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Saksri Suebsing; Nithinath Udomsun; Supimon Boonphok – Journal of Education and Learning, 2025
The purpose of this research is to develop the learning management model of early childhood teachers in Roi Et Province. The sample group includes early childhood teachers is obtained by selecting a simple random sample of the sample 400 people. The tools used in the research include questionnaires assessment form and learning quizzes for Primary…
Descriptors: Early Childhood Teachers, Teacher Attitudes, Instructional Effectiveness, Models
Uckarajade Sihawong; Songsak Phusee-orn – Journal of Education and Learning, 2024
This study pursues a comprehensive tripartite agenda: firstly, to investigate the essential requisites for formulating a model geared towards augmenting teachers' 21st century learning management competencies; secondly, to design a tailored model aligned with these competencies; and thirdly, to scrutinize the tangible impact of model…
Descriptors: Junior High School Teachers, 21st Century Skills, Stakeholders, Models
Michael Wade Ashby – ProQuest LLC, 2024
Whether machine learning algorithms effectively predict college students' course outcomes using learning management system data is unknown. Identifying students who will have a poor outcome can help institutions plan future budgets and allocate resources to create interventions for underachieving students. Therefore, knowing the effectiveness of…
Descriptors: Artificial Intelligence, Algorithms, Prediction, Learning Management Systems
Aïcha Bakki; Lahcen Oubahssi; Youness Laghouaouta; Sébastien George – Interactive Learning Environments, 2024
Business Process Model and Notation (BPMN) is a standard formalism for business process modeling that is very popular in professional practices due to its expressiveness, the well-defined meta-model, and its easiness of use by non-technical users. For instance, BPMN2.0 is used for business processes in commercial areas such as banks, shops,…
Descriptors: MOOCs, Learning Management Systems, Business Education, Models
Meriem Zerkouk; Miloud Mihoubi; Belkacem Chikhaoui; Shengrui Wang – Education and Information Technologies, 2024
School dropout is a significant issue in distance learning, and early detection is crucial for addressing the problem. Our study aims to create a binary classification model that anticipates students' activity levels based on their current achievements and engagement on a Canadian Distance learning Platform. Predicting student dropout, a common…
Descriptors: Artificial Intelligence, Dropouts, Prediction, Distance Education
Xinyu Li; Yizhou Fan; Tongguang Li; Mladen Rakovic; Shaveen Singh; Joep van der Graaf; Lyn Lim; Johanna Moore; Inge Molenaar; Maria Bannert; Dragan Gaševic – Journal of Learning Analytics, 2025
The focus of education is increasingly on learners' ability to regulate their own learning within technology-enhanced learning environments. Prior research has shown that self-regulated learning (SRL) leads to better learning performance. However, many learners struggle to productively self-regulate their learning, as they typically need to…
Descriptors: Learning Analytics, Metacognition, Independent Study, Skill Development
Marc Burchart; Joerg M. Haake – IEEE Transactions on Learning Technologies, 2024
In distance education courses with a large number of students and groups, the organization and facilitation of collaborative writing tasks are challenging. Teachers need support for planning, specification, execution, monitoring, and evaluation of collaborative writing tasks in their course. This requires a collaborative learning platform for…
Descriptors: Writing Instruction, Distance Education, Large Group Instruction, Learning Management Systems
Hoa-Huy Nguyen; Kien Do Trung; Loc Nguyen Duc; Long Dang Hoang; Phong Tran Ba; Viet Anh Nguyen – Education and Information Technologies, 2024
This article presents the results of an experiment in personalizing course content and learning activity model tailored for online courses based on students' learning styles. The main research objectives are to design and pilot a model to determine students' learning styles to create personalized online courses. The study also addressed an…
Descriptors: Models, Online Courses, Cognitive Style, Classification
Anneli Dyrvold; Ida Bergvall – Scandinavian Journal of Educational Research, 2024
This article explores how seven Swedish digital teaching platforms in mathematics make use of the affordances provided by various modalities and dynamic functions. A model based on social semiotics is used to analyse how dynamic functions are used, whether or not the language is technically oriented, if relational or operational processes are…
Descriptors: Foreign Countries, Mathematics Instruction, Teaching Methods, Learning Management Systems
Huili Zhang; Guoliang Xu – International Journal of Web-Based Learning and Teaching Technologies, 2025
The process of building a teaching platform for contemporary Chinese literature poses many challenges. Based on big data research, this study was conducted using diversified intelligent analysis technology and theory. Through a fuzzy analytic hierarchy process method and relevant steps regarding intelligent parameter improvement, this study…
Descriptors: Multiple Intelligences, Foreign Countries, Chinese, Literature
Md Akib Zabed Khan; Agoritsa Polyzou – Journal of Educational Data Mining, 2024
In higher education, academic advising is crucial to students' decision-making. Data-driven models can benefit students in making informed decisions by providing insightful recommendations for completing their degrees. To suggest courses for the upcoming semester, various course recommendation models have been proposed in the literature using…
Descriptors: Academic Advising, Courses, Data Use, Artificial Intelligence
Thuy Dung Pham Thi; Nam Tien Duong – Education and Information Technologies, 2024
With the explosive growth of various applications on the Internet, higher education institutions have advocated distance learning courses, making research on online learning increasingly important. This study attempts to emphasize the characteristics of instruction in online learning systems, using the Theory of Planned Behavior. Two groups of…
Descriptors: Electronic Learning, College Students, Behavior Theories, Intention
Hua Ma; Wen Zhao; Yuqi Tang; Peiji Huang; Haibin Zhu; Wensheng Tang; Keqin Li – IEEE Transactions on Learning Technologies, 2024
To prevent students from learning risks and improve teachers' teaching quality, it is of great significance to provide accurate early warning of learning performance to students by analyzing their interactions through an e-learning system. In existing research, the correlations between learning risks and students' changing cognitive abilities or…
Descriptors: College Students, Learning Analytics, Learning Management Systems, Academic Achievement
Saba Sareminia; Vida Mohammadi Dehcheshmeh – International Journal of Information and Learning Technology, 2024
Purpose: Although E-learning has been in use for over two decades, running parallel to traditional learning systems, it has gained increased attention due to its vital role in universities in the wake of the COVID-19 pandemic. The primary challenge within E-learning pertains to the maintenance of sustainable effectiveness and the assurance of…
Descriptors: Educational Improvement, Electronic Learning, Personality Traits, Models
Longwei Zheng; Tong Liu; Yuanyuan Feng; Xiaoqing Gu; Ming-Hua Yu – SAGE Open, 2024
Understanding the teacher's technology adoption process is essential to comprehend and narrow the digital divide in the post-epidemic age. During the pandemic, the stay-at-home orders not only intervened schooling and teaching but also increased digital accessibility to teachers. This research studies teacher heterogeneity and adoption controls in…
Descriptors: COVID-19, Pandemics, Technology Integration, Technology Uses in Education