NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 4 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
Direct linkDirect link
Mousavinasab, Elham; Zarifsanaiey, Nahid; R. Niakan Kalhori, Sharareh; Rakhshan, Mahnaz; Keikha, Leila; Ghazi Saeedi, Marjan – Interactive Learning Environments, 2021
With the rapid growth of technology, computer learning has become increasingly integrated with artificial intelligence techniques in order to develop more personalized educational systems. These systems are known as Intelligent Tutoring systems (ITSs). This paper focused on the variant characteristics of ITSs developed across different educational…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Individualized Instruction, Web Based Instruction
Peer reviewed Peer reviewed
Direct linkDirect link
Moore, Robert L.; Oliver, Kevin M.; Wang, Chuang – Interactive Learning Environments, 2019
Learning analytics focuses on extracting meaning from large amounts of data. One of the largest datasets in education comes from Massive Open Online Courses (MOOCs) that typically feature enrollments in the tens of thousands. Analyzing MOOC discussion forums presents logistical issues, resulting chiefly from the size of the dataset, which can…
Descriptors: Cognitive Processes, Online Courses, Discussion Groups, Learning Analytics
Peer reviewed Peer reviewed
Direct linkDirect link
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