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Eleonora Barelli; Michael Lodi; Laura Branchetti; Olivia Levrini – Science & Education, 2025
In a historical moment in which Artificial Intelligence and machine learning have become within everyone's reach, science education needs to find new ways to foster "AI literacy." Since the AI revolution is not only a matter of having introduced extremely performant tools but has been determining a radical change in how we conceive and…
Descriptors: Artificial Intelligence, Science Education, Cognitive Development, Cultural Influences
Xinyi Wang; Mohd Nazri Bin Abdul Rahman; Mohd Shahril Nizam Shaharom – Cogent Education, 2024
Augmented reality (AR) technology is increasingly utilized in cognitive development and education of preschoolers. The Augmented Reality Integrated STEM Preschooler (ARISP) module combines AR technology with STEM (Science, Technology, Engineering, and Mathematics) in teaching and learning activity. This study aims to assess the impacts of the…
Descriptors: Foreign Countries, Preschool Education, STEM Education, Learning Activities
LeMoine, Sarah; Reschke, Kathy; Greene, Kristen – ZERO TO THREE, 2017
Educators interact with more than 4 million infants and toddlers each week in the United States and can provide positive, nurturing experiences that enhance development. Tragically, the infant-toddler workforce in the United States often lacks the support and resources necessary to support their work. These urgent needs require comprehensive…
Descriptors: Infants, Toddlers, Early Childhood Education, Preschool Teachers
Investigating and Developing Engineering Students' Mathematical Modelling and Problem-Solving Skills
Wedelin, Dag; Adawi, Tom; Jahan, Tabassum; Andersson, Sven – European Journal of Engineering Education, 2015
How do engineering students approach mathematical modelling problems and how can they learn to deal with such problems? In the context of a course in mathematical modelling and problem solving, and using a qualitative case study approach, we found that the students had little prior experience of mathematical modelling. They were also inexperienced…
Descriptors: Engineering Education, Mathematical Models, Problem Solving, Qualitative Research
Attitudes towards Online Feedback on Writing: Why Students Mistrust the Learning Potential of Models
Strobl, Carola – ReCALL, 2015
This exploratory study sheds new light on students' perceptions of online feedback types for a complex writing task, summary writing from spoken input in a foreign language (L2), and investigates how these correlate with their actual learning to write. Students tend to favour clear-cut, instructivist rather than constructivist feedback, and guided…
Descriptors: Feedback (Response), Writing (Composition), Constructivism (Learning), Computer Mediated Communication