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Qin Ni; Yifei Mi; Yonghe Wu; Liang He; Yuhui Xu; Bo Zhang – IEEE Transactions on Learning Technologies, 2024
Learning style recognition is an indispensable part of achieving personalized learning in online learning systems. The traditional inventory method for learning style identification faces the limitations such as subject and static characteristics. Therefore, an automatic and reliable learning style recognition mechanism is designed in this…
Descriptors: Cognitive Style, Electronic Learning, Prediction, Identification
Yang, Tzu-Chi; Chen, Sherry Y. – Interactive Learning Environments, 2023
Individual differences exist among learners. Among various individual differences, cognitive styles can strongly predict learners' learning behavior. Therefore, cognitive styles are essential for the design of online learning. There are a variety of cognitive style dimensions and overlaps exist among these dimensions. In particular, Witkin's field…
Descriptors: Student Behavior, Educational Technology, Electronic Learning, Cognitive Style
Li, Kam Cheong; Wong, Billy Tak-ming – Journal of Computing in Higher Education, 2023
This paper reports a comprehensive review of literature on personalised learning in STEM and STEAM (or STE(A)M) education, which involves the disciplinary integration of Science, Technology, Engineering, and Mathematics, as well as Arts. The review covered the contexts of STE(A)M education where personalised learning was adopted, the objectives of…
Descriptors: Individualized Instruction, STEM Education, Art Education, Educational Objectives
Sun, Fu-Rong; Hu, Hong-Zhen; Wan, Rong-Gen; Fu, Xiao; Wu, Shu-Jing – Interactive Learning Environments, 2022
To determine the impact of cognitive style on change of concept of engagement in the flipped classroom, a sequential analysis from the perspective of Bloom's Taxonomy was conducted to establish if significant differences existed between the learning achievements and engagement of students with different cognitive styles. The participants were…
Descriptors: Learning Analytics, Preservice Teachers, Educational Change, Learner Engagement
Joseph, Lumy; Abraham, Sajimon; Mani, Biju P.; N., Rajesh – Journal of Educational Computing Research, 2022
A fixed learning path for all learners is a major drawback of virtual learning systems. An online learning path recommendation system has the advantage of offering flexibility to select appropriate learning content. Learning Analytics Intervention (LAI) provides several educational benefits, particularly for low-performing students. Researchers…
Descriptors: Cognitive Style, Learning Analytics, Educational Benefits, Integrated Learning Systems
Aleksandra Maslennikova; Daniela Rotelli; Anna Monreale – Journal of Learning Analytics, 2023
Students organize and manage their own learning time, choosing when, what, and how to study due to the flexibility of online learning. Each person has unique learning habits that define their behaviours and distinguish them from others. To investigate the temporal behaviour of students in online learning environments, we seek to identify suitable…
Descriptors: Learning Analytics, Online Courses, Time Management, Self Management
Han, Feifei; Pardo, Abelardo; Ellis, Robert A. – Journal of Computer Assisted Learning, 2020
This study examines the extent to which the learning orientations identified by student self-reports and the observation of their online learning events were related to each other and to their academic performance. The participants were 322 first-year engineering undergraduates, who were enrolled in a blended course. Using students' self-report on…
Descriptors: College Students, Electronic Learning, Blended Learning, Curriculum Design
Sridharan, Shwetha; Saravanan, Deepti; Srinivasan, Akshaya Kesarimangalam; Murugan, Brindha – Education and Information Technologies, 2021
There exist numerous resources online to gain the desired level of knowledge on any topic. However, this complicates the process of selecting the most appropriate resources. Every learner differs in terms of their learning speed, proficiency, and preferred mode of learning. This paper develops an adaptive learning management system to tackle this…
Descriptors: Integrated Learning Systems, Computer Assisted Instruction, Individualized Instruction, Learning Analytics
Li, Xiaoyu; Xia, Jianping – Science Insights Education Frontiers, 2020
The rise of big data technology provides direction and support for the reform and development of education. Big data technology can realize the inventory management and effective dynamic monitoring of schools, students, and teachers. It is conducive to comprehensively and accurately controlling the development of teaching activities, injecting new…
Descriptors: Foreign Countries, Middle School Students, Data Analysis, Data Collection
Tempelaar, Dirk T.; Rienties, Bart; Nguyen, Quan – Applied Cognitive Psychology, 2020
Worked-examples have been established as an effective instructional format in problem-solving practices. However, less is known about variations in the use of worked examples across individuals at different stages in their learning process in student-centred learning contexts. This study investigates different profiles of students' learning…
Descriptors: Individual Differences, Preferences, Demonstrations (Educational), Learning Analytics
Chuang, Tsung-Yen; Yeh, Martin K.-C.; Lin, Yu-Lun – Educational Technology & Society, 2021
Students with different cognitive styles benefit from different instructional strategies, including learning through playing video games. Although playing video games can be an effective learning method, we do not know its impact on the reasoning ability of students with different cognitive styles. The purposes of this study are to investigate…
Descriptors: Game Based Learning, Video Games, Computer Games, Puzzles
Aguilar, J.; Buendia, O.; Pinto, A.; Gutiérrez, J. – Interactive Learning Environments, 2022
Social Learning Analytics (SLA) seeks to obtain hidden information in large amounts of data, usually of an educational nature. SLA focuses mainly on the analysis of social networks (Social Network Analysis, SNA) and the Web, to discover patterns of interaction and behavior of educational social actors. This paper incorporates the SLA in a smart…
Descriptors: Learning Analytics, Cognitive Style, Socialization, Social Networks
Priyanka, Priyanka Gupta; Mehrotra, Deepti – Journal of Information Technology Education: Innovations in Practice, 2022
Aim/Purpose: This paper focuses on designing and implementing the rubric for objective JAVA programming assessments. An unsupervised learning approach was used to group learners based on their performance in the results obtained from the rubric, reflecting their learning ability. Background: Students' learning outcomes have been evaluated…
Descriptors: Objective Tests, Outcomes of Education, Scoring Rubrics, Programming Languages
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
Rozo, Hugo; Real, Miguel – Journal of Technology and Science Education, 2019
The present article constitutes a systematic review of the literature with the objective of identifying the appropriate elements that must be considered when designing and creating adaptive digital educational resources. The methodological process was rigorous and systematic, employing an article search in which the texts related to the object of…
Descriptors: Instructional Design, Intelligent Tutoring Systems, Instructional Materials, Educational Technology
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