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Showing all 11 results Save | Export
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Markus W. H. Spitzer; Lisa Bardach; Eileen Richter; Younes Strittmatter; Korbinian Moeller – Journal of Computer Assisted Learning, 2025
Background: Many students face difficulties with algebra. At the same time, it has been observed that fraction understanding predicts achievements in algebra; hence, gaining a better understanding of how algebra understanding builds on fraction understanding is an important goal for research and educational practice. Objectives: However, a wide…
Descriptors: Psychological Patterns, Network Analysis, Fractions, Algebra
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Wen Chiang Lim; Neil T. Heffernan; Adam Sales – Grantee Submission, 2025
As online learning platforms become more popular and deeply integrated into education, understanding their effectiveness and what drives that effectiveness becomes increasingly important. While there is extensive prior research illustrating the benefits of intelligent tutoring systems (ITS) for student learning, there is comparatively less focus…
Descriptors: Intelligent Tutoring Systems, Computer Uses in Education, Prompting, Reports
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Wen-Chiang Ivan Lim; Neil T. Heffernan III; Ivan Eroshenko; Wai Khumwang; Pei-Chen Chan – Grantee Submission, 2025
Intelligent tutoring systems are increasingly used in schools, providing teachers with valuable analytics on student learning. However, many teachers lack the time to review these reports in detail due to heavy workloads, and some face challenges with data literacy. This project investigates the use of large language models (LLMs) to generate…
Descriptors: Intelligent Tutoring Systems, Natural Language Processing, Assignments, Learning Management Systems
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Conrad Borchers; Jeroen Ooge; Cindy Peng; Vincent Aleven – Grantee Submission, 2025
Personalized problem selection enhances student practice in tutoring systems. Prior research has focused on transparent problem selection that supports learner control but rarely engages learners in selecting practice materials. We explored how different levels of control (i.e., full AI control, shared control, and full learner control), combined…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Learner Controlled Instruction, Learning Analytics
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Conrad Borchers; Cindy Peng; Qianru Lyu; Paulo F. Carvalho; Kenneth R. Koedinger; Vincent Aleven – Grantee Submission, 2025
Many AIED systems support self-regulated learning, yet, support for setting and achieving practice goals has received little attention. We examine how middle school students respond to system-recommended practice goals, building on the success of similar data-driven recommendations in other domains. We introduce an adaptive dashboard in an…
Descriptors: Goal Orientation, Student Attitudes, Self Control, Intelligent Tutoring Systems
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Luiz Rodrigues; Guilherme Guerino; Thomaz E. V. Silva; Geiser C. Challco; Lívia Oliveira; Rodolfo S. da Penha; Rafael F. Melo; Thales Vieira; Marcelo Marinho; Valmir Macario; Ig I. Bittencourt; Diego Dermeval; Seiji Isotani – International Journal of Artificial Intelligence in Education, 2025
Intelligent Tutoring Systems (ITS) possess significant potential to enhance learning outcomes. However, deploying ITSs in global south countries presents challenges due to their frequent lack of essential technological resources, such as computers and internet access. The concept of AIED Unplugged has emerged to bridge this digital divide,…
Descriptors: Teacher Attitudes, Intelligent Tutoring Systems, Numeracy, Mathematics Education
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Anitia Lubbe; Elma Marais; Donnavan Kruger – Education and Information Technologies, 2025
Amalgamating generative artificial intelligence (Gen AI), Bloom's taxonomy and critical thinking present a promising avenue to revolutionize assessment pedagogy and foster higher-order cognitive skills needed for learning autonomy in the domain of self-directed learning. Gen AI, a subset of artificial intelligence (AI), has emerged as a…
Descriptors: Critical Thinking, Computer Software, Learning Analytics, Intelligent Tutoring Systems
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Devika Venugopalan; Ziwen Yan; Conrad Borchers; Jionghao Lin; Vincent Aleven – Grantee Submission, 2025
Caregivers (i.e., parents and members of a child's caring community) are underappreciated stakeholders in learning analytics. Although caregiver involvement can enhance student academic outcomes, many obstacles hinder involvement, most notably knowledge gaps with respect to modern school curricula. An emerging topic of interest in learning…
Descriptors: Homework, Computational Linguistics, Teaching Methods, Learning Analytics
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Caitlin Mills, Editor; Giora Alexandron, Editor; Davide Taibi, Editor; Giosuè Lo Bosco, Editor; Luc Paquette, Editor – International Educational Data Mining Society, 2025
The University of Palermo is proud to host the 18th International Conference on Educational Data Mining (EDM) in Palermo, Italy, from July 20 to July 23, 2025. EDM is the annual flagship conference of the International Educational Data Mining Society. This year's theme is "New Goals, New Measurements, New Incentives to Learn." The theme…
Descriptors: Artificial Intelligence, Data Analysis, Computer Science Education, Technology Uses in Education
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Morakinyo Akintolu; Akinpelu A. Oyekunle – Journal of Educators Online, 2025
This paper provides a comprehensive overview of the research on the application of artificial intelligence (AI) in primary education to explore its potential to enhance teaching and learning processes. Through a systematic review of the relevant literature, this study identifies key areas in which AI can significantly impact primary education and…
Descriptors: Data Analysis, Learning Analytics, Artificial Intelligence, Computer Software
Suijing Yang; Daniel Taylor-Griffiths; Fabienne van der Kleij; Pauline Taylor-Guy; Ralph Saubern – Australian Council for Educational Research, 2025
Many existing reviews of educational technologies focus on the affordances of specific types of technology rather than how different technologies can be designed and used to achieve specific teaching and learning objectives. Furthermore, there appears to be a widely held assumption that the use of educational technology will result in improved…
Descriptors: Teacher Empowerment, Educational Technology, Technology Uses in Education, Technology Integration