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Pedro Isaias, Editor; Demetrios G. Sampson, Editor; Dirk Ifenthaler, Editor – Cognition and Exploratory Learning in the Digital Age, 2024
The Cognition and Exploratory Learning in the Digital Age (CELDA) conference focuses on discussing and addressing the challenges pertaining to the evolution of the learning process, the role of pedagogical approaches and the progress of technological innovation, in the context of the digital age. In each edition, CELDA, gathers researchers and…
Descriptors: Artificial Intelligence, Cognitive Processes, Discovery Learning, Teaching Methods
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Julius Meier; Peter Hesse; Stephan Abele; Alexander Renkl; Inga Glogger-Frey – Instructional Science: An International Journal of the Learning Sciences, 2024
Self-explanation prompts in example-based learning are usually directed backwards: Learners are required to self-explain problem-solving steps just presented ("retrospective" prompts). However, it might also help to self-explain upcoming steps ("anticipatory" prompts). The effects of the prompt type may differ for learners with…
Descriptors: Problem Based Learning, Problem Solving, Prompting, Models
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Tom Reshef-Israeli; Shulamit Kapon – Online Submission, 2024
As problems become increasingly complex, science educators need to better understand how new knowledge is constructed and applied in heterogeneous team collaborations, and how to teach students to productively engage in these processes. We discuss the emergence of insights in collaborative sensemaking and suggest a model that articulates the…
Descriptors: Comprehension, Constructivism (Learning), Teaching Methods, Learner Engagement
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Dinsmore, Daniel L.; Fryer, Luke K.; Dumas, Denis G. – Educational Psychology Review, 2023
The literature on cognitive processing and strategic processing is murky with regard to how these types of processing influence learning. One reason for this is that the frameworks used to investigate these relations have separately focused on different aspects related to cognitive processing with little integration between them. To address these…
Descriptors: Cognitive Processes, Models, Barriers, Learning
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Yuang Wei; Bo Jiang – IEEE Transactions on Learning Technologies, 2024
Understanding student cognitive states is essential for assessing human learning. The deep neural networks (DNN)-inspired cognitive state prediction method improved prediction performance significantly; however, the lack of explainability with DNNs and the unitary scoring approach fail to reveal the factors influencing human learning. Identifying…
Descriptors: Cognitive Mapping, Models, Prediction, Short Term Memory
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Khong, Hou Keat; Kabilan, Muhammad Kamarul – Computer Assisted Language Learning, 2022
The notion of "Micro-Learning" (ML) has been repeatedly accented as a successful learning approach in different learning phenomena. Despite these optimistic emphases, several studies lack a theoretical grounding in adoption of ML, thus missing a shared perspective of the education community. The scarce theoretical justification for…
Descriptors: Second Language Instruction, Cognitive Processes, Difficulty Level, Self Determination
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Yang, Qi-Fan; Lian, Li-Wen; Zhao, Jia-Hua – International Journal of Educational Technology in Higher Education, 2023
According to previous studies, traditional laboratory safety courses are delivered in a classroom setting where the instructor teaches and the students listen and read the course materials passively. The course content is also uninspiring and dull. Additionally, the teaching period is spread out, which adds to the instructor's workload. As a…
Descriptors: Undergraduate Students, Gamification, Artificial Intelligence, Robotics
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Siew, Cynthia S. Q. – Journal of Learning Analytics, 2022
This commentary discusses how research approaches from Cognitive Network Science can be of relevance to research in the field of Learning Analytics, with a focus on modelling the knowledge representations of learners and students as a network of interrelated concepts. After providing a brief overview of research in Cognitive Network Science, I…
Descriptors: Network Analysis, Learning Analytics, Cognitive Processes, Knowledge Level
Sarah E. Stanlick; Joseph Doiron – Metropolitan Universities, 2024
Global crises continue to shape the higher education landscape by posing challenges at every step of the educational process. From pedagogical delivery to experience design to undergraduate student research, pandemics, unrest, war, and environmental disasters have given us many imperatives to pivot and adapt. While the COVID-19 pandemic brought…
Descriptors: Critical Theory, Models, Global Approach, Electronic Learning
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Kumar, Vivekanandan; Ally, Mohamed; Tsinakos, Avgoustos; Norman, Helmi – Canadian Journal of Learning and Technology, 2022
Over the past decade, opportunities for online learning have dramatically increased. Learners around the world now have digital access to a wide array of corporate trainings, certifications, comprehensive academic degree programs, and other educational and training options. Some organizations are blending traditional instruction methods with…
Descriptors: Electronic Learning, Cognitive Processes, Artificial Intelligence, Educational Technology
Guled, Abdiwahab – ProQuest LLC, 2022
This Design-based research study aimed to develop a design framework that would help learning designers to apply learning theory principles when designing learning objects. The study examined the experiential learning theory, information processing theory, and cognitive load theory to develop the iterative learning development (ILD) model. Several…
Descriptors: Learning Theories, Instructional Design, Experiential Learning, Information Processing
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Zheng Liu; Jiahui Wen; Yikang Liu; Chuan-Peng Hu – British Journal of Educational Psychology, 2024
Background: Self-related information is difficult to ignore and forget, which brings valuable implications for educational practice. Self-referential encoding techniques involve integrating self-referencing cues during the processing of learning material. However, the evidence base and effective implementation boundaries for these techniques in…
Descriptors: Self Concept, Meta Analysis, Student Attitudes, Models
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Natalia Riapina – Business and Professional Communication Quarterly, 2024
This article presents a conceptual framework for integrating AI-enabled business communication in higher education. Drawing on established theories from business communication and educational technology, the framework provides comprehensive guidance for designing engaging learning experiences. It emphasizes the significance of social presence,…
Descriptors: Artificial Intelligence, Business Communication, Higher Education, Technology Uses in Education
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Julius Moritz Meier; Peter Hesse; Stephan Abele; Alexander Renkl; Inga Glogger-Frey – Journal of Computer Assisted Learning, 2024
Background: In example-based learning, examples are often combined with generative activities, such as comparative self-explanations of example cases. Comparisons induce heavy demands on working memory, especially in complex domains. Hence, only stronger learners may benefit from comparative self-explanations. While static text-based examples can…
Descriptors: Video Technology, Models, Cues, Problem Solving
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Haoxin Xu; Tianrun Deng; Xianlong Xu; Xiaoqing Gu; Lingyun Huang; Haoran Xie; Minhong Wang – Education and Information Technologies, 2025
In the 21st century, the urgent educational demand for cultivating complex skills in vocational training and learning is met with the effectiveness of the four-component instructional design model. Despite its success, research has identified a notable gap in the address of formative assessment, particularly within computer-supported frameworks.…
Descriptors: Models, Instructional Design, Computer Assisted Testing, Formative Evaluation
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