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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
Jyoti Prakash Meher; Rajib Mall – IEEE Transactions on Education, 2025
Contribution: This article suggests a novel method for diagnosing a learner's cognitive proficiency using deep neural networks (DNNs) based on her answers to a series of questions. The outcome of the forecast can be used for adaptive assistance. Background: Often a learner spends considerable amounts of time in attempting questions on the concepts…
Descriptors: Cognitive Ability, Assistive Technology, Adaptive Testing, Computer Assisted Testing
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
Jin, Hao-Yue; Cutumisu, Maria – Education and Information Technologies, 2023
Computational thinking (CT) skills of pre-service teachers have been explored extensively, but the effectiveness of CT training has yielded mixed results in previous studies. Thus, it is necessary to identify patterns in the relationships between predictors of CT and CT skills to further support CT development. This study developed an online CT…
Descriptors: Preservice Teachers, Computation, Thinking Skills, Predictor Variables
Mike, Koby; Hazzan, Orit – IEEE Transactions on Education, 2023
Contribution: This article presents evidence that electrical engineering, computer science, and data science students, participating in introduction to machine learning (ML) courses, fail to interpret the performance of ML algorithms correctly, since they fail to consider the application domain. This phenomenon is referred to as the domain neglect…
Descriptors: Engineering Education, Computer Science Education, Data Science, Introductory Courses
Miaomiao Liu; Yixun Li; Yongqiang Su; Hong Li – Scientific Studies of Reading, 2024
Purpose: This study sought to 1) identify linguistic features important for Chinese text complexity with a theory-based and systematic approach, and 2) address how feature sets and algorithms affect the performance of Chinese text complexity models. Method: Texts from Chinese language arts textbooks from Grades 1 to 6 (N = 1,478) in Mainland China…
Descriptors: Difficulty Level, Textbooks, Algorithms, Artificial Intelligence
Mingying Zheng – ProQuest LLC, 2024
The digital transformation in educational assessment has led to the proliferation of large-scale data, offering unprecedented opportunities to enhance language learning, and testing through machine learning (ML) techniques. Drawing on the extensive data generated by online English language assessments, this dissertation investigates the efficacy…
Descriptors: Artificial Intelligence, Computational Linguistics, Language Tests, English (Second Language)