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Helen Benson; Keith Heggart; Kylie A. Williams; Chloé Smit; Patrick Abela – TechTrends: Linking Research and Practice to Improve Learning, 2025
This article investigates the effectiveness of a newly developed online tool for assessing and improving the design and accessibility of Learning Management System (LMS) sites in Higher Education. The study employs a mixed-methods approach, incorporating both quantitative and qualitative data. Results from 25 subject coordinators and 3 peer…
Descriptors: Blended Learning, Learning Management Systems, Higher Education, Usability
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Emine Cabi – Education and Information Technologies, 2025
Learning Management System (LMS) can track student interactions with digital learning resources during an online learning activity. Learners with different goals, motivations and preferences may exhibit different behaviours when accessing these materials. These different behaviours may further affect their learning performance. The purpose of this…
Descriptors: Academic Achievement, Electronic Learning, Learning Management Systems, Student Behavior
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Eddy Triswanto Setyoadi; Syaad Patmanthara; Heru Wahyu Herwanto; Hartarto Junaedi; Alexander Wirapraja; Titasari Rahmawati – Electronic Journal of e-Learning, 2025
The adoption of digital learning systems is closely related to user engagement and system relevance. This quantitative research aims to explore the factors influencing students' switching intention from traditional Learning Management Systems (LMS) to a gamified LMS platform, using the Push-Pull-Mooring (PPM) framework. A conceptual model was…
Descriptors: Foreign Countries, College Students, Higher Education, Gamification
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Chaewon Lee; Lan Luo; Shelbi L. Kuhlmann; Robert D. Plumley; Abigail T. Panter; Matthew L. Bernacki; Jeffrey A. Greene; Kathleen M. Gates – Journal of Learning Analytics, 2025
The increasing use of learning management systems (LMSs) generates vast amounts of clickstream data, opening new avenues for predicting learner performance. Traditionally, LMS predictive analytics have relied on either supervised machine learning or Markov models to classify learners based on predicted learning outcomes. Machine learning excels at…
Descriptors: Electronic Learning, Prediction, Data Analysis, Artificial Intelligence
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Sonam Dhendup; Thinley Wangdi – Journal of Educators Online, 2023
This study is presented in two sections. A total of 436 students from five different colleges under the Royal University of Bhutan participated in this study. The first part involved validating the E-Learning Acceptance Measure (ELAM) proposed by Teo (2010) for its applicability in the context of the study by using Confirmatory Factor Analysis…
Descriptors: Foreign Countries, College Students, Electronic Learning, Validity
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Jamal Kay B. Rogers; Tamara Cher R. Mercado; Ronald S. Decano – Journal of Education and Learning (EduLearn), 2025
Poor academic performance remains among the most concerning educational issues, especially in higher education and online learning. To address the concern, institutions like the University of Southeastern Philippines (USeP) leverage educational data mining (EDM) techniques to generate relevant information from learning management systems (LMS)…
Descriptors: Foreign Countries, Learning Management Systems, Academic Achievement, Data Analysis
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Zulherman; Supriansyah; Desvian Bandarsyah; Mohamed Nazreen Shahul Hamid – Journal of Education and Learning (EduLearn), 2025
Online and distance learning technology with the learning management system (LMS) is an example of the application of online learning models at universities, which is the impact of technological developments. However, advances in LMS technology still need to be implemented in universities, the problem of university readiness being the main factor.…
Descriptors: Learning Management Systems, Models, Universities, Electronic Learning
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Wang, Yang – Technology, Knowledge and Learning, 2023
Learning affective state is determinate to online learning. Different affective states are associated with different online learning behaviors. Given the behavioral indicators of different affective states are still to be explored, this study constructed a data-driven online learning affective state detector by analyzing the learning log data of…
Descriptors: Electronic Learning, Affective Behavior, Learning Management Systems, Measures (Individuals)
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Yang Tian; Tak Jie Chan; Sharifah Sofiah Syed Zainudin; Farhana Muslim Mohd Jalis – Journal of Educators Online, 2025
This study aims to identify the mediating effect of collaborative learning on the relationship between Learning Management System (LMS) usage and academic performance among undergraduate students in a public university through the constructivism theory. The study employed a purposive sampling survey method, and 381 valid respondents were…
Descriptors: Learning Management Systems, Cooperative Learning, Academic Achievement, Undergraduate Students
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Yifat Davidoff; Wurud Jayusi – Education and Information Technologies, 2025
Higher Education has serious challenges regarding academic online teaching-learning-evaluation methods and tools. This study examined 980 students from diverse disciplines about their social-emotional-psychological (SEP) perceptions. We also examined the presence and desirability of 14 TLE (teaching-learning-evaluation) tools in the online…
Descriptors: Instructional Effectiveness, Electronic Learning, Learning Strategies, Student Attitudes
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Martin Ebner; Sarah Edelsbrunner; Katharina Gasplmayr; Katharina Hohla-Sejkora; Philipp Leitner; Sandra Schön; Behnam Taraghi – International Journal on E-Learning, 2025
This paper explores the challenges and first experiences of implementing federated virtual learning management within the European University Alliance "Unite!". Through the lens of Learning Tools Interoperability (LTI), the study investigates the complexities inherent in connecting Learning Management Systems (LMS) across diverse…
Descriptors: Foreign Countries, Learning Management Systems, Universities, Electronic Learning
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Gerardo Quiroz Vieyra; Luis Fernando Muñoz González – European Journal of Education (EJED), 2023
Learning Management Systems (LMS) or Learning Content Management Systems (LCMS) are the core of e-learning platforms and have evolved according to the development of new information and communication technologies. In this type of software there are many products on the market, some developed by the institutions themselves (in-house), others are…
Descriptors: Online Systems, Electronic Learning, Learning Management Systems, Artificial Intelligence
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Trgalová, Jana; Tabach, Michal – Digital Experiences in Mathematics Education, 2023
The slow uptake of technology by mathematics teachers is in contrast with the rapid growth in the availability of different digital resources specifically designed to help teaching and learning mathematics. We refer to platforms that were designed to permit for mathematical communication between multiple users. We seek to explore the affordances…
Descriptors: Affordances, Electronic Learning, Mathematics Instruction, Learning Management Systems
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Diogo Santos-Ferreira; Bruno Guimarães; Ricardo Ladeiras-Lopes; Pedro Gonçalves-Teixeira; Sílvia Oliveira Diaz; Pedro Ferreira; Francisco Gonçalves; Rita Gonçalves Cardoso; Maria Amelia Ferreira; Paulo Castro Chaves; Ricardo Fontes-Carvalho; Adelino Leite-Moreira – Advances in Physiology Education, 2024
Use of digital flashcards promotes active recall, spaced repetition, and self-assessment academic principles. This work explores the association and dose-dependent effect of this study method and locomotor (LP) and cardiovascular physiology (CP) grades. A single-faculty cohort study of medical LP and CP students was conducted, and 155 and 676…
Descriptors: Instructional Materials, Electronic Learning, Medical Education, Physiology
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Rafael Alé-Ruiz; Fernando Martínez-Abad; María Teresa del Moral-Marcos – Education and Information Technologies, 2024
The flexible, changing, and uncertain nature of present-day society requires its citizens have new personal, professional, and social competences which exceed the traditional knowledge-based, academic skills imparted in higher education. This study aims to identify those factors associated with active methodologies that predict university…
Descriptors: Learner Engagement, Individualized Instruction, Active Learning, Higher Education
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