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Anitia Lubbe; Elma Marais; Donnavan Kruger – Education and Information Technologies, 2025
Amalgamating generative artificial intelligence (Gen AI), Bloom's taxonomy and critical thinking present a promising avenue to revolutionize assessment pedagogy and foster higher-order cognitive skills needed for learning autonomy in the domain of self-directed learning. Gen AI, a subset of artificial intelligence (AI), has emerged as a…
Descriptors: Critical Thinking, Computer Software, Learning Analytics, Intelligent Tutoring Systems
Erick Fernando; Rosilah Hassan; Dina Fitria Murad; Zeyad Ghaleb Al-Mekhlafi – Educational Process: International Journal, 2025
Background/purpose: Education continues to evolve along with technological advances, and one of the biggest changes is the application of artificial intelligence (AI) in the learning process. The main problem in this study is the lack of in-depth understanding of the factors that influence the effectiveness of using AI in self-paced learning…
Descriptors: Literature Reviews, Meta Analysis, Bibliometrics, Artificial Intelligence
Genghu Shi; Shun Peng; Daphne Greenberg; Jan Frijters; Arthur C. Graesser – International Educational Data Mining Society, 2025
Adult literacy in the U.S. remains a persistent challenge. Alarmingly, half of adults demonstrated literacy skills at or below basic proficiency levels. This deficiency significantly impacts the daily functioning, workplace success, health outcomes, and socioeconomic disparities. Intelligent tutoring systems (ITS) serve as a promising solution for…
Descriptors: Adult Learning, Adult Education, Adult Students, Academic Persistence
Nedim Slijepcevic; Ali Yaylali – Journal of Teaching and Learning, 2025
This mixed-methods study investigated the effectiveness of Generative AI (GenAI) powered intelligent tutoring systems (ITS) in undergraduate physics education, specifically comparing learning outcomes between students using Khanmigo (Khan Academy's AI tutor) and the Google search engine. The study involved 69 undergraduate students divided into…
Descriptors: Undergraduate Students, Science Education, Physics, Scientific Concepts
Jasmine Donkoh; Susan Maruca; Eli Meir – American Biology Teacher, 2025
Online learning in higher education has grown significantly over the past decade, with millions of students engaging with online learning tutorials and assessments. However, the effectiveness of online learning is less understood, particularly whether students achieve the same learning gains when taking online assessments at home versus in a…
Descriptors: Undergraduate Students, Electronic Learning, Online Courses, College Science
Matsuda, Noboru – International Journal of Artificial Intelligence in Education, 2022
This paper demonstrates that a teachable agent (TA) can play a dual role in an online learning environment (OLE) for learning by teaching--the teachable agent working as a synthetic peer for students to learn by teaching and as an interactive tool for cognitive task analysis when authoring an OLE for learning by teaching. We have developed an OLE…
Descriptors: Artificial Intelligence, Teaching Methods, Intelligent Tutoring Systems, Feedback (Response)
Pavlik, Philip I., Jr.; Zhang, Liang – Grantee Submission, 2022
A longstanding goal of learner modeling and educational data mining is to improve the domain model of knowledge that is used to make inferences about learning and performance. In this report we present a tool for finding domain models that is built into an existing modeling framework, logistic knowledge tracing (LKT). LKT allows the flexible…
Descriptors: Models, Regression (Statistics), Intelligent Tutoring Systems, Learning Processes
John Hollander; John Sabatini; Art Graesser – Grantee Submission, 2022
AutoTutor-ARC (adult reading comprehension) is an intelligent tutoring system that uses conversational agents to help adult learners improve their comprehension skills. However, in such a system, not all lessons and items optimally serve the same purposes. In this paper, we describe a method for classifying items that are "instructive,…
Descriptors: Intelligent Tutoring Systems, Reading Skills, Psychometrics, Reading Comprehension
Wang, Tingting; Lajoie, Susanne P. – Educational Psychology Review, 2023
Although cognitive load (CL) and self-regulated learning (SRL) have been widely recognized as two determinant factors of students' performance, the integration of these two factors is still in its infancy. To further specify why and how CL links with SRL, we first conducted an overview to describe the multiple dimensions of cognitive load (i.e.,…
Descriptors: Cognitive Ability, Metacognition, Cognitive Processes, Correlation
Personalized Recommendation in the Adaptive Learning System: The Role of Adaptive Testing Technology
Dai, Jing; Gu, Xiaoqing; Zhu, Jiawen – Journal of Educational Computing Research, 2023
Personalized recommendation plays an important role on content selection during the adaptive learning process. It is always a challenge on how to recommend effective items to improve learning performance. The aim of this study was to examine the feasibility of applying adaptive testing technology for personalized recommendation. We proposed the…
Descriptors: Individualized Instruction, Intelligent Tutoring Systems, Evaluation Methods, Tests
Alberto Giretti; Dilan Durmus; Massimo Vaccarini; Matteo Zambelli; Andrea Guidi; Franco Ripa di Meana – International Association for Development of the Information Society, 2023
This paper provides a possible strategy for integrating large language artificial intelligence models (LLMs) in supporting students' education in artistic or design activities. We outline the methodological foundations concerning the integration of CHATGPT LLM in the educational approach aimed at enhancing artistic conception and design ideation.…
Descriptors: Art Education, Design, Artificial Intelligence, Computer Software
Matzavela, Vasiliki; Alepis, Efthimios – Education and Information Technologies, 2023
During the last decade an eruptive increase in the demand for intelligent m-learning environments has been observed since instructors in the online academic procedures need to ensure reliability. The research for decision systems seemed inevitable for flexible and effective learning in all levels of education. The prediction of the performance of…
Descriptors: Self Evaluation (Individuals), Mathematics Education, Intelligent Tutoring Systems, Electronic Learning
Guo, Lu; Wang, Dong; Gu, Fei; Li, Yazheng; Wang, Yezhu; Zhou, Rongting – Asia Pacific Education Review, 2021
Intelligent tutoring systems (ITSs) are a promising integrated educational tool for customizing formal education using intelligent instruction or feedback. In recent decades, ITSs have transformed teaching and learning and associated research. This study examined the evolution and future trends of ITS research with scientometric methods. First, a…
Descriptors: Intelligent Tutoring Systems, Educational Research, Educational Trends, Futures (of Society)
Yang, Chunsheng; Chiang, Feng-Kuang; Cheng, Qiangqiang; Ji, Jun – Journal of Educational Computing Research, 2021
Machine learning-based modeling technology has recently become a powerful technique and tool for developing models for explaining, predicting, and describing system/human behaviors. In developing intelligent education systems or technologies, some research has focused on applying unique machine learning algorithms to build the ad-hoc student…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Data Use, Models
Graf von Malotky, Nikolaj Troels; Martens, Alke – International Association for Development of the Information Society, 2021
ITSs have the requirement to be adaptive to the student with AI. The classical ITS architecture defines three components to split the data and to keep it flexible and thus adaptive. However, there is a lack of abstract descriptions how to put adaptive behavior into practice. This paper defines how you can structure your data for case based systems…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Instructional Development, Instructional Improvement

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