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Jia He – International Electronic Journal of Mathematics Education, 2025
This study examined 11 U.S. textbooks written for prospective teachers to investigate how standard decimal multiplication and division algorithms are presented, especially the rationale of both algorithms. Analytical frameworks of various methods used in different textbooks were developed. The findings suggest that half of the textbooks do not…
Descriptors: Elementary School Teachers, Preservice Teachers, Arithmetic, Mathematics Instruction
Ibrahim Albluwi; Raghda Hriez; Raymond Lister – ACM Transactions on Computing Education, 2025
Explain-in-Plain-English (EiPE) questions are used by some researchers and educators to assess code reading skills. EiPE questions require students to briefly explain (in plain English) the purpose of a given piece of code, without restating what the code does line-by-line. The premise is that novices who can explain the purpose of a piece of code…
Descriptors: Questioning Techniques, Programming, Computer Science Education, Student Evaluation
Brady L. Nash; Allison Skerrett – Harvard Educational Review, 2025
In this essay, Brady L. Nash and Allison Skerrett reexamine the New London Group's theory of multiliteracies thirty years after its initial conception, considering how changes in technology, culture, and politics have impacted the ability of young people to act as designers of social futures. Multiliteracies theory led to an explosion of…
Descriptors: Multiple Literacies, Design, Digital Literacy, Artificial Intelligence
Muhammad Kamal Hossen; Mohammad Shorif Uddin – Education and Information Technologies, 2025
Online learning continues to expand due to globalization and the COVID-19 pandemic. However, maintaining student engagement in this new normal has become increasingly difficult. Conventional techniques, such as self-reports and manual observations, often fall short of capturing the subtle behaviors that indicate attentiveness. This emphasizes the…
Descriptors: Learner Engagement, Online Courses, Artificial Intelligence, Technology Uses in Education
Abdul Ghaffar; Irfan Ud Din; Asadullah Tariq; Mohammad Haseeb Zafar – Review of Education, 2025
University Examination Timetabling Problem is the most important combinational problem to develop a conflict-free timetable to execute all of the exams in and with the limited timeslots and other resources for universities, colleges or schools. It is also an important Nondeterministic Polynomial Time (NP)-hard problem that has no deterministic…
Descriptors: Artificial Intelligence, Universities, Tests, Student Evaluation
Jiangyi Cui; Ruijiao Li; Qiushu Chen; Libin Liu; Xuan Zhao; Kai Liu; Huiliang Shang – International Journal of Technology in Education and Science, 2025
Face anonymization in intelligent experimental education is crucial for privacy protection. This paper presents a novel, real-time face blurring system for smart experimental settings. Our key contributions include: 1) customized YOLOv8 (Multi-Scale Feature Fusion YOLOv8) algorithm achieving 96% accuracy at 22.67 fps for 1080p video. 2) An…
Descriptors: Privacy, Experiments, Confidentiality, Ethics
Ahmad Slim; Chaouki Abdallah; Elisha Allen; Michael Hickman; Ameer Slim – International Educational Data Mining Society, 2025
Curricular design in higher education significantly impacts student success and institutional performance. However, academic programs' complexity--shaped by pass rates, prerequisite dependencies, and course repeat policies--creates challenges for administrators. This paper presents a method for modeling curricular pathways including development of…
Descriptors: Curriculum Design, Integrated Curriculum, Data Analysis, Monte Carlo Methods
Mila Zhu – Thresholds in Education, 2025
This study investigates the role of generative artificial intelligence (AI) in music education, focusing on its dual function as a creative tool and a mechanism of algorithmic surveillance. Utilizing AI platforms such as Suno.AI, MusicFX, and Udio, the study examines AI's potential to foster creativity, enable synesthetic learning, and personalize…
Descriptors: Music Education, Artificial Intelligence, Technology Uses in Education, Creativity
Harikesh Singh; Li-Minn Ang; Dipak Paudyal; Mauricio Acuna; Prashant Kumar Srivastava; Sanjeev Kumar Srivastava – Technology, Knowledge and Learning, 2025
Wildfires pose significant environmental threats in Australia, impacting ecosystems, human lives, and property. This review article provides a comprehensive analysis of various empirical and dynamic wildfire simulators alongside machine learning (ML) techniques employed for wildfire prediction in Australia. The study examines the effectiveness of…
Descriptors: Artificial Intelligence, Computer Software, Computer Simulation, Prediction
Félix González-Carrasco; Felipe Espinosa Parra; Izaskun Álvarez-Aguado; Sebastián Ponce Olguín; Vanessa Vega Córdova; Miguel Roselló-Peñaloza – British Journal of Learning Disabilities, 2025
Background: The study focuses on the need to optimise assessment scales for support needs in individuals with intellectual and developmental disabilities. Current scales are often lengthy and redundant, leading to exhaustion and response burden. The goal is to use machine learning techniques, specifically item-reduction methods and selection…
Descriptors: Artificial Intelligence, Intellectual Disability, Developmental Disabilities, Individual Needs
Inés Gallego-Sánchez; Verónica Martín-Molina; Isabel Caro-Torró; José María Gavilán-Izquierdo – Education 3-13, 2025
Our work investigated how six primary school students used a non-traditional method for adding and subtracting: the ABN method, a Spanish acronym for Open (method) Based on Numbers. Commognitive theory [Sfard, A. 2008. "Thinking as Communicating: Human Development, the Growth of Discourses, and Mathematizing." New York: Cambridge…
Descriptors: Foreign Countries, Elementary School Students, Addition, Subtraction
Gamze Türkmen – Journal of Educational Computing Research, 2025
Explainable Artificial Intelligence (XAI) refers to systems that make AI models more transparent, helping users understand how outputs are generated. XAI algorithms are considered valuable in educational research, supporting outcomes like student success, trust, and motivation. Their potential to enhance transparency and reliability in online…
Descriptors: Artificial Intelligence, Natural Language Processing, Trust (Psychology), Electronic Learning
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)
Aicha Er-Rafyg; Abdellah Idrissi; Kaoutar El Handri – International Journal of Learning Technology, 2025
In today's digital age, online courses have become a valuable tool for learners to acquire new skills and knowledge. The global outbreak of COVID-19 has further accelerated the adoption of online learning as education service providers are forced to move their courses online to ensure the continuity of education. However, with many online courses,…
Descriptors: Technology Uses in Education, Online Courses, Artificial Intelligence, Information Systems
Hyunkyung Chee; Solmoe Ahn; Jihyun Lee – British Journal of Educational Technology, 2025
This study aims to develop a comprehensive competency framework for artificial intelligence (AI) literacy, delineating essential competencies and sub-competencies. This framework and its potential variations, tailored to different learner groups (by educational level and discipline), can serve as a crucial reference for designing and implementing…
Descriptors: Competence, Digital Literacy, Artificial Intelligence, Technology Uses in Education

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