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Fu-Yun Yu; Chih-Wei Kuo – Journal of Research on Technology in Education, 2024
There has been an increasing interest in the development of student question-generation (SQG) systems since 2000. To offer a holistic and detailed view of extant SQG systems, a two-dimensional classification scheme was derived to identify commonly embedded ancillary functionalities and design features in the 54 SQG learning systems located through…
Descriptors: Intelligent Tutoring Systems, Holistic Approach, Questioning Techniques, Instructional Design
MacLellan, Christopher J.; Koedinger, Kenneth R. – International Journal of Artificial Intelligence in Education, 2022
Intelligent tutoring systems are effective for improving students' learning outcomes (Pane et al. 2013; Koedinger and Anderson, "International Journal of Artificial Intelligence in Education," 8, 1-14, 1997; Bowen et al. "Journal of Policy Analysis and Management," 1, 94-111 2013). However, constructing tutoring systems that…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Models, Instructional Design
Galafassi, Cristiano; Galafassi, Fabiane Flores Penteado; Vicari, Rosa Maria; Reategui, Eliseo Berni – International Journal of Artificial Intelligence in Education, 2023
This work presents the intelligent tutoring system, EvoLogic, developed to assist students in problems of natural production in propositional logic. EvoLogic has been modeled as a multiagent system composed of three autonomous agents: interface, pedagogical and specialist agents. It supports pedagogical strategies inspired by the theory of…
Descriptors: Intelligent Tutoring Systems, Logical Thinking, Models, Teaching Methods
Yuhui Yang; Hao Zhang; Huifang Chai; Wei Xu – Interactive Learning Environments, 2023
The COVID-19 pandemic has accelerated the transformation of education forms, and the combination of online and offline teaching has become the core development direction of university teaching at present and in the future. Therefore, appropriate teaching space is urgently needed to support the practice of blended teaching. Firstly, this paper…
Descriptors: Intelligent Tutoring Systems, Instructional Design, Universities, Blended Learning
Huang, Yun; Brusilovsky, Peter; Guerra, Julio; Koedinger, Kenneth; Schunn, Christian – Journal of Computer Assisted Learning, 2023
Background: Skill integration is vital in students' mastery development and is especially prominent in developing code tracing skills which are foundational to programming, an increasingly important area in the current STEM education. However, instructional design to support skill integration in learning technologies has been limited. Objectives:…
Descriptors: Intelligent Tutoring Systems, Coding, Programming, Skill Development
Eglington, Luke G.; Pavlik, Philip I., Jr. – International Journal of Artificial Intelligence in Education, 2023
An important component of many Adaptive Instructional Systems (AIS) is a 'Learner Model' intended to track student learning and predict future performance. Predictions from learner models are frequently used in combination with mastery criterion decision rules to make pedagogical decisions. Important aspects of learner models, such as learning…
Descriptors: Computer Assisted Instruction, Intelligent Tutoring Systems, Learning Processes, Individual Differences
Ling Zhang; Zijun Yao; Arya Hadizadeh Moghaddam – Journal of Teacher Education, 2025
Educator preparation, personalized learning (PL) implementation, and applications of Generative AI converge as three interrelated systems that, when carefully designed, can help achieve the long-sought goal of providing inclusive education for all learners. However, realizing this potential comes with challenges resulting from theoretical…
Descriptors: Artificial Intelligence, Computer Software, Technology Integration, Faculty Development
Jinhee Kim; Seongryeong Yu; Rita Detrick; Na Li – Education and Information Technologies, 2025
The rapid development of generative artificial intelligence (GenAI), including large language models (LLM), has merged to support students in their academic writing process. Keeping pace with the technical and educational landscape requires careful consideration of the opportunities and challenges that GenAI-assisted systems create within…
Descriptors: Student Attitudes, Artificial Intelligence, Technology Uses in Education, Natural Language Processing
Jiyou Jia; Tianrui Wang; Yuyue Zhang; Guangdi Wang – Asia Pacific Journal of Education, 2024
In designing an intelligent tutoring system, a core area of the application of AI in education, tips from the system or virtual tutors are crucial in helping students solve difficult questions in disciplines like mathematics. Traditionally, the manual design of general tips by teachers is time-consuming and error-prone. Generative AI, like…
Descriptors: Problem Solving, Artificial Intelligence, Learning Processes, Prompting
Pavlik, Philip I., Jr.; Eglington, Luke G. – Grantee Submission, 2021
An intelligent textbook may be defined as an interaction layer between the text and the student, helping the student master the content in the text. The Mobile Fact and Concept Training System (MoFaCTS) is an adaptive instructional system for simple content that has been developed into an interaction layer to mediate textbook instruction and so is…
Descriptors: Textbooks, Intelligent Tutoring Systems, Electronic Learning, Instructional Design
Lutfun Nahar; Riza Sulaiman – Education and Information Technologies, 2025
Studying and solving geometry questions are the most challenging parts of mathematics for visually impaired students (VIS). This study begins with the needs assessment to identify the needs of VIS, which shows that technology-assisted effective teaching and learning are not available for VIS to learn geometry. Therefore, this study focuses on…
Descriptors: Instructional Design, Mathematics Instruction, Instructional Effectiveness, Computer Oriented Programs
Hollander, John; Sabatini, John; Graesser, Art – COABE Journal: The Resource for Adult Education, 2021
Twenty-first century literacy includes a mixture of digital and print literacy skills and strategies. AutoTutor for Adult Reading Comprehension is a web-based intelligent tutoring system that is designed to help adult learners develop effective reading comprehension strategies. Lessons span basic reading skills (vocabulary, word parts),…
Descriptors: Intelligent Tutoring Systems, Adult Literacy, Reading Instruction, Reading Comprehension
Hollander, John; Sabatini, John; Graesser, Art – Grantee Submission, 2021
Twenty-first century literacy includes a mixture of digital and print literacy skills and strategies. AutoTutor for Adult Reading Comprehension is a web-based intelligent tutoring system that is designed to help adult learners develop effective reading comprehension strategies. Lessons span basic reading skills (vocabulary, word parts),…
Descriptors: Intelligent Tutoring Systems, Adult Literacy, Reading Instruction, Reading Comprehension
Eglington, Luke G.; Pavlik, Philip I., Jr. – Grantee Submission, 2022
An important component of many Adaptive Instructional Systems (AIS) is a 'Learner Model' intended to track student learning and predict future performance. Predictions from learner models are frequently used in combination with mastery criterion decision rules to make pedagogical decisions. Important aspects of learner models, such as learning…
Descriptors: Computer Assisted Instruction, Intelligent Tutoring Systems, Learning Processes, Individual Differences
Linxuan Yi; Di Liu; Tiancheng Jiang; Yucheng Xian – International Journal of Science and Mathematics Education, 2025
Artificial intelligence (AI) shows increasing potential to improve mathematics instruction, yet integrative quantitative evidence currently is lacking on its overall effectiveness and factors influencing success. This systematic review and meta-analysis investigate the effectiveness of AI on improving mathematics performance in K-12 classrooms…
Descriptors: Program Effectiveness, Artificial Intelligence, Technology Uses in Education, Elementary School Students