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Li Jin; Dawei Shang – Interactive Learning Environments, 2024
Massive open online courses (MOOC) have become important in the learning process and have been adopted in higher education, especially during the COVID-19 pandemic. However, few studies investigated MOOC continuance intention (CI) for arts disciplines. Thus, an integrated framework was proposed based on the expectation-confirmation model (ECM) and…
Descriptors: Art Education, MOOCs, Computer System Design, Continuing Education
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
Maaliw, Renato R., III – Online Submission, 2020
Most virtual learning environment fails to recognize that students have different needs when it comes to learning. With the evolving characteristics and tendencies of students, these learning environments must provide adaptation and personalization features for adaptive learning materials, course content and navigational designs to support…
Descriptors: Virtual Classrooms, Electronic Learning, Integrated Learning Systems, Individualized Instruction
Yuan, Chia-Ching; Li, Cheng-Hsuan; Peng, Chin-Cheng – Interactive Learning Environments, 2023
Fighter jets are a critical national asset. Because of the high cost of their manufacture and that of their related equipment, both pilots and maintenance personnel must complete intensive training before coming into contact with a jet. Due to gradual military downsizing, one-on-one training is often impracticable, and the level of familiarization…
Descriptors: Artificial Intelligence, Man Machine Systems, Technology Uses in Education, Educational Technology
Pardo, Abelardo; Bartimote-Aufflick, Kathryn; Shum, Simon Buckingham; Dawson, Shane; Gao, Jing; Gaševic, Dragan; Leichtweis, Steve; Liu, Danny; Martínez-Maldonado, Roberto; Mirriahi, Negin; Moskal, Adon Christian Michael; Schulte, Jurgen; Siemens, George; Vigentini, Lorenzo – Journal of Learning Analytics, 2018
The learning analytics community has matured significantly over the past few years as a middle space where technology and pedagogy combine to support learning experiences. To continue to grow and connect these perspectives, research needs to move beyond the level of basic support actions. This means exploring the use of data to prove richer forms…
Descriptors: Individualized Instruction, Data Analysis, Learning, Feedback (Response)
Kolekar, Sucheta V.; Pai, Radhika M.; M. M., Manohara Pai – Education and Information Technologies, 2019
The term Adaptive E-learning System (AES) refers to the set of techniques and approaches that are combined together to offer online courses to the learners with the aim of providing customized resources and interfaces. Most of these systems focus on adaptive contents which are generated to the learners without considering the learning styles of…
Descriptors: Computer Interfaces, Computer Assisted Instruction, Electronic Learning, Online Courses
An Early Feedback Prediction System for Learners At-Risk within a First-Year Higher Education Course
Baneres, David; Rodriguez-Gonzalez, M. Elena; Serra, Montse – IEEE Transactions on Learning Technologies, 2019
Identifying at-risk students as soon as possible is a challenge in educational institutions. Decreasing the time lag between identification and real at-risk state may significantly reduce the risk of failure or disengage. In small courses, their identification is relatively easy, but it is impractical on larger ones. Current Learning Management…
Descriptors: Prediction, Feedback (Response), At Risk Students, College Freshmen
Maaliw, Renato R., III – Online Submission, 2016
Virtual Learning Environment (VLE) such as Moodle, Blackboard, and WebCT are commonly and successfully used in E-education. While they focus on supporting educators in creating and holding online courses, they typically do not consider the individual differences of learners. However, learners have different needs and characteristics such as prior…
Descriptors: Virtual Classrooms, Electronic Learning, Integrated Learning Systems, Cognitive Style
Hsiao, I-Han – ProQuest LLC, 2012
A large number of educational resources is now made available on the Web to support both regular classroom learning and online learning. However, the abundance of available content produced at least two problems: how to help students to find the most appropriate resources and how to engage them into using these resources and benefit from them.…
Descriptors: Electronic Learning, Navigation (Information Systems), Individualized Instruction, Socialization
Johnson, L.; Adams Becker, S.; Ludgate, H.; Cummins, M.; Estrada, V. – New Media Consortium, 2012
This report presents the findings of a research project led by the New Media Consortium (NMC) and intended to inform educational leaders about significant developments in technologies supporting teaching, learning, and creative inquiry in Singaporean K-12 education. It was produced to explore emerging technologies and forecast their potential…
Descriptors: Foreign Countries, Elementary Secondary Education, Technology Uses in Education, Educational Technology
Fernandez-Lopez, Alvaro; Rodriguez-Fortiz, Maria Jose; Rodriguez-Almendros, Maria Luisa; Martinez-Segura, Maria Jose – Computers & Education, 2013
Students with special education have difficulties to develop cognitive abilities and acquire new knowledge. They could also need to improve their behavior, communication and relationships with their environment. The development of customizable and adaptable applications tailored to them provides many benefits as it helps mold the learning process…
Descriptors: Foreign Countries, Electronic Learning, Educational Needs, Student Needs
Cho, Vincent; Cheng, T. C. Edwin; Lai, W. M. Jennifer – Computers & Education, 2009
While past studies on user-interface design focused on a particular system or application using the experimental approach, we propose a theoretical model to assess the impact of perceived user-interface design (PUID) on continued usage intention (CUI) of self-paced e-learning tools in general. We argue that the impact of PUID is mediated by two…
Descriptors: Intention, Foreign Countries, Use Studies, College Students
Chen, G.D.; Chang, C.K.; Wang, C.Y. – Computers & Education, 2008
With the growing popularity of computers and the Internet, most teachers are taking advantage of Internet functions to assist in both teaching and student learning. However, students only login to the assisted learning system once or twice a week on average to surf for relevant references, participate in discussions, or hand in assignments, even…
Descriptors: Delivery Systems, Computer Interfaces, Interaction, Internet

Bork, Alfred – T.H.E. Journal, 1997
Discusses problems in education, and examines problems of computer usage. Explores how computers could lead to improvements in education with individualized learning, interactive software, computer-based courses, language-based interfaces, and distance learning. (PEN)
Descriptors: Computer Assisted Instruction, Computer Interfaces, Computer Uses in Education, Conventional Instruction
Rehak, Daniel R. – 1997
The goal of the Carnegie Mellon Online project is to build an infrastructure for delivery of courses via the World Wide Web. The project aims to deliver educational content and to assess student competency in support of courses across the Carnegie Mellon University (Pennsylvania) curriculum and beyond, thereby providing an asynchronous,…
Descriptors: Computer Interfaces, Computer Science Education, Computer System Design, Computer Uses in Education
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