NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 10 results Save | Export
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
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
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
Troussas, Christos; Chrysafiadi, Konstantina; Virvou, Maria – Education and Information Technologies, 2021
Personalized computer-based tutoring demands learning systems and applications that identify and keep personal characteristics and features for each individual learner. This is achieved by the technology of student modeling. One prevalent technique of student modeling is stereotypes. Furthermore, individuals differ in how they learn. So, the way…
Descriptors: Individualized Instruction, Intelligent Tutoring Systems, Cognitive Style, Stereotypes
Peer reviewed Peer reviewed
Direct linkDirect link
Ghallabi, Sameh; Essalmi, Fathi; Jemni, Mohamed; Kinshuk – Education and Information Technologies, 2020
With the emergence of technology, the personalization of e-learning systems is enhanced. These systems use a set of parameters for personalizing courses. However, in literature, these parameters are not based on classification and optimization algorithms to implement them in the cloud. Cloud computing is a new model of computing where standard and…
Descriptors: Electronic Learning, Internet, Information Storage, Models
Peer reviewed Peer reviewed
Direct linkDirect link
Liu, Xinyang; Ardakani, Saeid Pourroostaei – Education and Information Technologies, 2022
The purpose of this study is to propose an e-learning system model for learning content personalisation based on students' emotions. The proposed system collects learners' brainwaves using a portable Electroencephalogram and processes them via a supervised machine learning algorithm, named K-nearest neighbours (KNN), to recognise real-time…
Descriptors: Foreign Countries, Undergraduate Students, Electronic Learning, Artificial Intelligence
Peer reviewed Peer reviewed
Direct linkDirect link
Maussumbayev, Rysbek; Toleubekova, Rymshash; Kaziyev, Karas; Baibaktina, Axaule; Bekbauova, Altynshash – Education and Information Technologies, 2022
The aim of this article is to theoretically and practically justify the development of a future social pedagogue's research capacity in the context of digital technologies. Practical implementation of a model for building social pedagogues' research capacity within the framework of an online educational course can provide effective training of…
Descriptors: Educational Research, Educational Technology, Capacity Building, Online Courses
Peer reviewed Peer reviewed
Direct linkDirect link
Tortorella, Richard A. W.; Kinshuk; Chen, Nian-Shing – Education and Information Technologies, 2018
Today people learn in many diverse locations and contexts, beyond the confines of classical brick and mortar classrooms. This trend is ever increasing, progressing hand-in-hand with the progress of technology. Context-aware learning systems are systems which adapt to the learner's context, providing tailored learning for a particular learning…
Descriptors: Electronic Learning, Educational Technology, Context Effect, Models
Peer reviewed Peer reviewed
Direct linkDirect link
Van Laer, Stijn; Elen, Jan – Education and Information Technologies, 2017
Blended forms of learning have become increasingly popular. Learning activities within these environments are supported by a large variety of online and face-to-face interventions. However, it remains unclear whether these blended environments are successful, and if they are, what makes them successful. Studies suggest that blended learning…
Descriptors: Blended Learning, Self Management, Educational Research, Individualized Instruction
Peer reviewed Peer reviewed
Direct linkDirect link
Fasihuddin, Heba; Skinner, Geoff; Athauda, Rukshan – Education and Information Technologies, 2017
Open learning represents a new form of online learning where courses are provided freely online for large numbers of learners. MOOCs are examples of this form of learning. The authors see an opportunity for personalising open learning environments by adapting to learners' learning styles and providing adaptive support to meet individual learner…
Descriptors: Online Courses, Open Education, Individualized Instruction, Cognitive Style