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Camilo Vieira; J. Chiu; B. Velasquez – Computer Science Education, 2024
Background and Context: Computational thinking (CT) is a fundamental skill and a new form of literacy that everyone should develop to participate in civic society. Sequencing and algorithmic thinking are at the core of CT. This study looked into how young children enrolled in a kindergarten in Colombia develop CT skills. Objective: This paper aims…
Descriptors: Children, Algorithms, Mental Computation, Foreign Countries
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Eva Portelance; Michael C. Frank; Dan Jurafsky – Cognitive Science, 2024
Interpreting a seemingly simple function word like "or," "behind," or "more" can require logical, numerical, and relational reasoning. How are such words learned by children? Prior acquisition theories have often relied on positing a foundation of innate knowledge. Yet recent neural-network-based visual question…
Descriptors: Vocabulary, Grammar, Visual Aids, Language Acquisition
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Arastoopour Irgens, Golnaz; Adisa, Ibrahim; Bailey, Cinamon; Vega Quesada, Hazel – Educational Technology & Society, 2022
As big data algorithm usage becomes more ubiquitous, it will become critical for all young people, particularly those from historically marginalized populations, to have a deep understanding of data science that empowers them to enact change in their local communities and globally. In this study, we explore the concept of critical machine…
Descriptors: Artificial Intelligence, Children, Algorithms, After School Programs
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Soukaina Gouraguine; Mohammed Qbadou; Mohamed Rafik; Mustapha Riad; Khalifa Mansouri – Journal of Information Technology Education: Research, 2023
Aim/Purpose: Our study is focused on prototyping, development, testing, and deployment of a new knowledge primitive for the humanoid robot assistant NAO, in order to enhance student visual learning by establishing a human-robot interaction. Background: This new primitive, utilizing a convolutional neural network (CNN), enables real-time…
Descriptors: Robotics, Technology Uses in Education, Algorithms, Children
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Allison Starks; Stephanie Michelle Reich – Information and Learning Sciences, 2024
Purpose: This study aims to explore children's cognitions about data flows online and their understandings of algorithms, often referred to as algorithmic literacy or algorithmic folk theories, in their everyday uses of social media and YouTube. The authors focused on children ages 8 to 11, as these are the ages when most youth acquire their own…
Descriptors: Concept Formation, Children, Social Media, Video Technology