NotesFAQContact Us
Collection
Advanced
Search Tips
Source
Education and Information…62
Audience
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Showing 1 to 15 of 62 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Yaqian Zheng; Deliang Wang; Junjie Zhang; Yanyan Li; Yaping Xu; Yaqi Zhao; Yafeng Zheng – Education and Information Technologies, 2025
Generating personalized learning pathways for e-learners is a critical issue in the field of e-learning as it plays a pivotal role in guiding learners towards the successful achievement of their learning objectives. The existing literature has proposed various methods from different perspectives to address this issue, including learner-based,…
Descriptors: Individualized Instruction, Electronic Learning, Academic Achievement, Student Educational Objectives
Peer reviewed Peer reviewed
Direct linkDirect link
Xiaoqing Xu; Wei Zhao; Yue Li; Lifang Qiao; Jinhong Tao; Fengjuan Liu – Education and Information Technologies, 2025
The success of online learning relies on college students' self-regulated learning. The common visualizations (e.g., presentation learning behaviors' frequency and duration) are widely used to enhance online self-regulated learning. But most college students still have difficulty in accurately understanding their learning patterns and…
Descriptors: Individualized Instruction, Electronic Learning, College Students, Visualization
Peer reviewed Peer reviewed
Direct linkDirect link
Yuan Liu; Yongquan Dong; Chan Yin; Cheng Chen; Rui Jia – Education and Information Technologies, 2024
The open online course (MOOC) platform has seen an increase in usage, and there are a growing number of courses accessible for people to select. An effective method is urgently needed to recommend personalized courses for users. Although the existing course recommendation models consider that users' interests change over time, they often model…
Descriptors: MOOCs, Online Courses, Models, Course Selection (Students)
Peer reviewed Peer reviewed
Direct linkDirect link
Rahayu, Nur W.; Ferdiana, Ridi; Kusumawardani, Sri S. – Education and Information Technologies, 2023
Learning path recommender systems are emerging. Given the popularity of ontology/knowledge-based systems in adaptive learning, this work reviews learning path in ontology-based recommender systems. The review covers recommendation trends, ontology use, recommendation process, recommendation technique, contributing factors, and recommender…
Descriptors: Artificial Intelligence, Learning Processes, Educational Technology, Individualized Instruction
Peer reviewed Peer reviewed
Direct linkDirect link
Smith, Bevan I.; Chimedza, Charles; Bührmann, Jacoba H. – Education and Information Technologies, 2022
Although using machine learning for predicting which students are at risk of failing a course is indeed valuable, how can we identify which characteristics of individual students contribute to their being At-Risk? By characterising individual At-Risk students we could potentially advise on specific interventions or ways to reduce their probability…
Descriptors: Individualized Instruction, At Risk Students, Intervention, Models
Peer reviewed Peer reviewed
Direct linkDirect link
Ying-Lien Lin; Wei-Tsong Wang; Min-Ju Hsieh – Education and Information Technologies, 2024
Self-regulated learning (SRL) strategies have been identified as a valuable component of digital game-based learning system (GBLS) activities. However, few studies have focused on the effects of information feedback on self-efficacy, SRL strategies, and perceived and actual learning effectiveness. Social cognitive and SRL theories describe the…
Descriptors: Self Efficacy, Self Management, Learning Strategies, Game Based Learning
Peer reviewed Peer reviewed
Direct linkDirect link
Rafael Alé-Ruiz; Fernando Martínez-Abad; María Teresa del Moral-Marcos – Education and Information Technologies, 2024
The flexible, changing, and uncertain nature of present-day society requires its citizens have new personal, professional, and social competences which exceed the traditional knowledge-based, academic skills imparted in higher education. This study aims to identify those factors associated with active methodologies that predict university…
Descriptors: Learner Engagement, Individualized Instruction, Active Learning, Higher Education
Peer reviewed Peer reviewed
Direct linkDirect link
Bellarhmouch, Youssra; Jeghal, Adil; Tairi, Hamid; Benjelloun, Nadia – Education and Information Technologies, 2023
