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Showing 1 to 15 of 82 results Save | Export
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Xiaorui Wang; Chao Liu; Jing Guo – International Journal of Web-Based Learning and Teaching Technologies, 2025
This research works on creating a hybrid Knowledge Recommendation System (KRS) for an Entrepreneurship Course using the Knowledge Graph (KG) and Clustering Technologies (CTs). The system aims at improving students' learning experience by providing relevant learning materials and even focusing on learner preferences. These results are already part…
Descriptors: Entrepreneurship, Individualized Instruction, Learning Experience, Feedback (Response)
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Joanna Vance – Journal of Faculty Development, 2025
This article explores how Los Angeles Pacific University (LAPU) uses its AI tool, Spark, to enhance student learning. Spark personalizes the learning experience, offers 24/7 tutoring, and fosters collaboration, leading to improved academic performance. The tool complements traditional teaching, providing equitable, accessible support to students…
Descriptors: Artificial Intelligence, Technology Uses in Education, Cooperation, Individualized Instruction
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Ilana Ram; Sara Harris; Ido Roll – International Journal of Artificial Intelligence in Education, 2024
Personalization in education describes instruction that is tailored to learners' interests, attributes, or background and can be applied in various ways, one of which is through choice. In choice-based personalization, learners choose topics or resources that fit them the most. Personalization may be especially important (and under-used) with…
Descriptors: MOOCs, Individualized Instruction, Student Interests, Active Learning
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Fatema Al Nabhani; Mahizer Bin Hamzah; Hassan Abuhassna – Contemporary Educational Technology, 2025
This study sought to investigate the effects of employing artificial intelligence (AI) on the customization of educational content and the enhancement of academic performance and engagement among students and teachers. The research involved a sample of ninth-grade students and their educators from diverse subjects, utilizing questionnaires to…
Descriptors: Artificial Intelligence, Technology Uses in Education, Individualized Instruction, Learning Experience
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Kumar, Raja S. – Journal of Educational Technology, 2023
This paper explores the concept of Flipped Mastery as an innovative approach to education that allows for the customization of learning experiences to meet each student's unique needs and preferences. To create a student-centered and personalised educational environment, Flipped Mastery blends the ideas of flipped learning with mastery-based…
Descriptors: Flipped Classroom, Mastery Learning, Individualized Instruction, Learning Experience
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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Gibbs, Kathryn – Australian Educational Researcher, 2023
This paper investigates the challenges experienced by some Australian school educators in implementing differentiated instruction (DI) at a large secondary school. A small-scale study was conducted using individual, semi-structured interviews with teachers and school leaders. Using thematic analysis, three major themes were identified, namely:…
Descriptors: Individualized Instruction, Learning Experience, Secondary Schools, Program Implementation
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Kaplan, Sandra N. – Gifted Child Today, 2023
This article discusses various key words that facilitate differentiated curricular experiences for gifted students. Key words such as "about," "in," "from," and "with" can present a different perspective on the learning experience and stimulate investigative behaviors. They are also a set of words that are…
Descriptors: Gifted Education, Language Usage, Learning Experience, Educational Experience
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Hao Zhou; Wenge Rong; Jianfei Zhang; Qing Sun; Yuanxin Ouyang; Zhang Xiong – IEEE Transactions on Learning Technologies, 2025
Knowledge tracing (KT) aims to predict students' future performances based on their former exercises and additional information in educational settings. KT has received significant attention since it facilitates personalized experiences in educational situations. Simultaneously, the autoregressive (AR) modeling on the sequence of former exercises…
Descriptors: Learning Experience, Academic Achievement, Data, Artificial Intelligence
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Thiemo Wambsganss; Ivo Benke; Alexander Maedche; Kenneth Koedinger; Tanja Käser – International Journal of Artificial Intelligence in Education, 2025
Conversational tutoring systems (CTSs) offer a promising avenue for individualized learning support, especially in domains like persuasive writing. Although these systems have the potential to enhance the learning process, the specific role of learner control and inter- activity within them remains underexplored. This paper introduces…
Descriptors: Learner Controlled Instruction, Interaction, Intelligent Tutoring Systems, Persuasive Discourse
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Hon Keung Yau; Ka Fai Tung – Turkish Online Journal of Educational Technology - TOJET, 2025
This study explores the development and evaluation of a chatbot model designed to facilitate learning within a department of a university. The project aims to enhance the learning experience by incorporating customized data into the chatbot's knowledge base, enabling personalized and context-aware interactions. The research investigates the…
Descriptors: Instructional Effectiveness, Artificial Intelligence, Computer Software, Technology Integration
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Jahnke, Isa – International Journal of Information and Learning Technology, 2023
Purpose: Fischer "et al." (2022) present a framework for rethinking education, including broad design components such as learning-on-demand or learning takes place in the context of authentic problems. How can we bring those design components into practice? I argue that the design of innovative learning approaches for the digital age…
Descriptors: Electronic Learning, Learning Experience, Instructional Design, Evaluation Methods
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Fatima Rahioui; Mohammed Ali Tahri Jouti; Mohammed El Ghzaoui – Journal of Educators Online, 2024
Artificial intelligence (AI) is now affecting all aspects of our social lives. Without always knowing it, we interact daily with intelligent systems. They serve us invisibly. At least that is the goal we assign to them: to make our lives better, task by task. Artificial intelligence has the potential to make biology education more engaging,…
Descriptors: Artificial Intelligence, Biological Sciences, Scientific Concepts, Technology Integration
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Sonia J. Ferns; Karsten E. Zegwaard; T. Judene Pretti; Anna D. Rowe – Higher Education Research and Development, 2025
The scope of work-integrated learning (WIL) has expanded and evolved globally and is a recognised pedagogy that enhances graduate employability, strengthens students' personal attributes, and affords a personalised learning experience. Despite abundant research and discourse on WIL, misconceptions about what WIL is and how WIL educative…
Descriptors: Curriculum Design, Work Based Learning, Stakeholders, Global Approach
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Nagaletchimee Annamalai; Darwalis Sazan – Educational Process: International Journal, 2025
Background/purpose: This study examines integrating the VARK learning style model into Learning Management Systems (LMS) to create more personalized learning experiences. The VARK model classifies the learners as Visual, Auditory, Reading, Writing, or Kinesthetic, enabling tailored instructional strategies. Materials/methods: By employing an…
Descriptors: Student Attitudes, Preferences, Cognitive Style, Learning Strategies
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