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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
Wang, Sufen; Du, Ming; Yu, Rong; Wang, Zhijun; Sun, Jingjing; Wang, Ling – Interactive Learning Environments, 2023
It has been controversial whether the matching of learning styles with teaching environment has improved the teaching effects. This paper constructs matching modes by choosing Sternberg's three learning styles (liberal leaning, internal scope and global level) and adopts curriculum comprehensiveness and instructing modes. The research, based on…
Descriptors: Foreign Countries, Cognitive Style, Cognitive Processes, Information Processing
Li, Kam Cheong; Wong, Billy Tak-Ming – Interactive Learning Environments, 2021
This paper provides a comprehensive review of the features and trends of personalised learning. The review covers a total of 203 journal articles collected from Scopus, which were published from 2001 to 2018 and involved personalised learning practices. Comparing the practices between 2001-2009 and 2010-2018, there was a clear trend that they…
Descriptors: Individualized Instruction, Educational Trends, Literature Reviews, Technology Uses in Education
Wang, Shuai; Christensen, Claire; Cui, Wei; Tong, Richard; Yarnall, Louise; Shear, Linda; Feng, Mingyu – Interactive Learning Environments, 2023
Adaptive learning systems personalize instruction to students' individual learning needs and abilities. Such systems have shown positive impacts on learning. Many schools in the United States have adopted adaptive learning systems, and the rate of adoption in China is accelerating, reaching almost 2 million unique users for one product alone in…
Descriptors: Comparative Analysis, Teaching Methods, Intelligent Tutoring Systems, Foreign Countries
Cha, H. J.; Ahn, M. L. – Interactive Learning Environments, 2020
The aim of this study is to design and develop a user-centered, smart-tool prototype that could be used to assist teachers to practice differentiated instruction (DI) in their classrooms. This study also demonstrates how user-centered design process for the development of teacher's tools might be useful to identify system features and to…
Descriptors: Teaching Methods, Individualized Instruction, Student Centered Learning, Instructional Design
Brita-Paja, J. L.; Gregorio, C.; Llana, L.; Pareja, C.; Riesco, A. – Interactive Learning Environments, 2019
During the last years online education, in particular Massive Open Online Courses (MOOCs), has contributed to spread and popularize educational methodologies such as peer-review, automatic assessment, self-paced courses, self-evaluation, etc. Although these techniques can benefit face-to-face courses, most of them are not yet widely used in these…
Descriptors: Online Courses, Synchronous Communication, Undergraduate Study, Peer Evaluation
Zou, Di; Wang, Minhong; Xie, Haoran; Cheng, Gary; Wang, Fu Lee; Lee, Lap-Kei – Interactive Learning Environments, 2021
Personalized learning has become an important and powerful paradigm catering for various needs, styles, preferences, and modes of learning. Several methods including task recommendations and path planning have recently emerged to effectively implement personalized learning using e-learning systems. The literature shows that the use of task…
Descriptors: Linguistic Theory, Vocabulary Development, Second Language Learning, Second Language Instruction
Chen, Sherry Y.; Huang, Pei-Ren; Shih, Yu-Cheng; Chang, Li-Ping – Interactive Learning Environments, 2016
In the past decade, a number of personalized learning systems have been developed and they mainly focus on learners' prior knowledge. On the other hand, previous research suggested that gender differences and cognitive styles have great effects on student learning. To this end, this study examines how human factors, especially gender differences…
Descriptors: Prior Learning, Student Characteristics, Gender Differences, Cognitive Style
Wang, Yen-Hui – Interactive Learning Environments, 2017
The study integrated self-paced mobile learning (m-learning) into a language course, and examined what impacts were being produced on learners' reading comprehension and student satisfaction resulting from the instruction with m-learning integration. The self-paced, learner-centered mobile learning integration instruction (MLI) was compared with…
Descriptors: Telecommunications, Handheld Devices, Technology Uses in Education, Educational Technology