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Bayounes, Walid; Saâdi, Ines Bayoudh; Kinsuk – Smart Learning Environments, 2022
The goal of ITS is to support learning content, activities, and resources, adapted to the specific needs of the individual learner and influenced by learner's motivation. One of the major challenges to the mainstream adoption of adaptive learning is the complexity and time involved in guiding the learning process. To tackle these problems, this…
Descriptors: Learning Processes, Learning Motivation, Individualized Instruction, Models
Mao, Shun; Zhan, Jieyu; Wang, Yizhao; Jiang, Yuncheng – IEEE Transactions on Learning Technologies, 2023
For offering adaptive learning to learners in intelligent tutoring systems, one of the fundamental tasks is knowledge tracing (KT), which aims to assess learners' learning states and make prediction for future performance. However, there are two crucial issues in deep learning-based KT models. First, the knowledge concepts are used to predict…
Descriptors: Intelligent Tutoring Systems, Learning Processes, Prediction, Prior Learning
von Leipzig, Tanja; Lutters, Eric; Hummel, Vera; Schutte, Cornè – International Journal of Game-Based Learning, 2022
Dynamic personalization of learning trajectories that integrate different perspectives and variable scenarios is a viable way to improve the effectiveness and efficiency of training and education. Serious games offer a designated platform for this, by aggregating learner interactions, and using these to dynamically configure, adjust and tailor the…
Descriptors: Educational Games, Game Based Learning, Individualized Instruction, Instructional Design
Jamal Eddine Rafiq; Abdelali Zakrani; Mohammed Amraouy; Said Nouh; Abdellah Bennane – Turkish Online Journal of Distance Education, 2025
The emergence of online learning has sparked increased interest in predicting learners' academic performance to enhance teaching effectiveness and personalized learning. In this context, we propose a complex model APPMLT-CBT which aims to predict learners' performance in online learning settings. This systemic model integrates cognitive, social,…
Descriptors: Models, Online Courses, Educational Improvement, Learning Processes
Li, Xiao; Xu, Hanchen; Zhang, Jinming; Chang, Hua-hua – Journal of Educational and Behavioral Statistics, 2023
The adaptive learning problem concerns how to create an individualized learning plan (also referred to as a learning policy) that chooses the most appropriate learning materials based on a learner's latent traits. In this article, we study an important yet less-addressed adaptive learning problem--one that assumes continuous latent traits.…
Descriptors: Learning Processes, Models, Algorithms, Individualized Instruction
Bander Ayed Allogmany – ProQuest LLC, 2023
Advances in data analytics and intelligent technologies are enabling smart learning environments that promote personalized learning. Personalized learning systems where learners engage with information in a manner tailored to their unique needs, goals, and abilities have garnered significant academic research attention. If students can achieve…
Descriptors: Individualized Instruction, Learning Management Systems, Artificial Intelligence, Technology Uses in Education
Lluch Molins, Laia; Cano García, Elena – Journal of New Approaches in Educational Research, 2023
One of the main generic competencies in Higher Education is "Learning to Learn". The key component of this competence is the capacity for self-regulated learning (SRL). For this competence to be developed, peer feedback seems useful because it fosters evaluative judgement. Following the principles of peer feedback processes, an online…
Descriptors: Learning Analytics, Learning Management Systems, Peer Evaluation, Higher Education
Zhou, Yuhao; Li, Xihua; Cao, Yunbo; Zhao, Xuemin; Ye, Qing; Lv, Jiancheng – International Educational Data Mining Society, 2021
In educational applications, "Knowledge Tracing" (KT) has been widely studied for decades as it is considered a fundamental task towards adaptive online learning. Among proposed KT methods, Deep Knowledge Tracing (DKT) and its variants are by far the most effective ones due to the high flexibility of the neural network. However, DKT…
Descriptors: Online Courses, Computer Assisted Instruction, Networks, Learning Analytics
Soboleva, Elena V.; Zhumakulov, Khurshidzhon K.; Umurkulov, Kayumzhon P.; Ibragimov, Gasanguseyn I.; Kochneva, Lyubov V.; Timofeeva, Maria O. – EURASIA Journal of Mathematics, Science and Technology Education, 2022
The lack of sufficiently developed methodological basis before graduation adversely affects the mathematical competency of future experts that are required by the modern economy. The study aims to investigate the features of the development of a personalized model of teaching mathematics by means of interactive novels to improve the quality of…
Descriptors: Mathematics Instruction, Teaching Methods, Novels, Mathematics Skills
Guinibert, Matthew – Australasian Journal of Educational Technology, 2020
Based on the presupposition that visual literacy skills are not usually learned unaided by osmosis, but require targeted learning support, this article explores how everyday encounters with visuals can be leveraged as contingent learning opportunities. The author proposes that a learner's environment can become a visual learning space if…
Descriptors: Visual Literacy, Telecommunications, Handheld Devices, Informal Education
Kucirkova, Natalia; Littleton, Karen – Learning, Media and Technology, 2017
Massive open online courses (MOOCs) are online courses aimed at global unlimited participation, originally conceptualised to carry no fee and offer no formal accreditation to the students (McAuley et al. 2010). Although their pedagogies vary, the most popular MOOC providers (e.g., Coursera, FutureLearn and EdX) are turning towards what Rodriguez…
Descriptors: Online Courses, Models, Educational Practices, Educational Methods
Alhasan, Khawla; Chen, Liming; Chen, Feng – International Association for Development of the Information Society, 2017
Various learners with various requirements have led to the raise of a crucial concern in the area of e-learning. A new technology for propagating learning to learners worldwide, has led to an evolution in the e-learning industry that takes into account all the requirements of the learning process. In spite of the wide growing, the e-learning…
Descriptors: Semantics, Models, Cognitive Style, Electronic Learning
Blumenstein, Marion – Journal of Learning Analytics, 2020
The field of learning analytics (LA) has seen a gradual shift from purely data-driven approaches to more holistic views of improving student learning outcomes through data-informed learning design (LD). Despite the growing potential of LA in higher education (HE), the benefits are not yet convincing to the practitioner, in particular aspects of…
Descriptors: Learning Analytics, Instructional Design, Effect Size, Higher Education
Zou, Di; Wang, Minhong; Xie, Haoran; Cheng, Gary; Wang, Fu Lee; Lee, Lap-Kei – Interactive Learning Environments, 2021
Personalized learning has become an important and powerful paradigm catering for various needs, styles, preferences, and modes of learning. Several methods including task recommendations and path planning have recently emerged to effectively implement personalized learning using e-learning systems. The literature shows that the use of task…
Descriptors: Linguistic Theory, Vocabulary Development, Second Language Learning, Second Language Instruction
Clement, Benjamin; Oudeyer, Pierre-Yves; Lopes, Manuel – International Educational Data Mining Society, 2016
Online planning of good teaching sequences has the potential to provide a truly personalized teaching experience with a huge impact on the motivation and learning of students. In this work we compare two main approaches to achieve such a goal, POMDPs that can find an optimal long-term path, and Multi-armed bandits that optimize policies locally…
Descriptors: Intelligent Tutoring Systems, Markov Processes, Models, Teaching Methods