with literacy practices in the age of AI through the use of counter-cartographies within the Nayah-Irú curriculum. By critically examining digital platforms and the underlying algorithms, students embarked on a journey to understand and challenge the pervasive influence of artificial intelligence in their…
Descriptors: Digital Literacy, Artificial Intelligence, Algorithms, Educational Technology
Eyüp Yurt – International Society for Technology, Education, and Science, 2024
This study addresses the opportunities presented by AI applications in education and the ethical issues brought about by this technology. AI in education holds excellent potential in personalized learning, automated assessment and feedback, and monitoring and analyzing student performance. However, using these technologies also raises ethical…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, Ethics
Munish Saini; Eshan Sengupta; Naman Sharma – Education and Information Technologies, 2025
To be an effective teacher, one must possess strong learning abilities. Developing lesson planning, pursuing learning objectives, and assessing post-lesson accomplishments all these depend on reflection and ongoing learning. As education is context-specific, the iterative process of preparing, reflecting, and improving is what makes teaching…
Descriptors: Artificial Intelligence, Technology Uses in Education, Nonverbal Communication, Feedback (Response)
Maciej Pankiewicz; Yang Shi; Ryan S. Baker – International Educational Data Mining Society, 2025
Knowledge Tracing (KT) models predicting student performance in intelligent tutoring systems have been successfully deployed in several educational domains. However, their usage in open-ended programming problems poses multiple challenges due to the complexity of the programming code and a complex interplay between syntax and logic requirements…
Descriptors: Algorithms, Artificial Intelligence, Models, Intelligent Tutoring Systems
adam patrick bell – Action, Criticism, and Theory for Music Education, 2025
In this article I examine the generative AI music-making applications of Google called MusicFX DJ and Music AI Sandbox, as well as Udio, an end-to-end generative AI music system created by ex-Google employees. I frame these generative AI music systems designed by Big Tech as part of their neoliberal agenda, which involves influencing music…
Descriptors: Music Education, Artificial Intelligence, Technology Uses in Education, Educational Technology
Abdelmadjid Benmachiche; Abdelhadi Sahia; Soundes Oumaima Boufaida; Khadija Rais; Makhlouf Derdour; Faiz Maazouzi – Education and Information Technologies, 2025
In the context of massive open online courses (MOOCs), searching and retrieving information can be challenging because there is a huge amount of unstructured content, which creates a problem and makes it difficult for users to quickly find relevant lessons or resources. As a result, learners and teachers face significant barriers to accessing the…
Descriptors: MOOCs, Natural Language Processing, Artificial Intelligence, Search Engines
Kaitlyn Tracy; Ourania Spantidi – IEEE Transactions on Learning Technologies, 2025
Virtual reality (VR) has emerged as a transformative educational tool, enabling immersive learning environments that promote student engagement and understanding of complex concepts. However, despite the growing adoption of VR in education, there remains a significant gap in research exploring how generative artificial intelligence (AI), such as…
Descriptors: Artificial Intelligence, Computer Assisted Instruction, Computer Simulation, Educational Technology
Shabnam Ara S. J.; Tanuja Ramachandriah; Manjula S. Haladappa – Online Learning, 2025
Predicting learner performance with precision is critical within educational systems, offering a basis for tailored interventions and instruction. The advent of big data analytics presents an opportunity to employ Machine Learning (ML) techniques to this end. Real-world data availability is often hampered by privacy concerns, prompting a shift…
Descriptors: Learning Analytics, Privacy, Artificial Intelligence, Regression (Statistics)
Imtiaz Ahamed; Afsana Azmari – Journal of Education and Learning, 2025
A crucial aspect of this research is determining the effectiveness of the tool developed for this study. This tool is built upon the understanding that technology continually evolves and significantly impacts higher education. It is believed that technology plays a vital role in how students learn in college today. This belief is supported by the…
Descriptors: Educational Technology, Educational History, Automation, Educational Innovation
Johri, Aditya – Research in Learning Technology, 2022
There has been a conscious effort in the past decade to produce a more theoretical account of the use of technology for learning. At the same time, advances in artificial intelligence (AI) are being rapidly incorporated into learning technologies, significantly changing their affordances for teaching and learning. In this article I address the…
Descriptors: Artificial Intelligence, Educational Technology, Technology Uses in Education, Affordances

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