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Showing 1 to 15 of 44 results Save | Export
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Qian Xu – Discover Education, 2024
This research suggests a methodology to examine the effectiveness Artificial Intelligence (AI) on the cognitive abilities of college students so that future researchers can utilize this experimental project to focus on how AI-powered Intelligent Tutoring Systems (ITSs) affect learning outcomes. As AI continues to revolutionize all walks of life,…
Descriptors: Artificial Intelligence, Cognitive Ability, College Students, Intelligent Tutoring Systems
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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)
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Shakya, Anup; Rus, Vasile; Venugopal, Deepak – International Educational Data Mining Society, 2023
Understanding a student's problem-solving strategy can have a significant impact on effective math learning using Intelligent Tutoring Systems (ITSs) and Adaptive Instructional Systems (AISs). For instance, the ITS/AIS can better personalize itself to correct specific misconceptions that are indicated by incorrect strategies, specific problems can…
Descriptors: Equal Education, Mathematics Education, Word Problems (Mathematics), Problem Solving
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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
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Ismail Celik; Egle Gedrimiene; Signe Siklander; Hanni Muukkonen – Australasian Journal of Educational Technology, 2024
Twenty-first-century skills should be integrated into higher education to prepare students for complex working-life challenges. Artificial intelligence (AI)-powered tools have the potential to optimise skill development among higher education students. Therefore, it is important to conceptualise relevant affordances of AI systems for 21st-century…
Descriptors: Artificial Intelligence, 21st Century Skills, Higher Education, Educational Research
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Quadir, Benazir; Mostafa, Kazi; Yang, Jie Chi; Shen, Juming; Akter, Rokaya – Education and Information Technologies, 2023
This study used the ARCS approach to investigate the effects of university students' motivation, including attention, relevance, confidence, and satisfaction, to use the Programming Teaching Assistant (PTA) on their Programming Problem-Solving Skills (PPSS). Previous studies have shown that PTA features enhance learners' programming performance,…
Descriptors: Programming Languages, Computer Science Education, Problem Solving, Student Motivation
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Yung-Hsiang Hu – Education and Information Technologies, 2024
In this study, a generative artificial intelligence (AI)-assisted Think-Aloud Pair Problem-Solving (TAPPS) learning strategy was introduced to support ethical dilemma-related problem-solving learning activities. Then, an interactive virtual learning companion system was developed and tested in a business ethics course to evaluate the efficacy of…
Descriptors: Ethics, Problem Solving, Thinking Skills, Verbal Communication
Vincent Aleven; Jori Blankestijn; LuEttaMae Lawrence; Tomohiro Nagashima; Niels Taatgen – Grantee Submission, 2022
Past research has yielded ample knowledge regarding the design of analytics-based tools for teachers and has found beneficial effects of several tools on teaching and learning. Yet there is relatively little knowledge regarding the design of tools that support teachers when a class of students uses AI-based tutoring software for self-paced…
Descriptors: Educational Technology, Artificial Intelligence, Problem Solving, Intelligent Tutoring Systems
Zhiwen Tang – ProQuest LLC, 2021
Artificial intelligence (AI) aims to build intelligent systems that can interact with and assist humans. During the interaction, a system learns the requirements from the human user and adapts to the needs to complete tasks. A popular type of interactive system is retrieval-based, where the system uses a retrieval function to retrieve relevant…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Objectives, Reinforcement
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Liang, Jia-Cing; Hwang, Gwo-Jen; Chen, Mei-Rong Alice; Darmawansah, Darmawansah – Interactive Learning Environments, 2023
This study explores the roles and research foci of AILEd (Artificial Intelligence in Language Education). The AILEd studies published from 1990 to 2020 in the WOS (Web of Science) database were included in the present study. Based on the well-recognized Technology-based Learning Review model, several dimensions, such as research methods, research…
Descriptors: Artificial Intelligence, Technology Uses in Education, Second Language Learning, Educational Trends
Daniel Weitekamp III; Erik Harpstead; Kenneth R. Koedinger – Grantee Submission, 2020
Intelligent tutoring systems (ITSs) have consistently been shown to improve the educational outcomes of students when used alone or combined with traditional instruction. However, building an ITS is a time-consuming process which requires specialized knowledge of existing tools. Extant authoring methods, including the Cognitive Tutor Authoring…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Instructional Design, Simulation
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Viktor Wang, Editor – IGI Global, 2025
Artificial Intelligence (AI) integration in andragogical education offers significant enhancements to the learning experience for adult learners. By utilizing AI-powered platforms, instructors can provide personalized learning paths that adapt to the unique needs, interests, and goals of each individual. These systems can analyze performance data…
Descriptors: Andragogy, Artificial Intelligence, Computer Software, Technology Integration
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Danial Hooshyar; Nour El Mawas; Yeongwook Yang – Knowledge Management & E-Learning, 2024
The use of learner modelling approaches is critical for providing adaptive support in educational computer games, with predictive learner modelling being among the key approaches. While adaptive supports have been shown to improve the effectiveness of educational games, improperly customized support can have negative effects on learning outcomes.…
Descriptors: Artificial Intelligence, Course Content, Tests, Scores
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How, Meng-Leong; Hung, Wei Loong David – Education Sciences, 2019
Artificial intelligence-enabled adaptive learning systems (AI-ALS) are increasingly being deployed in education to enhance the learning needs of students. However, educational stakeholders are required by policy-makers to conduct an independent evaluation of the AI-ALS using a small sample size in a pilot study, before that AI-ALS can be approved…
Descriptors: Stakeholders, Artificial Intelligence, Bayesian Statistics, Probability
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Behera, Ardhendu; Matthew, Peter; Keidel, Alexander; Vangorp, Peter; Fang, Hui; Canning, Susan – International Journal of Artificial Intelligence in Education, 2020
Learning involves a substantial amount of cognitive, social and emotional states. Therefore, recognizing and understanding these states in the context of learning is key in designing informed interventions and addressing the needs of the individual student to provide personalized education. In this paper, we explore the automatic detection of…
Descriptors: Nonverbal Communication, Intelligent Tutoring Systems, Eye Movements, Learning Processes
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