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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
Alexander Skulmowski – Educational Psychology Review, 2024
Generative AIs have been embraced by learners wishing to offload (parts of) complex tasks. However, recent research suggests that AI users are at risk of failing to correctly monitor the extent of their own contribution when being assisted by an AI. This difficulty in keeping track of the division of labor has been shown to result in placebo and…
Descriptors: Artificial Intelligence, Cognitive Processes, Difficulty Level, Epistemology
Samah AlKhuzaey; Floriana Grasso; Terry R. Payne; Valentina Tamma – International Journal of Artificial Intelligence in Education, 2024
Designing and constructing pedagogical tests that contain items (i.e. questions) which measure various types of skills for different levels of students equitably is a challenging task. Teachers and item writers alike need to ensure that the quality of assessment materials is consistent, if student evaluations are to be objective and effective.…
Descriptors: Test Items, Test Construction, Difficulty Level, Prediction

Andreea Dutulescu; Stefan Ruseti; Mihai Dascalu; Danielle S. McNamara – Grantee Submission, 2024
Assessing the difficulty of reading comprehension questions is crucial to educational methodologies and language understanding technologies. Traditional methods of assessing question difficulty rely frequently on human judgments or shallow metrics, often failing to accurately capture the intricate cognitive demands of answering a question. This…
Descriptors: Difficulty Level, Reading Tests, Test Items, Reading Comprehension
Ridvan Elmas; Merve Adiguzel-Ulutas; Mehmet Yilmaz – Education and Information Technologies, 2024
Many people use technological tools that are widely accessible, respond quickly, and have extensive information networks today. Due to recent technological advances in education and the increasing acceptance of Artificial Intelligence (AI) technologies, the issues regarding their implementation in education require identification and analysis.…
Descriptors: Artificial Intelligence, Science Education, Biochemistry, Information Dissemination
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
Kalina Kostyszyn – ProQuest LLC, 2024
Language learning is a complex issue of interest to linguists, computer scientists, and psychologists alike. While the different fields approach these questions at different levels of granularity, findings in one field profoundly affect how the others proceed. My dissertation examines the perceptual and linguistic generalizations regarding the…
Descriptors: Artificial Intelligence, Second Language Learning, Difficulty Level, Phonemes
Skulmowski, Alexander – Educational Psychology Review, 2023
This review is aimed at synthesizing current findings concerning technology-based cognitive offloading and the associated effects on learning and memory. While cognitive externalization (i.e., using the environment to outsource mental computation) is a highly useful technique in various problem-solving tasks, a growing body of research suggests…
Descriptors: Mental Computation, Learning Processes, Memory, Problem Solving
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
Xiaoming Zhai; Matthew Nyaaba; Wenchao Ma – Science & Education, 2025
This study aimed to examine an assumption regarding whether generative artificial intelligence (GAI) tools can overcome the cognitive intensity that humans suffer when solving problems. We examine the performance of ChatGPT and GPT-4 on NAEP science assessments and compare their performance to students by cognitive demands of the items. Fifty-four…
Descriptors: Artificial Intelligence, National Competency Tests, Elementary Secondary Education, Problem Solving
Xiaodong Wei; Lei Wang; Lap-Kei Lee; Ruixue Liu – Journal of Educational Computing Research, 2025
Notwithstanding the growing advantages of incorporating Augmented Reality (AR) in science education, the pedagogical use of AR combined with Pedagogical Agents (PAs) remains underexplored. Additionally, few studies have examined the integration of Generative Artificial Intelligence (GAI) into science education to create GAI-enhanced PAs (GPAs)…
Descriptors: Artificial Intelligence, Technology Uses in Education, Models, Science Education
Chih-Hung Wu; Vu Tran Ho – Education and Information Technologies, 2025
The present study investigated the potential of ChatGPT in enhancing the learning outcomes and engagement. Data were gathered from a survey of 687 university personnel and higher education students who utilized ChatGPT for educational purposes. The conceptual framework of the study was validated and analyzed using partial least squares structural…
Descriptors: Artificial Intelligence, Technology Uses in Education, Educational Benefits, Learner Engagement
Michael Hermann Hahn – ProQuest LLC, 2022
As humans, we use language with ease and speed, solving the complex computational problem of processing form and meaning seemingly without effort. This dissertation studies how the properties of language enable us to achieve this, by investigating what is computationally difficult about language, and what is easy. We first investigate the…
Descriptors: Language Usage, Difficulty Level, Artificial Intelligence, Language Processing
Moresi, Marco; Gomez, Marcos J.; Benotti, Luciana – IEEE Transactions on Learning Technologies, 2021
Based on hundreds of thousands of hours of data about how students learn in massive open online courses, educational machine learning promises to help students who are learning to code. However, in most classrooms, students and assignments do not have enough historical data for feeding these data hungry algorithms. Previous work on predicting…
Descriptors: Prediction, Difficulty Level, Programming, Online Courses
Gerardo Ibarra-Vazquez; María Soledad Ramírez-Montoya; Hugo Terashima – Education and Information Technologies, 2024
This article aims to study machine learning models to determine their performance in classifying students by gender based on their perception of complex thinking competency. Data were collected from a convenience sample of 605 students from a private university in Mexico with the eComplexity instrument. In this study, we consider the following…
Descriptors: Foreign Countries, College Students, Private Colleges, Gender Bias