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Yu Lei; Xin Fu; Jingjie Zhao; Baolin Yi – Education and Information Technologies, 2025
Grouping students according to their abilities and promoting deeper interaction and moderation are key issues in improving computational thinking in collaborative programming. However, the distribution characteristics and evolving pathways of computational thinking in different groups have not been deeply explored. During the course of a…
Descriptors: Ability Grouping, Computation, Programming, Cooperative Learning
Jie Liu; Zhifeng Li; Jiawang Yang; Hao He; Fang Cui – npj Science of Learning, 2025
This study explores the cognitive and neural mechanisms underlying math avoidance in individuals with high math anxiety (HMA), a pattern contributing to reduced practice and poor performance. Using an approach-avoid conflict paradigm and both general linear mixed model and Hierarchical Drift Diffusion Model (HDDM) regression analyses, we found…
Descriptors: Cognitive Processes, Neurology, Mathematics Education, Mathematics Anxiety
Jian-Hong Ye, Editor; Liying Nong, Editor; Li Wang, Editor; Weiguaju Nong, Editor – IntechOpen, 2025
Learning is always a core activity in forming cognitive abilities and personality traits in people's growth process, and motivation is the key psychological mechanism that drives learning behaviour. Therefore, motivation in learning is an important area of research in educational psychology. It not only determines the initiation and continuation…
Descriptors: Learning Motivation, Learning, Student Motivation, Educational Psychology
Peijian Paul Sun; Zeqi Ren; Xian Zhao – Journal of Computer Assisted Learning, 2025
Background: Student engagement has been conceptualised and operationalised in various learning environments. However, there is currently a lack of established scales to measure student engagement in synchronous online learning. One possible reason is the existence of the conceptual and structural ambiguity regarding student engagement. Objective:…
Descriptors: Student Participation, Second Language Learning, Synchronous Communication, Electronic Learning
Yoon Lee; Gosia Migut; Marcus Specht – British Journal of Educational Technology, 2025
Learner behaviours often provide critical clues about learners' cognitive processes. However, the capacity of human intelligence to comprehend and intervene in learners' cognitive processes is often constrained by the subjective nature of human evaluation and the challenges of maintaining consistency and scalability. The recent widespread AI…
Descriptors: Artificial Intelligence, Cognitive Processes, Student Behavior, Cues
Man Huang – Education and Information Technologies, 2025
As educational technology advances, the role of artificial intelligence (AI) in enhancing language education becomes increasingly prominent. However, there is a scarcity of empirical research assessing how AI integration influences student engagement and contributes to the language learning performance. This mixed-methods study seeks to fill the…
Descriptors: Foreign Countries, Middle School Students, Artificial Intelligence, Learner Engagement
Zhao Yangyang; Muhammad Faizal Bin A. Ghani; Kazi Enamul Hoque – Psychology in the Schools, 2025
This study aimed to analyze the relationship between student cognitive engagement and academic achievement and inquired about the moderating effects of student gender on the relationship. A cross-sectional quantitative survey approach was conducted to do descriptive and inferential statistics. Simple random sampling was employed to select…
Descriptors: Foreign Countries, Academic Achievement, Learner Engagement, Secondary School Students
Axel Grund; Stefan Fries; Matthias Nückles; Alexander Renkl; Julian Roelle – Educational Psychology Review, 2024
In the context of instructional design and self-regulated learning research, the notion of mental effort allocation, monitoring, and control has gained increasing attention. Bringing together a cognitive perspective, focusing on Cognitive Load Theory, and a motivational perspective, merging central accounts from Situated Expectancy Value Theory…
Descriptors: Cognitive Processes, Metacognition, Performance, Academic Achievement
Ling Zhang; Naiqing Song; Guowei Wu; Jinfa Cai – Educational Studies in Mathematics, 2025
This study concerns the cognitive process of mathematical problem posing, conceptualized in three stages: understanding the task, constructing the problem, and expressing the problem. We used the eye tracker and think-aloud methods to deeply explore students' behavior in these three stages of problem posing, especially focusing on investigating…
Descriptors: Cognitive Processes, Mathematics Skills, Problem Solving, Eye Movements
Mai Bui; Jessica Pierson Bishop – Mathematics Teacher: Learning and Teaching PK-12, 2025
Noticing students' mathematical thinking is foundational to responsive teaching. However, it is cognitively demanding because teachers must attend to important details in students' strategies, interpret their understandings, and decide on next steps--all in the moment. This article introduces the Big Ideas of Measurement (BIM), a research-based…
Descriptors: Measurement Techniques, Student Behavior, Cognitive Processes, Teacher Behavior
Yashasvi Walia; Rajnish Kumar Gupta – Cognitive Research: Principles and Implications, 2025
Cognitive conflict and risk-taking behaviors are linked in complex ways. This study examined whether threat sensitivity explains the relationship between conflict monitoring and risk-taking in young adults. A sample of 204 university students (ages 18-25, mean = 20.55, SD = 2.14) completed a computerized Stroop task (cognitive conflict), the RT-18…
Descriptors: Foreign Countries, Young Adults, College Students, Interference (Learning)
Qiuchen Yu; Jiangfeng Gou; Yan Li; Zhongling Pi; Jiumin Yang – British Journal of Educational Technology, 2024
Instructional videos risk overloading learners' limited working memory resources due to the transient information effect. Learner control is one way to mitigate this concern, but has shown almost zero overall effect and considerable heterogeneity. Consequently, it is essential to identify when learner control is most beneficial. The present study…
Descriptors: Video Technology, Audiovisual Aids, Cues, Student Behavior
Hoi Vo – Applied Linguistics, 2024
L2 learner engagement is an emerging but critical construct in the field of psychology of language learning and teaching. However, research on L2 learner engagement has suffered from the inconsistent operationalization of the multidimensional structure of the construct and the conceptual overlap among its different components, making research…
Descriptors: Second Language Learning, Learner Engagement, English (Second Language), Asians
Lämsä, Joni; Mannonen, Joonas; Tuhkala, Ari; Heilala, Ville; Helovuo, Arto; Tynkkynen, Ilkka; Lampi, Emilia; Sipiläinen, Katriina; Kärkkäinen, Tommi; Hämäläinen, Raija – Journal of Computer Assisted Learning, 2023
Background: Cognitive load (CL) management is essential in safety-critical fields so that professionals can monitor and control their cognitive resources efficiently to perform and solve scenarios in a timely and safe manner, even in complex and unexpected circumstances. Thus, cognitive load theory (CLT) can be used to design virtual reality (VR)…
Descriptors: Cognitive Processes, Difficulty Level, Computer Simulation, Flight Training
Coppess, Brian – Educational Research: Theory and Practice, 2022
Largely because of its behaviorist roots and despite several progressive education movements, external control has been the primary motivation technique used by educators since the dawn of formal schooling in the United States. Decades of recent research, however, has led to a paradigm shift of sorts, suggesting that by challenging their mental…
Descriptors: Cognitive Processes, Student Motivation, Motivation Techniques, Principals

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