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Showing 1 to 15 of 28 results Save | Export
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Guiyun Feng; Honghui Chen – Education and Information Technologies, 2025
Data mining has been successfully and widely utilized in educational information systems, and an important research field has been formed, which is educational data mining. Process mining inherits the characteristics of data mining which can not only use historical data in the system to analyze learning behavior and predict academic performance,…
Descriptors: Educational Research, Artificial Intelligence, Data Use, Algorithms
Emily J. Barnes – ProQuest LLC, 2024
This quantitative study investigates the predictive power of machine learning (ML) models on degree completion among adult learners in higher education, emphasizing the enhancement of data-driven decision-making (DDDM). By analyzing three ML models - Random Forest, Gradient-Boosting machine (GBM), and CART Decision Tree - within a not-for-profit,…
Descriptors: Artificial Intelligence, Higher Education, Models, Prediction
Yihe Zhang – ProQuest LLC, 2024
Machine learning (ML) techniques have been successfully applied to a wide array of applications. This dissertation aims to take application data handling into account when developing ML-based solutions for real-world problems through a holistic framework. To demonstrate the generality of our framework, we consider two real-world applications: spam…
Descriptors: Artificial Intelligence, Problem Solving, Social Media, Computer Mediated Communication
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Yannik Fleischer; Susanne Podworny; Rolf Biehler – Statistics Education Research Journal, 2024
This study investigates how 11- to 12-year-old students construct data-based decision trees using data cards for classification purposes. We examine the students' heuristics and reasoning during this process. The research is based on an eight-week teaching unit during which students labeled data, built decision trees, and assessed them using test…
Descriptors: Decision Making, Data Use, Cognitive Processes, Artificial Intelligence
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M. B. Saikrishna – On the Horizon, 2025
Purpose: The purpose of this paper is to investigate how educators perceive and adapt their roles in the face of changes in technology-driven learning environments. The Gioia methodology explores how educators enable adaptive learning, broaden their pedagogical practice and promote cultural inclusivity to educate diverse students.…
Descriptors: Teacher Attitudes, Educational Technology, Technology Uses in Education, Teacher Role
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Lukas Höper; Carsten Schulte – Informatics in Education, 2024
In K-12 computing education, there is a need to identify and teach concepts that are relevant to understanding machine learning technologies. Studies of teaching approaches often evaluate whether students have learned the concepts. However, scant research has examined whether such concepts support understanding digital artefacts from everyday life…
Descriptors: Student Empowerment, Data Use, Computer Science Education, Artificial Intelligence
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Cherise McBride; Clifford H. Lee; Elisabeth Soep – Reading Research Quarterly, 2024
Rapidly developing technological advances have raised new questions about what makes us uniquely human. As data and generative AI become more powerful, what does it mean to learn, teach, create, make meaning, and express ourselves, even as machines are trained to take care of these tasks for us? With youth, and in the context of literacy and media…
Descriptors: Literacy, Media Education, Adolescents, Young Adults
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Mukesh Kumar Rohil; Saksham Mahajan; Trishna Paul – Education and Information Technologies, 2025
Intelligent Tutoring Systems (ITS) and Augmented Reality (AR) have become greatly popular in current scenario, especially for helping students in mastering difficult subjects through a variety of different methods with the implementation of smart algorithms. There are many papers in the current literature that discuss the ITS architecture and the…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Physical Environment, Simulated Environment
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Qinyi Liu; Ronas Shakya; Jelena Jovanovic; Mohammad Khalil; Javier Hoz-Ruiz – British Journal of Educational Technology, 2025
High-volume, high-quality and diverse datasets are crucial for advancing research in the education field. However, such datasets often contain sensitive information that poses significant privacy challenges. Traditional anonymisation techniques fail to meet the privacy standards required by regulations like GDPR, prompting the need for more robust…
Descriptors: Privacy, Data, Information Security, Compliance (Legal)
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Jongsawas Chongwatpol – Education and Information Technologies, 2024
The philosophy for information system (IS)-related projects, such as artificial intelligence (AI) projects, embodies systematic and scientific approaches, that encompass the development, use, and applications of IS by focusing on the interactions among individuals, organizations, and society. However, many organizations still need to learn more…
Descriptors: Artificial Intelligence, Information Systems, Thinking Skills, Design
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Fernando Filgueiras – Education, Citizenship and Social Justice, 2024
Artificial intelligence (AI) and big data methodologies have provided a vast possibility of applications in different public policy sectors. AI and big data provide essential innovations in school teaching and learning practices, curriculum, and management in education, transforming the entire formulation and implementation of education policy.…
Descriptors: Artificial Intelligence, Social Justice, Technology Uses in Education, Educational Technology
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Andrea Zanellati; Stefano Pio Zingaro; Maurizio Gabbrielli – IEEE Transactions on Learning Technologies, 2024
Academic dropout remains a significant challenge for education systems, necessitating rigorous analysis and targeted interventions. This study employs machine learning techniques, specifically random forest (RF) and feature tokenizer transformer (FTT), to predict academic attrition. Utilizing a comprehensive dataset of over 40 000 students from an…
Descriptors: Dropouts, Dropout Characteristics, Potential Dropouts, Artificial Intelligence
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Md Akib Zabed Khan; Agoritsa Polyzou – Journal of Educational Data Mining, 2024
In higher education, academic advising is crucial to students' decision-making. Data-driven models can benefit students in making informed decisions by providing insightful recommendations for completing their degrees. To suggest courses for the upcoming semester, various course recommendation models have been proposed in the literature using…
Descriptors: Academic Advising, Courses, Data Use, Artificial Intelligence
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Krista Bixler; Marjorie Ceballos – Leadership and Policy in Schools, 2025
Instructional leadership is a complex dimension, which requires that principals possess expertise in goal setting, leading the instructional program, and creating the conditions for a successful school environment. Effective instructional leaders manage the instructional program by planning, coordinating, and evaluating the work of teachers and…
Descriptors: Principals, Instructional Leadership, Artificial Intelligence, Educational Technology
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Emily C. Hanno; Ximena A. Portilla; JoAnn Hsueh – Child Development Perspectives, 2025
In this article, we adopt culturally relevant perspectives on developmental science that acknowledge and value the diversity of backgrounds and experiences of young children and their families to identify opportunities to advance the measurement of early childhood development. We focus on direct child assessments that can drive more equitable…
Descriptors: Young Children, Child Development, Equal Education, Evaluation Methods
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