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Norizan Mat Diah; Syahirul Riza; Suzana Ahmad; Norzilah Musa; Shakirah Hashim – Journal of Education and Learning (EduLearn), 2025
Sudoku is a puzzle that has a unique solution. No matter how many methods are used, the result will always be the same. The player thought that the number of givens or clues, the initial value on the Sudoku puzzles, would significantly determine the difficulty level, which is not necessarily correct. This research uses two search algorithms,…
Descriptors: Puzzles, Artificial Intelligence, Problem Solving, Algorithms
Pu Wang; Yifeng Lin; Tiesong Zhao – Education and Information Technologies, 2025
With the emergence of Artificial Intelligence (AI), smart education has become an attractive topic. In a smart education system, automated classrooms and examination rooms could help reduce the economic cost of teaching, and thus improve teaching efficiency. However, existing AI algorithms suffer from low surveillance accuracies and high…
Descriptors: Supervision, Artificial Intelligence, Technology Uses in Education, Automation
Mahmoud Abdasalam; Ahmad Alzubi; Kolawole Iyiola – Education and Information Technologies, 2025
This study introduces an optimized ensemble deep neural network (Optimized Ensemble Deep-NN) to enhance the accuracy of predicting student grades. This model solves the problem of different and complicated student performance data by using deep neural networks, ensemble learning, and a number of optimization algorithms, such as Adam, SGD, and RMS…
Descriptors: Grades (Scholastic), Prediction, Accuracy, Artificial Intelligence
Pallavi Singh; Phat K. Huynh; Dang Nguyen; Trung Q. Le; Wilfrido Moreno – IEEE Transactions on Learning Technologies, 2025
In organizational and academic settings, the strategic formation of teams is paramount, necessitating an approach that transcends conventional methodologies. This study introduces a novel application of multicriteria integer programming (MCIP), which simultaneously accommodates multiple criteria, thereby innovatively addressing the complex task of…
Descriptors: Teamwork, Group Dynamics, Research Design, Models
Gulnara Z. Karimova; Yevgeniya D. Kim; Amir Shirkhanbeik – Education and Information Technologies, 2025
This exploratory study investigates the convergence of marketing communications and AI-powered technology in higher education, adopting a perspective on student interactions with generative AI tools. Through a comprehensive content analysis of learners' responses, we employed a blend of manual scrutiny, Python-generated Word Cloud, and Latent…
Descriptors: Artificial Intelligence, Marketing, Student Attitudes, Higher Education
Long Zhang; Khe Foon Hew – Education and Information Technologies, 2025
Although self-regulated learning (SRL) plays an important role in supporting online learning performance, the lack of student self-regulation skills poses a persistent problem to many educators. Recommender systems have the potential to promote SRL by delivering personalized feedback and tailoring learning strategies to meet individual learners'…
Descriptors: Independent Study, Electronic Learning, Online Courses, Artificial Intelligence
Zuchao Shen; Walter Leite; Huibin Zhang; Jia Quan; Huan Kuang – Journal of Experimental Education, 2025
When designing cluster-randomized trials (CRTs), one important consideration is determining the proper sample sizes across levels and treatment conditions to cost-efficiently achieve adequate statistical power. This consideration is usually addressed in an optimal design framework by leveraging the cost structures of sampling and optimizing the…
Descriptors: Randomized Controlled Trials, Feasibility Studies, Research Design, Sample Size
Mirjam Sophia Glessmer; Rachel Forsyth – Teaching & Learning Inquiry, 2025
Generative AI tools (GenAI) are increasingly used for academic tasks, including qualitative data analysis for the Scholarship of Teaching and Learning (SoTL). In our practice as academic developers, we are frequently asked for advice on whether this use for GenAI is reliable, valid, and ethical. Since this is a new field, we have not been able to…
Descriptors: Artificial Intelligence, Research Methodology, Data Analysis, Scholarship
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
Qian Fu; Xinyi Zhou; Yafeng Zheng; Zhenyi Wang – Journal of Computer Assisted Learning, 2025
Background: Understanding algorithms is crucial for programming education, yet their abstract nature often challenges students. Algorithm visualisation (AV) has been proven effective in enhancing algorithmic thinking among university students. However, its efficacy for elementary school students and the optimal forms of AV tools remain unclear.…
Descriptors: Algorithms, Visualization, Elementary School Students, Learning Motivation
Mustafa Serkan Pelen – International Journal of Science and Mathematics Education, 2025
The main purpose of this research is to examine the informal strategies of fifth and sixth grade students while solving inverse proportional word problems. Multiple case study was used in this study. The research was carried out in a public middle school from a southern city of Türkiye. The participants of the research consist of three fifth and…
Descriptors: Algorithms, Word Problems (Mathematics), Problem Solving, Mathematics Instruction
Shoba S. Meera; Divya Swaminathan; Sri Ranjani Venkata Murali; Reny Raju; Malavi Srikar; Sahana Shyam Sundar; Senthil Amudhan; Alejandrina Cristia; Rahul Pawar; Achuth Rao; Prathyusha P. Vasuki; Shree Volme; Ashok Mysore – Journal of Speech, Language, and Hearing Research, 2025
Purpose: The Language ENvironment Analysis (LENA) technology uses automated speech processing (ASP) algorithms to estimate counts such as total adult words and child vocalizations, which helps understand children's early language environment. This ASP has been validated in North American English and other languages in predominantly monolingual…
Descriptors: Foreign Countries, Multilingualism, Adults, Speech Communication
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
Austin Wyman; Zhiyong Zhang – Grantee Submission, 2025
Automated detection of facial emotions has been an interesting topic for multiple decades in social and behavioral research but is only possible very recently. In this tutorial, we review three popular artificial intelligence based emotion detection programs that are accessible to R programmers: Google Cloud Vision, Amazon Rekognition, and…
Descriptors: Artificial Intelligence, Algorithms, Computer Software, Identification
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