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Verena Dornauer; Michael Netzer; Éva Kaczkó; Lisa-Maria Norz; Elske Ammenwerth – International Journal of Artificial Intelligence in Education, 2024
Cognitive presence is a core construct of the Community of Inquiry (CoI) framework. It is considered crucial for deep and meaningful online-based learning. CoI-based real-time dashboards visualizing students' cognitive presence may help instructors to monitor and support students' learning progress. Such real-time classifiers are often based on…
Descriptors: Electronic Learning, Discussion, Classification, Automation
Lena S. Geiger; Torsten Wüstenberg; Zhenxiang Zang; Mirjam Melzer; Stephanie H. Witt; Marcella Rietschel; Markus M. Nöthen; Stefan Herms; Franziska Degenhardt; Andreas Meyer-Lindenberg; Carolin Moessnang – npj Science of Learning, 2024
Procedural learning and automatization have widely been studied in behavioral psychology and typically involves a rapid improvement, followed by a plateau in performance throughout repeated training. More recently, brain imaging studies have implicated frontal-striatal brain circuits in skill learning. However, it is largely unknown whether…
Descriptors: Cognitive Processes, Brain Hemisphere Functions, Short Term Memory, Behavior Patterns
Aaron S. Richmond; Anna Ropp; Jennifer Bradford; Graham S. Ignizio; Jeff Hammond; Denise Mowder; Jessica M. Bittmann – College Teaching, 2024
Past research indicates that the testing effect is an effective tool to improve memory and retention and academic performance, however, very few studies have investigated the effects across academic disciplines with a focus on higher- vs. lower-level learning. Therefore, in the current study, we sought to examine whether the testing effect occurs…
Descriptors: Testing, Cognitive Processes, Learning Processes, Intellectual Disciplines
Erin M. Anderson; Apoorva Shivaram; Susan J. Hespos; Dedre Gentner – Grantee Submission, 2023
The ability to generalize previous knowledge to new contexts is a key aspect of human cognition and relational learning. A well-known learning maxim is that breadth of training predicts "breadth of training predicts breadth of transfer." When examples vary in their surface features, this provides evidence that only the common relational…
Descriptors: Learning Processes, Generalization, Transfer of Training, Familiarity
Nick Serki; San Bolkan – Communication Education, 2024
This study tested the notion that the impact of clarity (i.e., structure) on learning is indirect and occurs, in part, through the reduction of cognitive load and subsequently through students' motivation to process instructional information. Two hundred fifty-two students were randomly assigned to one of two text-based lessons (clear or unclear)…
Descriptors: College Students, Difficulty Level, Cognitive Processes, Student Motivation
Gaoxia Zhu; Marlene Scardamalia; Raadiyah Nazeem; Zoe Donoahue; Leanne Ma; Zhixin Lai – Instructional Science: An International Journal of the Learning Sciences, 2024
Knowledge Building principles such as real ideas, authentic problems; epistemic agency; and collective responsibility for advancement of community knowledge convey ways in which Knowledge Building mirrors work in knowledge-creating communities. Previous studies suggest Metadiscourse--discourse about discourse--helps sustain and improve community…
Descriptors: Elementary School Students, Grade 2, Learning Processes, Psychological Patterns
Nicholas P. Maxwell; Mark J. Huff – Metacognition and Learning, 2024
Judgments of learning (JOLs) are often reactive on memory for cue-target pairs. This pattern, however, is moderated by relatedness, as related but not unrelated pairs often show a memorial benefit compared to a no-JOL control group. Based on Soderstrom et al.'s, "Journal of Experimental Psychology: Learning, Memory, and Cognition" 41,…
Descriptors: Decision Making, Recall (Psychology), Cues, Cognitive Processes
Delianidi, Marina; Diamantaras, Konstantinos – Journal of Educational Data Mining, 2023
Student performance is affected by their knowledge which changes dynamically over time. Therefore, employing recurrent neural networks (RNN), which are known to be very good in dynamic time series prediction, can be a suitable approach for student performance prediction. We propose such a neural network architecture containing two modules: (i) a…
Descriptors: Academic Achievement, Prediction, Cognitive Measurement, Bayesian Statistics
James C. Kaufman; Vlad P. Glaveanu – Journal of Creative Behavior, 2025
The traditionally studied positive outcomes of creativity tend to be product-focused, such as Big-C contributions, good grades, or strong work performance. This paper makes an argument for the importance of less-discussed products of the process--the benefits that arise from being creative, regardless of one's abilities or level of achievement.…
Descriptors: Creative Development, Creative Thinking, Creativity, Self Concept
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
Julia Waldeyer; Tino Endres; Julian Roelle; Martine Baars; Alexander Renkl – Educational Psychology Review, 2024
The present study was designed to understand and optimize self-assessment accuracy in cognitive skill acquisition through example-based learning. We focused on the initial problem-solving phase, which follows after studying worked examples. At the end of this phase, it is important that learners are aware whether they have already understood the…
Descriptors: Self Evaluation (Individuals), Cognitive Processes, Problem Based Learning, Accuracy
Daryn A. Dever; Megan D. Wiedbusch; Sarah M. Romero; Roger Azevedo – British Journal of Educational Technology, 2024
Intelligent tutoring systems (ITSs) incorporate pedagogical agents (PAs) to scaffold learners' self-regulated learning (SRL) via prompts and feedback to promote learners' monitoring and regulation of their cognitive, affective, metacognitive and motivational processes to achieve their (sub)goals. This study examines PAs' effectiveness in…
Descriptors: Intelligent Tutoring Systems, Scaffolding (Teaching Technique), Independent Study, Prompting
Sumardani, Dadan; Lin, Chih-Hung – Education and Information Technologies, 2023
Virtual Reality (VR) has gained popularity in educational fields enabling new learning possibilities. In the implementation process, VR could improve learning by increasing positive affective and cognitive processing, whereas VR also could hurt learning by increasing distraction and leading to poorer learning outcomes. Thus, understanding the…
Descriptors: Computer Simulation, Cognitive Processes, Brain Hemisphere Functions, Reading Processes
Bharadwaj, Avni; Dargue, Nicole; Sweller, Naomi – Cognitive Science, 2022
Research has shown that gesture production supports learning across a number of tasks. It is unclear, however, whether gesture production during encoding can support narrative recall, who gesture production benefits most, and whether certain types of gestures are more beneficial than others. This study, therefore, investigated the effect of…
Descriptors: Nonverbal Communication, Recall (Psychology), Cognitive Processes, Verbal Communication
Teodóra Vékony; Claire Pleche; Orsolya Pesthy; Karolina Janacsek; Dezso Nemeth – npj Science of Learning, 2022
Procedural learning is key to optimal skill learning and is essential for functioning in everyday life. The findings of previous studies are contradictory regarding whether procedural learning can be modified by prioritizing speed or accuracy during learning. The conflicting results may be due to the fact that procedural learning is a multifaceted…
Descriptors: Learning Processes, Accuracy, Reaction Time, Cognitive Processes