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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
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Wu, Jiajun; Chen, Liwei – SAGE Open, 2022
The study proposes a frontline deliberate learning (FDL) process involving knowledge generation, knowledge articulation, and knowledge codification, which enable organizations to capture knowledge embedded in the frontlines. It examines the antecedent effects of three orientations (i.e., performance, learning, and customer orientation) at both the…
Descriptors: Models, Health Services, Knowledge Level, Learning Processes
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Lu, Yu; Chen, Penghe; Pian, Yang; Zheng, Vincent W. – IEEE Transactions on Learning Technologies, 2022
In this article, we advocate for and propose a novel concept map driven knowledge tracing (CMKT) model, which utilizes educational concept map for learner modeling. This article particularly addresses the issue of learner data sparseness caused by the unwillingness to practice and irregular learning behaviors on the learner side. CMKT considers…
Descriptors: Concept Mapping, Learning Processes, Prediction, Models
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Weikang Lu; Chenghua Lin – Asia-Pacific Education Researcher, 2025
Based on the UTAUT model, many studies have analyzed the factors influencing the use of artificial intelligence by teachers and students, but the conclusions are not uniform. This study chose high quality studies and encoded them to do meta analysis. After heterogeneity testing, sensitivity analysis and publication bias test, it has been found…
Descriptors: Meta Analysis, Technology Integration, Computer Software, Artificial Intelligence
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Kwaku Adu-Gyamfi; Kayla Chandler; Anthony Thompson – School Science and Mathematics, 2025
The challenge posed by algebra story problems creates a significant hurdle for many students, transcending both the mathematical content of the problem and the specific instructional background received. This study offers a distinctive contribution to the existing literature by focusing on the cognitive conditions essential for comprehension in…
Descriptors: Algebra, Mathematics Instruction, Barriers, Cognitive Processes
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Sonja Dieterich; Stefan Rumann; Marc Rodemer – Educational Psychology Review, 2025
Example-based learning is a well-known instructional method for effective cognitive skill acquisition in complex domains. "(Contrasting) erroneous examples" are a promising extension that embed errors in instructional material, potentially fostering not only positive but negative knowledge. However, the mechanisms and conditions for…
Descriptors: Learning Processes, Teaching Methods, Instructional Effectiveness, Models
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Somayeh B. Shafiei; Saeed Shadpour; Farzan Sasangohar; James L. Mohler; Kristopher Attwood; Zhe Jing – npj Science of Learning, 2024
The existing performance evaluation methods in robot-assisted surgery (RAS) are mainly subjective, costly, and affected by shortcomings such as the inconsistency of results and dependency on the raters' opinions. The aim of this study was to develop models for an objective evaluation of performance and rate of learning RAS skills while practicing…
Descriptors: Robotics, Surgery, Eye Movements, Medicine
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Xia, Xiaona; Qi, Wanxue – International Journal of Educational Technology in Higher Education, 2023
The temporal sequence of learning behavior is multidimensional and continuous in MOOCs. On the one hand, it supports personalized learning methods, achieves flexible time and space. On the other hand, it also makes MOOCs produce a large number of dropouts and incomplete learning behaviors. Dropout prediction and decision feedback have become an…
Descriptors: MOOCs, Dropouts, Prediction, Decision Making
Hyeon-Ah Kang; Adam Sales; Tiffany A. Whittaker – Grantee Submission, 2023
Increasing use of intelligent tutoring systems in education calls for analytic methods that can unravel students' learning behaviors. In this study, we explore a latent variable modeling approach for tracking learning flow during computer-interactive artificial tutoring. The study considers three models that give discrete profiles of a latent…
Descriptors: Intelligent Tutoring Systems, Algebra, Educational Technology, Learning Processes
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Preyanuch Kijrongrojjalearn; Luxana Keyuraphan; Narumol Soonsawad; Srimongkol Thepranoo; Tadcha Jaikwang – International Education Studies, 2025
This research aimed to develop and evaluate an innovative learning management model based on the local wisdom of the Lao Vieng community in Nakhon Nayok Province, to enhance community potential. The objectives were to 1) study the basic information on learning management innovations for local wisdom in the Lao Vieng community, 2) develop an…
Descriptors: Foreign Countries, Educational Innovation, Indigenous Knowledge, Information Management
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Osipenko, Maria – Education and Information Technologies, 2022
A data-driven model where individual learning behavior is a linear combination of certain stylized learning patterns scaled by learners' affinities is proposed. The absorption of stylized behavior through the affinities constitutes "building blocks" in the model. Non-negative matrix factorization is employed to extract common learning…
Descriptors: Behavior Patterns, Models, Undergraduate Students, Preferences
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Lachner, Andreas; Hoogerheide, Vincent; van Gog, Tamara; Renkl, Alexander – Educational Psychology Review, 2022
Teaching the contents of study materials by providing explanations to fellow students can be a beneficial instructional activity. A learning-by-teaching effect can also occur when students provide explanations to a real, remote, or even fictitious audience that cannot be interacted with. It is unclear, however, which underlying mechanisms drive…
Descriptors: Instruction, Instructional Effectiveness, Models, Educational Practices
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Xia, Xiaona – SAGE Open, 2022
Mining problems and exploring rules are the key problems in the learning process, and also the difficulties in education big data. Therefore, taking learning behavior as the research objective, this study demonstrates the collaborative training method of multi view learning interaction process driven by big data, so as to realize the tendency…
Descriptors: Learning Analytics, Learning Processes, Cooperative Learning, Training Methods
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Sharma, Meenakshi – Georgia Educational Researcher, 2022
The present article analyzes two critical frameworks within teacher education and how they construct preservice teachers and their learning within teacher education. These frameworks of 'Apprenticeship of Observation' (AoO) and 'Ambitious Practice' (AP) present opposing narratives about preservice teachers. While AoO directs our attention to…
Descriptors: Preservice Teachers, Learning, Preservice Teacher Education, Learning Processes
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Luke Strickland; Simon Farrell; Micah K. Wilson; Jack Hutchinson; Shayne Loft – Cognitive Research: Principles and Implications, 2024
In a range of settings, human operators make decisions with the assistance of automation, the reliability of which can vary depending upon context. Currently, the processes by which humans track the level of reliability of automation are unclear. In the current study, we test cognitive models of learning that could potentially explain how humans…
Descriptors: Automation, Reliability, Man Machine Systems, Learning Processes
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