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Murphy, Michelle Pauley; Hung, Woei – TechTrends: Linking Research and Practice to Improve Learning, 2023
One hundred years ago, Paul Weiss and Ludwig von Bertalanffy independently proposed that living organisms interact with their environment through systems. In the century that has followed, systems thinking and modeling have grown in tandem with discovery of the vast complexity of the universe at microscopic through astronomic levels. As our…
Descriptors: Systems Approach, Cognitive Processes, Artificial Intelligence, Learning Processes
Liu, Zhi; Kong, Xi; Chen, Hao; Liu, Sannyuya; Yang, Zongkai – IEEE Transactions on Learning Technologies, 2023
In a massive open online courses (MOOCs) learning environment, it is essential to understand students' social knowledge constructs and critical thinking for instructors to design intervention strategies. The development of social knowledge constructs and critical thinking can be represented by cognitive presence, which is a primary component of…
Descriptors: MOOCs, Cognitive Processes, Students, Models
Takami, Kyosuke; Flanagan, Brendan; Dai, Yiling; Ogata, Hiroaki – Smart Learning Environments, 2023
In the age of artificial intelligence (AI), trust in AI systems is becoming more important. Explainable recommenders, which explain why an item is recommended, have recently been proposed in the field of learning technology to improve transparency, persuasiveness, and trustworthiness. However, the methods for generating explanations are limited…
Descriptors: Artificial Intelligence, Personality, Cognitive Processes, Public Health
Xu Chen; Di Wu – IEEE Transactions on Learning Technologies, 2024
Generative artificial intelligence (AI) is widely recognized as one of the most influential technologies for the future, having sparked a paradigm shift in scientific research. The field of education has also been greatly impacted by this transformative technology, with researchers exploring the applications of generative AI, particularly ChatGPT,…
Descriptors: Automation, Multimedia Materials, Instructional Materials, Artificial Intelligence
Celeste Combrinck – Discover Education, 2024
The current article used real data to demonstrate the analysis and synthesis of Mixed Methods Research (MMR) data with generative Artificial Intelligence (Gen AI). I explore how reliable and valid Gen AI data outputs are and how to improve their use. The current content is geared towards enhancing methodological application regardless of field or…
Descriptors: Foreign Countries, College Freshmen, Engineering Education, Artificial Intelligence
Anja Strobel; Alexander Strobel; Franzis Preckel; Ricarda Steinmayr – AERA Open, 2024
While intelligence and motivational variables are well-established predictors of academic achievement, Need for Cognition (NFC), the stable intrinsic motivation to engage in and enjoy challenging intellectual activity, has not yet been considered comprehensively in this field, especially not longitudinally. By applying latent change score…
Descriptors: Academic Achievement, Self Concept, Learning Motivation, Cognitive Processes
Lewis J. Baker; Hongyue Li; Hugo Hammond; Christopher B. Jaeger; Anne Havard; Jonathan D. Lane; Caroline E. Harriott; Daniel T. Levin – Cognitive Research: Principles and Implications, 2024
As a wide variety of intelligent technologies become part of everyday life, researchers have explored how people conceptualize agents that in some ways act and think like living things but are clearly machines. Much of this work draws upon the idea that people readily default to generalizing human-like properties to such agents, and only pare back…
Descriptors: Cognitive Processes, Psychological Patterns, Abstract Reasoning, Attribution Theory
Anna Trifonova; Mariela Destéfano; Mario Barajas – Digital Education Review, 2024
This article proposes a comprehensive AI curriculum tailored for young learners aged 11 to 14, emphasizing a humanistic approach. We review other AI curricula proposals for children and young people and underline that they focus primarily on AI's technological benefits and on learning coding and logic. Our curriculum explores human cognition that…
Descriptors: Artificial Intelligence, Cognitive Processes, Children, Constructivism (Learning)
Nancy Sulla – Eye on Education, 2024
If students haven't developed the brain-based skills to focus, catch and correct errors, identify cause-and-effect relationships, and more, they can't make sense of lessons. Executive function is the missing link to student achievement. But how can you develop this in the classroom? Bestselling author Nancy Sulla has the answers. She explains how…
Descriptors: Executive Function, Academic Achievement, Cognitive Processes, Daily Living Skills
Giulia Cosentino; Jacqueline Anton; Kshitij Sharma; Mirko Gelsomini; Michail Giannakos; Dor Abrahamson – British Journal of Educational Technology, 2025
This study explores the role of generative AI (GenAI) in providing formative feedback in children's digital learning experiences, specifically in the context of mathematics education. Using multimodal data, the research compares AI-generated feedback with feedback from human instructors, focusing on its impact on children's learning outcomes.…
Descriptors: Artificial Intelligence, Technology Uses in Education, Feedback (Response), Mathematics Education
Chia-Jung Li; Gwo-Jen Hwang; Ching-Yi Chang; Hui-Chi Su – British Journal of Educational Technology, 2025
In professional training, developing critical thinking is essential for professionals to analyse problem situations and respond effectively to emergencies. Conventional professional training typically employs multimedia materials combined with progressive prompting (PP) to support trainees in constructing knowledge and solving problems on their…
Descriptors: Artificial Intelligence, Technology Uses in Education, Prompting, Academic Achievement
Fiori, Marina; Ortony, Andrew – Journal of Intelligence, 2021
In this article, we provide preliminary evidence for the 'hypersensitivity hypothesis', according to which Emotional Intelligence (EI) functions as a magnifier of emotional experience, enhancing the effect of emotion and emotion information on thinking and social perception. Measuring ability EI, and in particular Emotion Understanding, we…
Descriptors: Emotional Intelligence, Emotional Experience, Cognitive Processes, Individual Differences
Chuderski, Adam; Jastrzebski, Jan; Kroczek, Bartlomiej; Kucwaj, Hanna; Ociepka, Michal – Metacognition and Learning, 2021
Participants rated Intuition, Suddenness, Pleasure, and Certainty accompanying their solutions to items of a popular fluid intelligence test -- Raven's Advanced Progressive Matrices (RAPM) -- that varied from easy (around 80% correct) to difficult (around 20% correct). The same ratings were collected from four insight problems interleaved with…
Descriptors: Metacognition, Intelligence Tests, Intuition, Difficulty Level
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
Tyler A. Sassenberg; David M. Condon; Alexander P. Christensen; Colin G. DeYoung – Creativity Research Journal, 2023
Previous research has investigated the nature of imagination as a construct related to multiple forms of higher-order cognition. Despite the emergence of various conceptualizations of imagination, few attempts have been made to explore the structure of imagination as a trait in the context of existing hierarchically-nested personality dimensions.…
Descriptors: Imagination, Cognitive Processes, Measures (Individuals), Personality Assessment

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