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Gorney, Kylie; Wollack, James A. – Journal of Educational Measurement, 2022
Detection methods for item preknowledge are often evaluated in simulation studies where models are used to generate the data. To ensure the reliability of such methods, it is crucial that these models are able to accurately represent situations that are encountered in practice. The purpose of this article is to provide a critical analysis of…
Descriptors: Prior Learning, Simulation, Models, Reaction Time
Witherby, Amber E.; Carpenter, Shana K.; Smith, Andrew M. – Metacognition and Learning, 2023
Prior knowledge is often strongly related to students' learning. In the present research, we explored the relationship between prior knowledge and the accuracy of students' predictive monitoring judgments (judgments of learning; JOLs) and postdictive monitoring judgments (confidence judgments). In four experiments, students completed prior…
Descriptors: Metacognition, Prior Learning, Accuracy, Prediction
Iryna Schommartz; Angela M. Kaindl; Claudia Buss; Yee Lee Shing – Developmental Psychology, 2024
Childhood is a period when memory consolidation and knowledge base undergo rapid changes. The present study examined short-delay (overnight) and long-delay (after a 2-week period) consolidation of new information either congruent or incongruent with prior knowledge in typically developing 6- to 8-year-old children (n = 32), 9- to 11-year-old…
Descriptors: Access to Information, Children, Memory, Prior Learning
Kathryn S. McCarthy; Danielle S. McNamara – Grantee Submission, 2023
When students learn, they activate, use, revise, and acquire knowledge. As such, knowledge is a fundamental asset. We advocate for an asset-based approach which capitalizes on students' knowledge through prompts and activities that invite learners to leverage what they already know. Considering knowledge as an asset means that educators must…
Descriptors: Epistemology, Definitions, Prompting, Learning Activities
McCarthy, Kathryn S.; McNamara, Danielle S. – Educational Psychologist, 2021
Prior knowledge is one of the strongest contributors to comprehension, but there is little specificity about different aspects of prior knowledge and how they impact comprehension. This article introduces the Multidimensional Knowledge in Text Comprehension framework, which conceptualizes prior knowledge along four intersecting dimensions: amount,…
Descriptors: Reading Comprehension, Prior Learning, Knowledge Level, Accuracy
McCarthy, Kathryn S.; McNamara, Danielle S. – Grantee Submission, 2021
Prior knowledge is one of the strongest contributors to comprehension, but there is little specificity about different aspects of prior knowledge and how they impact comprehension. This article introduces the Multidimensional Knowledge in Text Comprehension framework, which conceptualizes prior knowledge along four intersecting dimensions: amount,…
Descriptors: Reading Comprehension, Prior Learning, Knowledge Level, Accuracy
Pooja G. Sidney; Julie F. Shirah; Lauren Zahrn; Clarissa A. Thompson – Grantee Submission, 2022
In mathematics, learners often spontaneously draw on prior knowledge when learning new ideas. In this study, we examined whether the specific diagrams used to represent more familiar (i.e., whole number division) and less familiar ideas (i.e., fraction division) shape successful transfer. Undergraduates (N = 177) were randomly assigned to…
Descriptors: Mathematics Education, Prior Learning, Transfer of Training, Visual Aids
Na Tao; Ying Wang – Language Teaching Research, 2025
Task design features have different effects on second language (L2) production and can be adopted for different pedagogical purposes. However, the synergistic effects of task features were left unexplored in the extant task-based literature. The present study investigated the synergistic effects of two task design features, namely, prior knowledge…
Descriptors: Foreign Countries, English (Second Language), Second Language Instruction, Writing (Composition)
Wang, Fei; Huang, Zhenya; Liu, Qi; Chen, Enhong; Yin, Yu; Ma, Jianhui; Wang, Shijin – IEEE Transactions on Learning Technologies, 2023
To provide personalized support on educational platforms, it is crucial to model the evolution of students' knowledge states. Knowledge tracing is one of the most popular technologies for this purpose, and deep learning-based methods have achieved state-of-the-art performance. Compared to classical models, such as Bayesian knowledge tracing, which…
Descriptors: Cognitive Measurement, Diagnostic Tests, Models, Prediction
Abdulhadi Shoufan – ACM Transactions on Computing Education, 2023
With the immense interest in ChatGPT worldwide, education has seen a mix of both excitement and skepticism. To properly evaluate its impact on education, it is crucial to understand how far it can help students without prior knowledge answer assessment questions. This study aims to address this question as well as the impact of the question type.…
Descriptors: Prior Learning, Artificial Intelligence, Technology Uses in Education, Computer Assisted Testing
Peri Aslan – PASAA: Journal of Language Teaching and Learning in Thailand, 2024
Morphological awareness is the metalinguistic realization that words consist of meaningful roots and affixes that can be isolated and manipulated. Learners at different proficiency levels use various forms of background knowledge such as cultural knowledge, technical knowledge, religious knowledge, vocabulary knowledge, and contextual visuals. The…
Descriptors: Morphology (Languages), Phonological Awareness, Knowledge Level, Second Language Learning
Eyupoglu, Tayyibe Fulya – ProQuest LLC, 2023
The current study aimed to contribute to the literature by implementing an intervention that examines the effects of explicit metacognitive strategy training and prompts embedded within a Game-Based Learning Environment (GBLE), "Missions with Monty," on metacognitive monitoring accuracy, game performance, and science knowledge of…
Descriptors: Game Based Learning, Metacognition, Educational Games, Grade 5
Cody, Christa; Maniktala, Mehak; Lytle, Nicholas; Chi, Min; Barnes, Tiffany – International Journal of Artificial Intelligence in Education, 2022
Research has shown assistance can provide many benefits to novices lacking the mental models needed for problem solving in a new domain. However, varying approaches to assistance, such as subgoals and next-step hints, have been implemented with mixed results. Next-Step hints are common in data-driven tutors due to their straightforward generation…
Descriptors: Comparative Analysis, Prior Learning, Intelligent Tutoring Systems, Problem Solving
Ian Thacker; Hannah French; Shon Feder – International Journal of Science Education, 2025
Presenting novel numbers about climate change to people after they estimate those numbers can shift their attitudes and scientific conceptions. Prior research suggests that such science learning can be supported by encouraging learners to make use of given benchmark information, however there are several other numerical estimation skills that may…
Descriptors: Climate, Computation, College Students, Hispanic American Students
Weitekamp, Daniel, III.; Harpstead, Erik; MacLellan, Christopher J.; Rachatasumrit, Napol; Koedinger, Kenneth R. – International Educational Data Mining Society, 2019
Computational models of learning can be powerful tools to test educational technologies, automate the authoring of instructional software, and advance theories of learning. These mechanistic models of learning, which instantiate computational theories of the learning process, are capable of making predictions about learners' performance in…
Descriptors: Computation, Models, Learning, Prediction