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Guoqian Luo; Hengnian Gu; Xiaoxiao Dong; Dongdai Zhou – Education and Information Technologies, 2025
In the realm of e-learning, supporting personalized learning effectively necessitates recommending sequences of learning items that maximize learning efficiency while minimizing cognitive load, all tailored to the learner's goals. These recommendations must account for the prerequisite relationships among learning items and the learner's…
Descriptors: Electronic Learning, Individualized Instruction, Sequential Learning, Learning Processes
Stephen Ferrigno; Samuel J. Cheyette; Susan Carey – Cognitive Science, 2025
Complex sequences are ubiquitous in human mental life, structuring representations within many different cognitive domains--natural language, music, mathematics, and logic, to name a few. However, the representational and computational machinery used to learn abstract grammars and process complex sequences is unknown. Here, we used an artificial…
Descriptors: Sequential Learning, Cognitive Processes, Knowledge Representation, Training
Yiqiu Zhou; Jina Kang; Yeyu Wang; Muhammad Ashiq – Educational Technology Research and Development, 2025
The complex processes of collaborative knowledge construction require a multimodal approach to capture the interplay between learners, tools, and the environment. While existing studies have recognized the importance of considering multiple modalities, there remains a need for a comprehensive framework that explicitly models the dynamics of…
Descriptors: Cooperative Learning, Computer Simulation, Astronomy, Network Analysis
Özlem Üzümcü – Journal of Educational Technology and Online Learning, 2023
This study aims to investigate the process of designing infographics through participants' knowledge construction in the assessment and evaluation process of IB Educator Certificate (IBEC) educational technologies education. The study, in which the case study method was used, was conducted with 12 participants who attended the educational…
Descriptors: Visual Aids, Assignments, Knowledge Representation, Educational Technology
Nguyen, Huy; Wang, Yeyu; Stamper, John; McLaren, Bruce M. – International Educational Data Mining Society, 2019
Knowledge components (KCs) define the underlying skill model of intelligent educational software, and they are critical to understanding and improving the efficacy of learning technology. In this research, we show how learning curve analysis is used to fit a KC model--one that was created after use of the learning technology--which can then be…
Descriptors: Middle School Students, Knowledge Representation, Models, Computer Games
Aldridge, David – Educational Theory, 2018
This article by David Aldridge concerns the promise of knowledge "insertion." The promise can be elucidated as follows: knowledge could be inserted by a less time-consuming (and possibly in many senses less expensive) technological process than traditional learning, whereby, for example, some relatively swift procedure of implanting or…
Descriptors: Technology Uses in Education, Brain, Epistemology, Learning Processes
Nitchot, Athitaya; Wettayaprasit, Wiphada; Gilbert, Lester – E-Learning and Digital Media, 2019
The aim of this research is to introduce a method of constructing knowledge structures which represent the relationships among the knowledge items in a pedagogically useful way. A prototype, "MyTeLeMap," was implemented to support both learners and instructors. Learners could visualize the knowledge structures of different knowledge…
Descriptors: Individualized Instruction, Visualization, Learning Processes, Cognitive Structures
Rau, Martina Angela – International Journal of Artificial Intelligence in Education, 2017
Traditional knowledge-component models describe students' content knowledge (e.g., their ability to carry out problem-solving procedures or their ability to reason about a concept). In many STEM domains, instruction uses multiple visual representations such as graphs, figures, and diagrams. The use of visual representations implies a…
Descriptors: Knowledge Representation, Models, Competence, Learning Processes
Twissell, Adrian – Educational Technology & Society, 2018
Abstract electronics concepts are difficult to develop because the phenomena of interest cannot be readily observed. Visualisation skills support learning about electronics and can be applied at different levels of representation and understanding (observable, symbolic and abstract). Providing learners with opportunities to make transitions…
Descriptors: Electronics, Case Studies, Concept Formation, Scientific Concepts

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