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Showing 1 to 15 of 27 results Save | Export
Richey, J. Elizabeth; McEldoon, Katherine; Tan, Elaine – Pearson, 2023
Pearson's Learning Foundations describe the optimal conditions for learning and reflect the learner experience Pearson hopes their products will create. Pearson does this by incorporating the Learning Design Principles. Each of the Learning Design Principles goes into detail about a key principle, supporting product design and marketing by…
Descriptors: Theory Practice Relationship, Research and Development, Individualized Instruction, Intelligent Tutoring Systems
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Da Teng; Xiangyang Wang; Yanwei Xia; Yue Zhang; Lulu Tang; Qi Chen; Ruobing Zhang; Sujin Xie; Weiyong Yu – Education and Information Technologies, 2025
The swift advancement of artificial intelligence, especially large language models (LLMs), has generated novel prospects for improving educational methodologies. Nonetheless, the successful incorporation of these technologies into pedagogical methods, such as flipped classrooms, continues to pose a challenge. This study investigates the…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Flipped Classroom, Technology Uses in Education
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Rogerson-Revell, Pamela M. – RELC Journal: A Journal of Language Teaching and Research, 2021
This viewpoint essay considers the current status of computer-assisted pronunciation training (CAPT) before examining some of the current issues and future directions in the field. The underlying premise is the pedagogic potential of CAPT systems and resources for teaching and learning, and the need for greater synergy between technological design…
Descriptors: Computer Assisted Instruction, Pronunciation Instruction, Individualized Instruction, Feedback (Response)
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Lijuan Feng – Journal of Educational Computing Research, 2025
This study investigates the impact of AI-assisted language learning (AIAL) strategies on cognitive load and learning outcomes in the context of language acquisition. Specifically, the study explores three distinct AIAL strategies: personalized feedback and adaptive learning, interactive exercises with speech recognition, and intelligent tutoring…
Descriptors: Artificial Intelligence, Computer Assisted Instruction, Second Language Learning, Second Language Instruction
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Kuhail, Mohammad Amin; Alturki, Nazik; Alramlawi, Salwa; Alhejori, Kholood – Education and Information Technologies, 2023
Chatbots hold the promise of revolutionizing education by engaging learners, personalizing learning activities, supporting educators, and developing deep insight into learners' behavior. However, there is a lack of studies that analyze the recent evidence-based chatbot-learner interaction design techniques applied in education. This study presents…
Descriptors: Educational Technology, Computer Mediated Communication, Artificial Intelligence, Technology Uses in Education
Suijing Yang; Daniel Taylor-Griffiths; Fabienne van der Kleij; Pauline Taylor-Guy; Ralph Saubern – Australian Council for Educational Research, 2025
Many existing reviews of educational technologies focus on the affordances of specific types of technology rather than how different technologies can be designed and used to achieve specific teaching and learning objectives. Furthermore, there appears to be a widely held assumption that the use of educational technology will result in improved…
Descriptors: Teacher Empowerment, Educational Technology, Technology Uses in Education, Technology Integration
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Yuan, Chia-Ching; Li, Cheng-Hsuan; Peng, Chin-Cheng – Interactive Learning Environments, 2023
Fighter jets are a critical national asset. Because of the high cost of their manufacture and that of their related equipment, both pilots and maintenance personnel must complete intensive training before coming into contact with a jet. Due to gradual military downsizing, one-on-one training is often impracticable, and the level of familiarization…
Descriptors: Artificial Intelligence, Man Machine Systems, Technology Uses in Education, Educational Technology
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Olsen, Jennifer K.; Rummel, Nikol; Aleven, Vincent – International Journal of Computer-Supported Collaborative Learning, 2019
Research on Computer-Supported Collaborative Learning (CSCL) has provided significant insights into why collaborative learning is effective and how we can effectively provide support for it. Building on this knowledge, we can investigate when collaboration is beneficial to support learning. Specifically, collaborative and individual learning are…
Descriptors: Cooperative Learning, Computer Assisted Instruction, Educational Technology, Intelligent Tutoring Systems
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Huang, Xinyi; Zou, Di; Cheng, Gary; Chen, Xieling; Xie, Haoran – Educational Technology & Society, 2023
Artificial Intelligence (AI) plays an increasingly important role in language education; however, the trends, research issues, and applications of AI in language learning remain largely under-investigated. Accordingly, the present paper, using bibliometric analysis, investigates these issues via a review of 516 papers published between 2000 and…
Descriptors: Trend Analysis, Educational Trends, Vocabulary Development, Artificial Intelligence
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Zulfiani Zulfiani; Iwan Permana Suwarna; Sujiyo Miranto – Journal of Baltic Science Education, 2018
Students with their different learning styles also have their own different learning approaches, and teachers cannot simultaneously facilitate them all. Teachers' limitation in serving all students' learning styles can be anticipated by the use of computer-based instructions. This research aims to develop ScEd-Adaptive Learning System (ScEd-ASL)…
Descriptors: Science Instruction, Cognitive Style, Intelligent Tutoring Systems, Teaching Methods
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Bernacki, Matthew L.; Walkington, Candace – Journal of Educational Psychology, 2018
Context personalization--the incorporation of students' out-of-school interests into learning tasks--has recently been shown to positively affect students' situational interest and their performance and learning in mathematics. However, few studies have shown effects on both interest and achievement, drawing into question whether context…
Descriptors: High School Students, Student Interests, Individualized Instruction, Mathematics Instruction
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Sharma Mittal, Ruhi; Nagar, Seema; Sharma, Mourvi; Dwivedi, Utkarsh; Dey, Prasenjit; Kokku, Ravi – International Educational Data Mining Society, 2018
As education gets increasingly digitized, and intelligent tutoring systems gain commercial prominence, scalable assessment generation mechanisms become a critical requirement for enabling increased learning outcomes. Assessments provide a way to measure learners' level of understanding and difficulty, and personalize their learning. There have…
Descriptors: Vocabulary Development, Language Tests, Semantics, Associative Learning
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O'Donnell, Eileen; Lawless, Séamus; Sharp, Mary; Wade, Vincent P. – International Journal of Distance Education Technologies, 2015
The realisation of personalised e-learning to suit an individual learner's diverse learning needs is a concept which has been explored for decades, at great expense, but is still not achievable by non-technical authors. This research reviews the area of personalised e-learning and notes some of the technological challenges which developers may…
Descriptors: Electronic Learning, Individualized Instruction, Programming, Authors
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Kortecamp, Karen L.; Harper, Ben; Green, Colin D. – AERA Online Paper Repository, 2016
Success in reading is often a predictor of broader school success, and children who finish elementary school with weak reading skills are at very high risk for dropping out of high school. Increasingly, early literacy programs are incorporating digital applications to enhance literacy teaching and learning. This evaluation of five teachers in…
Descriptors: Literacy Education, Teaching Methods, Technology Integration, Information Technology
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Sánchez, Inmaculada Arnedillo, Ed.; Isaias, Pedro, Ed. – International Association for Development of the Information Society, 2018
These proceedings contain the papers of the 14th International Conference on Mobile Learning 2018, which was organised by the International Association for Development of the Information Society, in Lisbon, Portugal, April 14-16, 2018. The Mobile Learning 2018 Conference seeks to provide a forum for the presentation and discussion of mobile…
Descriptors: Electronic Learning, Educational Research, Data Collection, Data Analysis
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