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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
Francisco Niño-Rojas; Diana Lancheros-Cuesta; Martha Tatiana Pamela Jiménez-Valderrama; Gelys Mestre; Sergio Gómez – International Journal of Education in Mathematics, Science and Technology, 2024
The use of intelligent tutoring systems (ITSs) is growing rapidly in the field of education. In mathematics, adaptive and personalized scenarios mediated by these systems have been implemented to aid concept comprehension and skill development. This study presents a systematic review on the current status of the use of ITSs in mathematics…
Descriptors: Intelligent Tutoring Systems, Higher Education, Mathematics Instruction, Teaching Methods
Jobin Jose; Alice Joselph; Pratheesh Abraham; Roshna Varghese; Beenamole T.; Sony Mary Varghese; Suby Elizabeth Oommen – Online Submission, 2024
As a major shift in education technologies, Adaptive Learning Systems (ALS) use artificial intelligence and similar technologies, adapting the lessons to the needs of individual students. Emphasizing transformative pedagogy and teaching strategies that transform the learners' cognitive and interactive patterns, this study presents a comprehensive…
Descriptors: Transformative Learning, Bibliometrics, Trend Analysis, Artificial Intelligence
Sebastian Hobert; Florian Berens – Educational Technology Research and Development, 2024
Individualized learning support is an essential part of formal educational learning processes. However, in typical large-scale educational settings, resource constraints result in limited interaction among students, teaching assistants, and lecturers. Due to this, learning success in those settings may suffer. Inspired by current technological…
Descriptors: Individualized Instruction, Intelligent Tutoring Systems, Learning Processes, Teaching Methods
David Roldan-Alvarez; Francisco J. Mesa – IEEE Transactions on Education, 2024
Artificial intelligence (AI) in programming teaching is something that still has to be explored, since in this area assessment tools that allow grading the students work are the most common ones, but there are not many tools aimed toward providing feedback to the students in the process of creating their program. In this work a small sized…
Descriptors: Intelligent Tutoring Systems, Grading, Artificial Intelligence, Feedback (Response)
Xiaoli Huang; Wei Xu; Ruijia Liu – International Journal of Distance Education Technologies, 2025
This article presents a meta-analysis of the existing literature using Stata 18.0, focusing on the effects of ITSs on learning attitudes, knowledge acquisition, learner motivation, performance, problem-solving skills, test scores, and educational outcomes across different countries and educational levels (k = 30, g = 0.86). The findings suggest…
Descriptors: Intelligent Tutoring Systems, Outcomes of Education, Learning Motivation, Student Attitudes
Jesús Pérez; Eladio Dapena; Jose Aguilar – Education and Information Technologies, 2024
In tutoring systems, a pedagogical policy, which decides the next action for the tutor to take, is important because it determines how well students will learn. An effective pedagogical policy must adapt its actions according to the student's features, such as knowledge, error patterns, and emotions. For adapting difficulty, it is common to…
Descriptors: Feedback (Response), Intelligent Tutoring Systems, Reinforcement, Difficulty Level
Melissa Lee; Chun-Wei Huang; Kelly Collins; Mingyu Feng – Grantee Submission, 2025
Math anxiety has been found to negatively correlate with math achievement, affecting students' choices to take fewer math classes and avoid math educational opportunities. Educational technology tools can ameliorate some of the negative effects of math anxiety. We examined students' math anxiety, effort in an educational technology platform, and…
Descriptors: Correlation, Mathematics Anxiety, Mathematics Achievement, Outcomes of Education
Gang Yang; Xiao-Qian Zheng; Qian Li; Miao Han; Yun-Fang Tu – Interactive Learning Environments, 2024
In Chinese, writing is a basic competency that pupils should possess. But it is still challenging for teachers to improve pupils' writing abilities. Therefore, this study proposes an intelligence-based cognitive diagnostic feedback strategy to improve pupils' writing ability and writing learning quality by analyzing their writing performance,…
Descriptors: Foreign Countries, Elementary School Students, Vocabulary Skills, Comparative Analysis
Eitemüller, Carolin; Trauten, Florian; Striewe, Michael; Walpuski, Maik – Journal of Science Education and Technology, 2023
For various reasons, students receive less formative feedback at post-secondary institutions compared to secondary school. Considering feedback as one of the most important influencing factors on learning processes, formative feedback is a promising approach to improving students' performances. In this context, new technologies, such as learning…
Descriptors: Chemistry, Science Instruction, Teaching Methods, Error Patterns
Zeyad Alshaikh – ProQuest LLC, 2021
Programming skills are a vital part of many disciplines but can be challenging to teach and learn. Thus, the programming courses are considered difficult and a major stumbling block. To overcome these challenges, students could benefit from extensive individual support such as tutoring, but there are simply not enough qualified tutors available to…
Descriptors: Questioning Techniques, Teaching Methods, Intelligent Tutoring Systems, Coding
Wijaya, Adi; Setiawan, Noor Akhmad; Shapiai, Mohd Ibrahim – Electronic Journal of e-Learning, 2023
This study aims to provide a comprehensive overview of the current state and potential future research in learning style detection. With the increasing number and diversity of research in this area, a quantitative approach is necessary to map out current themes and identify potential areas for future research. To achieve this goal, a bibliometric…
Descriptors: Bibliometrics, Cognitive Style, Diagnostic Tests, Content Analysis
Jonathan Brazil; Suijing Yang; Fabienne van der Kleij – Australian Council for Educational Research, 2025
This document provides guiding principles and practical examples for using AI in teaching and learning. Underpinned by a human-centred approach, the PATH principles serve as key guidance to ensure the ethical and effective integration of AI systems into teaching and learning. The PATH principles are: Promote teaching and learning; Advance…
Descriptors: Artificial Intelligence, Computer Software, Technology Integration, Educational Principles
Wiedbusch, Megan; Lester, James; Azevedo, Roger – Metacognition and Learning, 2023
Pedagogical agents have been designed to support the significant challenges that learners face when self-regulating in advanced learning environments. Evidence suggests differences in learners' prior skills and abilities, in conjunction with excessive didactic support, can cause overreliance on these external aids, which in turn prevents deeper…
Descriptors: Measurement Techniques, Metacognition, Learning Processes, Nonverbal Communication
Xiaxia Cao; Yao Zhao; Xiang Li – Education and Information Technologies, 2024
Various studies have been conducted on applying intelligent recognition technology, especially speech recognition technology to improve English learning ability, mostly listening and speaking. However, few studies have touched on how image-to-text recognition technology can be used for writing. The present research was conducted to fill this gap…
Descriptors: Captions, Second Language Learning, Second Language Instruction, Teaching Methods