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Benmesbah, Ouissem; Lamia, Mahnane; Hafidi, Mohamed – Interactive Learning Environments, 2023
Adaptive learning has garnered researchers' interest. The main issue within this field is how to select appropriate learning objects (LOs) based on learners' requirements and context, and how to combine the selected LOs to form what is known as an adaptive learning path. Heuristic and metaheuristic approaches have achieved significant progress on…
Descriptors: Algorithms, Teaching Methods, Educational Innovation, Genetics
Rosmansyah, Yusep; Putro, Budi Laksono; Putri, Atina; Utomo, Nur Budi; Suhardi – Interactive Learning Environments, 2023
In this article, smart learning environment (SLE) is defined as a hybrid learning system that provides learners and other stakeholders with a joyful learning process while achieving learning outcomes as a result of the employed intelligent tools and techniques. From literature study, existing SLE models and frameworks are difficult to understand…
Descriptors: Electronic Learning, Artificial Intelligence, Educational Technology, Technology Uses in Education
Yun Tang; Zhengfan Li; Guoyi Wang; Xiangen Hu – Interactive Learning Environments, 2023
To better understand the self-regulated learning process in online learning environments, this research applied a data mining method, the two-layer hidden Markov model (TL-HMM), to explore the patterns of learning activities. We analyzed 25,818 entries of behavior log data from an intelligent tutoring system. Results indicated that students with…
Descriptors: Electronic Learning, Learning Activities, Self Management, Intelligent Tutoring Systems
S. Sageengrana; S. Selvakumar; S. Srinivasan – Interactive Learning Environments, 2024
Students are termed "multitaskers," and it is likely that they easily fall prey to other subjects or topics that most interest them. They occasionally took heed or gave close and thoughtful attention to the lectures they were on. In the current educational system, our young generations receive materials from their leftovers, and their…
Descriptors: Electronic Learning, Dropouts, Student Behavior, Student Interests
Tang, Kai-Yu; Chang, Ching-Yi; Hwang, Gwo-Jen – Interactive Learning Environments, 2023
Artificial intelligence (AI) has been widely explored across the world over the past decades. A particularly emerging topic is the application of AI in e-learning (AIeL) to improve the effectiveness of teaching and learning in precision education. This study aims to systematically review publication patterns for AIeL research with a focus on…
Descriptors: Educational Trends, Trend Analysis, Artificial Intelligence, Technology Uses in Education
Wan, Haipeng; Yu, Shengquan – Interactive Learning Environments, 2023
Most online learning researchers use resource recommendation and retrieve based on learning performance and learning style to provide accurate learning resources, but it is a closed and passive adaptive way. Learners always do not know the recommendation rationale and just receive the result-oriented recommended resources without having a chance…
Descriptors: Electronic Learning, Intelligent Tutoring Systems, Artificial Intelligence, Cognitive Mapping
Zhang, Lishan; Pan, Mengqi; Yu, Shengquan; Chen, Ling; Zhang, Jing – Interactive Learning Environments, 2023
This paper introduces a system that supports student-centered online one-to-one tutoring and evaluates the practical value of the system by running an experiment with 64 experienced mathematics teachers and 810 students in Grade 7. The experiment lasted for 50 days. A comprehensive evaluation was performed using students' academic performance…
Descriptors: Mathematics Teachers, Grade 7, Middle School Students, Middle School Teachers
Hrastinski, Stefan; Stenbom, Stefan; Benjaminsson, Simon; Jansson, Malin – Interactive Learning Environments, 2021
Although we know that asking questions is an essential aspect of online tutoring, there is limited research on this topic. The aim of this paper was to identify commonly used direct question types and explore the effects of using these question types on conversation intensity, approach to tutoring, perceived satisfaction and perceived learning.…
Descriptors: Tutors, Tutoring, Electronic Learning, Synchronous Communication
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
Chu, Hui-Chun; Chen, Jun-Ming; Tsai, Chieh-Lun – Interactive Learning Environments, 2017
Mathematics has been widely recognized as being challenging for most students. In this study, an online formative peer-tutoring approach was proposed to cope with this problem, and an online learning system was developed accordingly. To evaluate the effectiveness of the proposed approach, an experiment was conducted to explore its effects on…
Descriptors: Peer Teaching, Tutoring, Electronic Learning, Student Behavior
Tsuei, Mengping – Interactive Learning Environments, 2017
This study examined the effects of low-achieving children's use of helping tools in a synchronous mathematics peer-tutoring system on the children's mathematics learning and their learning behaviours. In a remedial class, 16 third-grade students in a remedial class engaged in peer tutoring in a face-to-face synchronous online environment during a…
Descriptors: Peer Teaching, Tutoring, Student Behavior, Low Achievement
Chae, Soo Eun; Shin, Jae-Han – Interactive Learning Environments, 2016
This study was aimed to find which tutoring styles significantly predict learners' satisfaction with an e-learning service, academic involvement, and academic achievement. The tutoring styles included subject expert, facilitator, guider, and administrator. In this study, 818 Korean sixth-grade students (ages 11-12 years), enrolled in the…
Descriptors: Foreign Countries, Tutoring, Teaching Styles, Student Satisfaction
Lim, Wei-Ying; So, Hyo-Jeong; Tan, Seng-Chee – Interactive Learning Environments, 2010
While the growing prevalence of Web 2.0 in education opens up exciting opportunities for universities to explore expansive, new literacies practices, concomitantly, it presents unique challenges. Many universities are changing from a content delivery paradigm of eLearning 1.0 to a learner-focused paradigm of eLearning 2.0. In this article, we…
Descriptors: Models, Internet, Electronic Learning, Technology Uses in Education
The Social Semantic Web in Intelligent Learning Environments: State of the Art and Future Challenges
Jovanovic, Jelena; Gasevic, Dragan; Torniai, Carlo; Bateman, Scott; Hatala, Marek – Interactive Learning Environments, 2009
Today's technology-enhanced learning practices cater to students and teachers who use many different learning tools and environments and are used to a paradigm of interaction derived from open, ubiquitous, and socially oriented services. In this context, a crucial issue for education systems in general, and for Intelligent Learning Environments…
Descriptors: Models, Interaction, Educational Technology, Design Requirements