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Showing 1 to 15 of 22 results Save | Export
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Ahmed Tlili; Soheil Salha; Juan Garzón; Mouna Denden; Kinshuk; Saida Affouneh; Daniel Burgos – Journal of Computer Assisted Learning, 2024
Background Study: Several meta-analysis studies have investigated the effects of mobile learning on learning performance. However, limited attention has been paid to pedagogy in mobile learning, making quantitative evidence of the effects of pedagogical approaches on learning performance in mobile learning scarce. Filling this gap can therefore…
Descriptors: Teaching Methods, Instructional Effectiveness, Electronic Learning, Student Experience
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Zheng, Lanqin; Kinshuk; Fan, Yunchao; Long, Miaolang – Education and Information Technologies, 2023
Online collaborative learning has been an effective pedagogy in the field of education. However, productive collaborative learning cannot occur spontaneously. Learners often have difficulties in collaborative knowledge building, group performance, coregulated behaviors, learning engagement, and social interaction. To promote productive…
Descriptors: Learning Analytics, Performance, Electronic Learning, Cooperative Learning
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Ghallabi, Sameh; Essalmi, Fathi; Jemni, Mohamed; Kinshuk – Smart Learning Environments, 2022
Personalized learning systems use several components in order to create courses adapted to the learners'characteristics. Current emphasis on the reduction of costs of development of new resources has motivated the reuse of the e-learning personalization components in the creation of new components. Several systems have been proposed in the…
Descriptors: Individualized Instruction, Technology Uses in Education, Electronic Learning, Mathematics
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Bacca-Acosta, Jorge; Fabregat, Ramon; Baldiris, Silvia; Kinshuk; Guevara, Juan – Journal of Computer Assisted Learning, 2022
Background: Mobile-based assessment has been an active area of research in the field of mobile learning. Prior research has demonstrated that mobile-based assessment systems positively affect student performance. However, it is still unclear why and how these systems positively affect student performance. Objectives: This study aims to identify…
Descriptors: Academic Achievement, Electronic Learning, Handheld Devices, Computer Assisted Testing
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Yan, Hongxin; Lin, Fuhua; Kinshuk – International Journal of Artificial Intelligence in Education, 2021
Online education is growing because of its benefits and advantages that students enjoy. Educational technologies (e.g., learning analytics, student modelling, and intelligent tutoring systems) bring great potential to online education. Many online courses, particularly in self-paced online learning (SPOL), face some inherent barriers such as…
Descriptors: Learning Analytics, Independent Study, Online Courses, Electronic Learning
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Yan, Hongxin; Lin, Fuhua; Kinshuk – Canadian Journal of Learning and Technology, 2022
Self-paced online learning provides great flexibility for learning, yet it brings some inherent learning barriers because of the nature of this educational paradigm. This review paper suggests some corresponding strategies to address these barriers in order to create a more supportive self-paced online learning environment. These strategies…
Descriptors: Electronic Learning, Individualized Instruction, Educational Strategies, Barriers
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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
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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
Lan, Chung-Hsien; Chao, Stefan; Kinshuk; Chao, Kuo-Hung – International Association for Development of the Information Society, 2013
This study presents a conceptual framework for supporting mobile peer assessment by incorporating augmented reality technology to eliminate limitation of reviewing and assessing. According to the characteristics of mobile technology and augmented reality, students' work can be shown in various ways by considering the locations and situations. This…
Descriptors: Peer Evaluation, Electronic Learning, Computer Simulation, Undergraduate Students
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Kinshuk; Jesse, Ryan – International Review of Research in Open and Distance Learning, 2013
E-learning technologies have allowed authoring and playback of standardized reusable learning objects (RLO) for several years. Effective mobile learning requires similar functionality at both design time and runtime. Mobile devices can play RLO using applications like SMILE, mobile access to a learning management system (LMS), or other systems…
Descriptors: Foreign Countries, Electronic Learning, Educational Technology, Resource Units
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Lu, Chris; Chang, Maiga; Kinshuk; Huang, Echo; Chen, Ching-Wen – Educational Technology & Society, 2014
The research presented in this paper is part of a 5-year renewable national research program in Canada, namely the NSERC/iCORE/Xerox/Markin research chair program that aims to explore possibilities of adaptive mobile learning and to provide learners with a learning environment which facilitates personalized learning at any time and any place. One…
Descriptors: Foreign Countries, Educational Games, Role Playing, Electronic Learning
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Mac Callum, Kathryn; Jeffrey, Lynn; Kinshuk – Journal of Information Technology Education: Research, 2014
As mobile technology has advanced, awareness is growing that these technologies may benefit teaching and learning. However, despite this interest, the factors that will determine the acceptance of mobile technology by lecturers have been limited. This study proposed and tested a new model that extends the technology acceptance model (TAM) with…
Descriptors: Adoption (Ideas), Electronic Learning, Performance Factors, Technological Literacy
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Sridharan, Bhavani; Deng, Hepu; Kinshuk – Issues in Educational Research, 2014
Developing sustainable e-learning requires a better understanding of the perceptions and preferences of e-learning providers and e-learners on the four crucial dimensions for elearning success including pedagogies, technologies, learning resources and management of learning resources. There is, however, little research on evaluating whether these…
Descriptors: Electronic Learning, Sustainability, Preferences, Investigations
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Wen, Dunwei; Cuzzola, John; Brown, Lorna; Kinshuk – International Review of Research in Open and Distance Learning, 2012
Question answering systems have frequently been explored for educational use. However, their value was somewhat limited due to the quality of the answers returned to the student. Recent question answering (QA) research has started to incorporate deep natural language processing (NLP) in order to improve these answers. However, current NLP…
Descriptors: Language Processing, Natural Language Processing, Distance Education, Online Courses
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Chen, Nian-Shing; Kinshuk; Wei, Chun-Wang; Liu, Chia-Chi – Computers & Education, 2011
Reflection plays an important role in improving learning performance. This study, therefore, attempted to explore whether learners' reflection levels can be improved if teaching strategies are adapted to fit with learners' thinking styles in an online learning environment. Three teaching strategies, namely constructive, guiding, and inductive,…
Descriptors: Undergraduate Students, Graduate Students, Educational Environment, Thinking Skills
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