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Yadi Yu; Wenbo Zhao; Anran Li; David R. Shanks; Xiao Hu; Liang Luo; Chunliang Yang – Educational Psychology Review, 2025
Retrieval practice is well-established as a powerful tool for reinforcing long-term learning. Most previous research has concentrated on the effectiveness of overt retrieval, involving recalling information from memory and generating overt responses by writing, typing, or speaking aloud the retrieved information. Here we ask whether covert…
Descriptors: Recall (Psychology), Cognitive Processes, Learning Strategies, Meta Analysis
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Joachim Wirth; Xenia-Lea Weber-Reuter; Corinna Schuster; Jens Fleischer; Detlev Leutner; Ferdinand Stebner – Educational Psychology Review, 2025
Training of self-regulated learning is most effective if it supports learning strategies in combination with metacognitive regulation, and learners can transfer their acquired metacognitive regulation skills to different tasks that require the use of the same learning strategy (near transfer). However, whether learners can transfer metacognitive…
Descriptors: Foreign Countries, Grade 6, Grade 5, Metacognition
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Kuhlmann, Shelbi L.; Bernacki, Matthew L.; Greene, Jeffrey A. – New Directions for Teaching and Learning, 2023
The affordances of computer-based learning environments make them powerful tools for conveying information in higher education. However, to most effectively use these environments, students must be adept at self-regulating their learning. This self-regulation is effortful, including a myriad of processes, including defining tasks, making plans,…
Descriptors: Multimedia Instruction, Learning Theories, Learning Strategies, Electronic Learning
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Élisabeth Bélanger; Lorie-Marlène Brault Foisy; Steve Masson – International Journal of Research & Method in Education, 2025
The main objective of this methodological article is to discuss the contribution of response times as a tool in education research. The use of response times in research is largely a legacy of the work carried out in cognitive psychology, which has made it possible to describe the cognitive processes involved in information processing. In…
Descriptors: Educational Research, Reaction Time, Cognitive Processes, Research Methodology
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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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Wang, Tingting; Li, Shan; Huang, Xiaoshan; Pan, Zexuan; Lajoie, Susanne P. – Education and Information Technologies, 2023
Students process qualitatively and quantitatively different information during the dynamic self-regulated learning (SRL) process, and thus they may experience varying cognitive load in different SRL behaviors. However, there is limited research on the role of cognitive load in SRL. This study examined students' cognitive load in micro-level SRL…
Descriptors: Cognitive Processes, Difficulty Level, Learning Strategies, Self Efficacy
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Jana Gonnermann-Müller; Jule M. Krüger – Journal of Computer Assisted Learning, 2025
Background: Despite the numerous positive effects of augmented reality (AR) on learning, previous research has shown ambiguous results regarding the cognitive demand on the learner arising from, for example, the overlay of virtual elements or novel interaction techniques. At the same time, the number of evidence-based guidelines on designing AR is…
Descriptors: Computer Simulation, Computer Assisted Design, Difficulty Level, Cognitive Processes
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Janssen, Eva M.; van Gog, Tamara; van de Groep, Laura; de Lange, Anne Jóia; Knopper, Roosmarijn L.; Onan, Erdem; Wiradhany, Wisnu; de Bruin, Anique B. H. – Educational Psychology Review, 2023
Students tend to avoid effective but effortful study strategies. One potential explanation could be that high-effort experiences may not give students an immediate feeling of learning, which may affect their perceptions of the strategy's effectiveness and their willingness to use it. In two experiments, we investigated the role of mental effort in…
Descriptors: Cognitive Processes, Difficulty Level, Learning Strategies, Instructional Effectiveness
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Lanqin Zheng; Yunchao Fan; Zichen Huang; Lei Gao – Journal of Computer Assisted Learning, 2024
Background: Online collaborative learning has been widely adopted in the field of education. However, learners often find it difficult to engage in collaboratively building knowledge and jointly regulating online collaborative learning. Objectives: The study compared the impacts of the three learning approaches on collaborative knowledge building,…
Descriptors: Cooperative Learning, Electronic Learning, College Students, Learning Strategies
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Zhang, Shirong; Koning, Bjorn B.; Paas, Fred – British Journal of Educational Psychology, 2023
Background: Self-management of cognitive load is a recent development in cognitive load theory. Finger pointing has been shown to be a potential self-management strategy to support learning from spatially separated, but mutually referring text and pictures (i.e., split-attention examples). Aims: The present study aimed to extend the prior research…
Descriptors: Self Management, Cognitive Processes, Difficulty Level, Nonverbal Communication
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Bahari, Akbar; Wu, Sumei; Ayres, Paul – Educational Psychology Review, 2023
A contemporary review (over a 10-year period) was conducted into studies that used computer-assisted language learning (CALL) strategies to learn a second language (L2) by considering the impact of cognitive load. Twelve affordances were identified that led to enhanced learning, namely, online annotations and glosses, captioning, digital…
Descriptors: Computer Assisted Instruction, Second Language Learning, Cognitive Processes, Difficulty Level
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Zhao, Fuzheng; Liu, Gi-Zen; Zhou, Juan; Yin, Chengjiu – Educational Technology & Society, 2023
Big data in education promotes access to the analysis of learning behavior, yielding many valuable analysis results. However, with obscure and insufficient guidelines commonly followed when applying the analysis results, it is difficult to translate information knowledge into actionable strategies for educational practices. This study aimed to…
Descriptors: Learning Analytics, Man Machine Systems, Artificial Intelligence, Learning Strategies
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Yi Zhang; Jiumin Yang; Chenyan Dai; Zhongling Pi – Educational Technology & Society, 2024
Previous studies have shown that encouraging students to use self-explanation strategies has proven effective in text-focused learning contexts. However, no study to date has focused on how students' strategy preference moderates the effect of self-explanation strategies on learning from video lectures. The current study investigated how students'…
Descriptors: Teaching Methods, Video Technology, Lecture Method, Preferences
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Paul Evans; Maarten Vansteenkiste; Philip Parker; Andrew Kingsford-Smith; Sijing Zhou – Educational Psychology Review, 2024
Although cognitive load theory research has studied factors associated with motivation, these literatures have primarily been developed in isolation from each other. In this contribution, we aimed to advance both fields by examining the effects of instructional strategies on learners' experience of cognitive load, motivation, engagement, and…
Descriptors: Cognitive Processes, Difficulty Level, Learning Motivation, Self Determination
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Hajer Mguidich; Bachir Zoudji; Aïmen Khacharem – Journal of Experimental Education, 2025
The imagination effect occurs when learners who imagine a procedure perform better on a subsequent test than learners who study it. The present study explored whether this effect is restricted to short-term learning or whether it also applies when learning is tested after a delay. Forty novices and forty experts learned about a basketball game…
Descriptors: Imagination, Expertise, Cognitive Processes, Difficulty Level
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