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Ujjwal Biswas; Samit Bhattacharya – Education and Information Technologies, 2024
The application of machine learning (ML) has grown and is now used to enhance learning outcomes. In blended classroom settings, ML, emerging smartphones and wearable technologies are commonly used to improve teaching and learning. The combination of these advanced technologies and ML plays a crucial role in enhancing real-time feedback quality.…
Descriptors: Artificial Intelligence, Blended Learning, Flipped Classroom, Technology Uses in Education
Jeevan Khanal – Education and Information Technologies, 2024
The transition from traditional, in-person classrooms to technology-based models like online learning is a significant challenge. This change is not only brought on by the COVID-19 pandemic, but it also presents difficulties for low-income and developing countries that have adopted online education for students who are spread out over a wide area.…
Descriptors: Student Attitudes, Student Experience, In Person Learning, Electronic Learning
Liu, Mengchi; Yu, Dongmei – Education and Information Technologies, 2023
The prevalence of e-learning systems has made educational resources more accessible, interactive and effective to learners without the geographic and temporal boundaries. However, as the number of users increases and the volume of data grows, current e-learning systems face some technical and pedagogical challenges. This paper provides a…
Descriptors: Electronic Learning, Educational Technology, Literature Reviews, Client Server Architecture
Munshi, M.; Shrimali, Tarun; Gaur, Sanjay – Education and Information Technologies, 2023
Data mining approaches have been widely used to estimate student performance in online education. Various Machine Learning (ML) based data mining techniques have been developed to evaluate student performance accurately. However, they face specific issues in implementation. Hence, a novel hybrid Elman Neural with Apriori Mining (ENAM) approach was…
Descriptors: Academic Achievement, Electronic Learning, Technology Uses in Education, Data
Önder, Asuman; Akçapinar, Gökhan – Education and Information Technologies, 2023
The effective use of self-regulation strategies has been considered significant in online learning environments. It is known that learners must be supported in this context. Academic help-seeking (AHS), as one of the main self-regulated learning strategies, is associated with academic success. However, learners may avoid seeking help for…
Descriptors: Students, Help Seeking, Student Behavior, Learning Analytics
Cazarez, Rosa Leonor Ulloa – Education and Information Technologies, 2022
Educational institutions abruptly implemented online higher education to cope with sanitary distance restrictions in 2020, causing an increment in student failure. This negative impact attracts the analyses of online higher education as a critical issue for educational systems. The early identification of students at risk is a strategy to cope…
Descriptors: Accuracy, Grade Prediction, Academic Achievement, Electronic Learning
Al Hashlamoun, Nafeth – Education and Information Technologies, 2021
This study provides an in-depth assessment of the cultural challenges eLearners from the Gulf Corporation Council (GCC) countries face when enrolled in Western higher education institutions. The study adopts an analytical approach by identifying two themes that incorporate reviewing some of the most significant literature related to this area of…
Descriptors: Cultural Differences, Electronic Learning, Foreign Countries, Foreign Students
Murad, Dina Fitria; Heryadi, Yaya; Isa, Sani Muhamad; Budiharto, Widodo – Education and Information Technologies, 2020
The recommender system has gained research attention from education research communities mainly due to two main reasons: increasing needs for personalized learning and big data availability in the education sector. This paper presents a hybrid user-collaborative, rule-based filtering recommendation system for education context. User profiles are…
Descriptors: Automation, Online Systems, Electronic Learning, Prediction
Khamparia, Aditya; Pandey, Babita – Education and Information Technologies, 2017
In this paper we have discussed a novel method which has been developed for representation and retrieval of cases in case based reasoning (CBR) as a part of e-learning system which is based on various student features. In this approach we have integrated Artificial Neural Network (ANN) with Data mining (DM) and CBR. ANN is used to find the…
Descriptors: Case Method (Teaching Technique), Instructional Innovation, Electronic Learning, Artificial Intelligence
Kerimbayev, Nurassyl – Education and Information Technologies, 2016
In the article it was important to consider two basic moments i.e., impact mode of using virtual environment at training process within one faculty of the University, directly at training quality and what outcomes can be reached therewith. The work significance consists of studying the virtual environment effect instead of traditional educational…
Descriptors: Electronic Learning, College Instruction, Outcomes of Education, Educational Resources
Toppin, Ian N.; Toppin, Sheila M. – Education and Information Technologies, 2016
Virtual schools are a growing phenomenon in k-12 education. School systems in almost every state in the United States offer some version of fully online or blended education. It is no longer far-fetched to conclude that if the current trend continues, virtual school enrollments will eclipse those of traditional brick-and-mortar k-12 institutions…
Descriptors: Elementary Secondary Education, Electronic Learning, Institutional Characteristics, Futures (of Society)
Khaddage, Ferial; Christensen, Rhonda; Lai, Wing; Knezek, Gerald; Norris, Cathie; Soloway, Elliot – Education and Information Technologies, 2015
In this paper a review of the pedagogical, technological, policy and research challenges and concepts underlying mobile learning is presented, followed by a brief description of categories of implementations. A model Mobile learning framework and dynamic criteria for mobile learning implementations are proposed, along with a case study of one site…
Descriptors: Electronic Learning, Educational Environment, Barriers, Change Strategies
Keengwe, Jared; Onchwari, Grace; Agamba, Joachim – Education and Information Technologies, 2014
Although rapid advances in technology has allowed for the growth of collaborative e-learning experiences unconstrained by time and space, technology has not been heavily infused in the activities of teaching and learning. This article examines the theory of constructivism as well as the design of e-learning activities using constructivist…
Descriptors: Constructivism (Learning), Electronic Learning, Educational Practices, Educational Principles
Keengwe, Jared; Bhargava, Malini – Education and Information Technologies, 2014
Mobile technologies have a huge potential to transform education provided these technologies are designed and implemented in such a way that they are relevant to the social and cultural context of learning. Clearly, the application, implementation, and design of mobile technology in the global educational context pose technological and…
Descriptors: Technology Integration, Technology Uses in Education, Electronic Learning, Handheld Devices
Shippee, Micah; Keengwe, Jared – Education and Information Technologies, 2014
In the age of our mobile learning, an impending onus is placed on educational institutions to embrace this technological innovation that is widely accepted, used, and available globally. The clear societal value of mobile technology as a productivity tool for engagement, creation, and collaboration has generated a new need for education to revisit…
Descriptors: Electronic Learning, Educational Technology, Technology Integration, Handheld Devices