Nowadays, the need for e-learning is amplified, especially after the COVID-19 pandemic. E-learning platforms present a solution for the continuity of the learning process. Learners are using different platforms and tools for learning. For this, it is necessary to model the learner for the personalization of the learning environment according to…
Descriptors: Electronic Learning, Educational Environment, Models, Individualized Instruction
Peer reviewed Peer reviewed
Direct linkDirect link
Lee, Jung-Chieh; Xiong, Liangnan – Education and Information Technologies, 2023
Mobile-assisted language learning (MALL) applications (apps) can provide users with personalized learning content to meet their learning needs. Besides, from the learner perspective, the apps can be regarded as 'social' individuals, like anthropomorphic instructors who offer social support to help them with language learning. However, the current…
Descriptors: Use Studies, Decision Making, Handheld Devices, Electronic Learning
Peer reviewed Peer reviewed
Direct linkDirect link
Youngjin Lee – Education and Information Technologies, 2025
This study investigates the development and evaluation of a Retrieval-Augmented Generation (RAG)-based statistics tutor designed to assist students with quantitative analysis methods. The RAG approach was employed to address the well-documented issue of hallucination in Large Language Models (LLMs). A computer tutor was developed that utilizes…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Teachers, Students
Peer reviewed Peer reviewed
Direct linkDirect link
Tong Zhou; Xingliang Wu; Yudong Wang; Yilei Wang; Shunan Zhang – Education and Information Technologies, 2024
The application of artificial intelligence in physical education (AIPE) has provided new ways to improve learning and teaching activities in physical classes. However, literature reviews that provide a systematic review and analysis of AIPE are limited. To address this gap, this study provided an overview of AIPE-related empirical research.…
Descriptors: Artificial Intelligence, Physical Education, Technology Uses in Education, Athletics
Peer reviewed Peer reviewed
Direct linkDirect link
Hao Zhang; Shihan Chen; Sen Zheng – Education and Information Technologies, 2025
Based on the instructional interaction principles outlined by Chen and Wang (2016) in third-generation distance learning, this study employs a recursive logical perspective on the evolution of the theory of interaction in distance education. It constructs a structural equation model to measure the mediating utility path of the learner's proactive…
Descriptors: Personality Traits, Assertiveness, Interaction, Distance Education
Peer reviewed Peer reviewed
Direct linkDirect link
Seongyune Choi; Hyeoncheol Kim – Education and Information Technologies, 2025
Attention to programming education from K-12 to higher education has been growing with the aim of fostering students' programming ability. This ability involves employing appropriate algorithms and computer codes to solve problems and can be enhanced through practical learning. However, in a formal educational setting, it is challenging to provide…
Descriptors: Foreign Countries, High School Freshmen, Programming, Artificial Intelligence
Peer reviewed Peer reviewed
Direct linkDirect link
Feifei Wang; Alan C. K. Cheung; Ching Sing Chai; Jin Liu – Education and Information Technologies, 2025
As learners are able to perceive interactivity when interacting with instructors or peer learners in traditional learning environments, learners are similarly able to perceive interactivity when interacting with artificial intelligence (AI) in AI-supported learning environments. Advancements in AI, such as generative AI including ChatGPT and…
Descriptors: Test Construction, Test Validity, Interaction, Artificial Intelligence
Peer reviewed Peer reviewed
Direct linkDirect link
Stefanie Vanbecelaere; Rani Van Schoors; Sohum Bhatt; Kamakshi Rajagopal; Dries Debeer; Fien Depaepe – Education and Information Technologies, 2024
This study explores the role of teachers' perceptions of digital personalised learning (DPL) tools in their intention to use and actual usage of these tools in the classroom. Utilizing the Technology Acceptance Model (TAM), we address two gaps in the literature: the limited investigation of DPL in real-world settings and the reliance on…
Descriptors: Teacher Attitudes, Individualized Instruction, Electronic Learning, Foreign Countries
Previous Page | Next Page »
Pages: 1  |  2  |  3  |  4  |  5