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Behnam Karami; Caspar M. Schwiedrzik – npj Science of Learning, 2024
Visual objects are often defined by multiple features. Therefore, learning novel objects entails learning feature conjunctions. Visual cortex is organized into distinct anatomical compartments, each of which is devoted to processing a single feature. A prime example are neurons purely selective to color and orientation, respectively. However,…
Descriptors: Visual Perception, Visual Learning, Novelty (Stimulus Dimension), Brain Hemisphere Functions
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Sachio Otsuka; Yuki Miura; Jun Saiki – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2024
It has been reported that visual statistical learning (VSL) is facilitated in skewed distributions. However, it remains unclear whether enhancement of VSL in Zipfian distributions is due to consciousness of the regularities presented at high frequency. This study addressed this issue. We measured participants' subjective confidence in regularities…
Descriptors: Foreign Countries, College Students, Visual Learning, Visual Stimuli
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Stefan Depeweg; Contantin A. Rothkopf; Frank Jäkel – Cognitive Science, 2024
More than 50 years ago, Bongard introduced 100 visual concept learning problems as a challenge for artificial vision systems. These problems are now known as Bongard problems. Although they are well known in cognitive science and artificial intelligence, only very little progress has been made toward building systems that can solve a substantial…
Descriptors: Visual Learning, Problem Solving, Cognitive Science, Artificial Intelligence
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Injae Hong; Jeremy M. Wolfe – Cognitive Research: Principles and Implications, 2024
In classic visual search, observers typically search for the presence of a target in a scene or display. In foraging tasks, there may be multiple targets in the same display (or "patch"). Observers typically search for and collect these target items in one patch until they decide to leave that patch and move to the next one. This is a…
Descriptors: Food, Visual Learning, Decision Making, Learning Activities
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Don Ambrose – International Journal for Talent Development and Creativity, 2024
This interdisciplinary, conceptual analysis addresses the nature and benefits of artistic processes in learning and work. While recognizing various forms of artistry, the emphasis is on visual-spatial thinking. The benefits of this kind of thinking in academic and professional activities include the simplification of massively complex writing,…
Descriptors: STEM Education, Visual Learning, Visual Literacy, Spatial Ability
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Melissa Ballesteros-Mejía; María Angélica Madero – Journal of Visual Literacy, 2024
Images are central to our understanding of and learning about our world. We argue that visual training needs to be improved in the higher education system to enhance the potential of visual thinking to mediate productively our relationship with the context we inhabit. Initiatives from the social sciences and humanities since the end of the twenty…
Descriptors: Visual Literacy, Visual Learning, Interdisciplinary Approach, Higher Education
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Reza Pishghadam; Shaghayegh Shayesteh; Farveh Daneshvarfard; Nasim Boustani; Zahra Seyednozadi; Mohammad Zabetipour; Morteza Pishghadam – Journal of Psycholinguistic Research, 2024
This study mainly examined the role of the combination of three senses (i.e., auditory, visual, and tactile) and five senses (i.e., auditory, visual, tactile, olfactory, and gustatory) in the correlation between electrophysiological and electrodermal responses underlying second language (L2) sentence comprehension. Forty subjects did two…
Descriptors: Second Language Learning, Multisensory Learning, Auditory Perception, Visual Learning
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Yuchen Chen; Xinli Zhang; Lailin Hu – Educational Technology & Society, 2024
In conventional ancient Chinese poetry learning, students tend to be under-motivated and fail to understand many aspects of poetry. As generative artificial intelligence (GAI) has been applied to education, image-GAI (iGAI) provides great opportunities for students to generate visualized images based on their descriptions of poems, and to situate…
Descriptors: Elementary School Students, Grade 5, Poetry, Artificial Intelligence