Computational Thinking for Science Positions Youth to Be Better Science Learners

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Publicat a:Education Sciences vol. 15, no. 1 (2025), p. 105
Autor principal: Cannady, Matthew A
Altres autors: Collins, Melissa A, Hurt, Timothy, Montgomery, Ryan, Greenwald, Eric, Dorph, Rena
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MDPI AG
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100 1 |a Cannady, Matthew A 
245 1 |a Computational Thinking for Science Positions Youth to Be Better Science Learners 
260 |b MDPI AG  |c 2025 
513 |a Journal Article 
520 3 |a Computational thinking plays a central and ubiquitous role in many science disciplines and is increasingly prevalent in science instruction and learning experiences. This study empirically examines the computational thinking skills that are particular to engaging in science and science learning and then tests if these skills are predictive of science learning over the course of one semester. Using a sample from 600 middle school science students, we provide the psychometric properties of a computational thinking for science assessment and demonstrate that this construct is a consistent predictor of science content learning. The results demonstrate that the relationship between computational thinking for science and science content learning is consistent across variations in students and classrooms, above and beyond other demonstrated predictors—STEM fascination or scientific sensemaking. Further, the analysis also showed that experience with computer programming languages, especially block languages, is associated with higher levels of computational thinking. The findings reveal implications for research, teaching, and learning, including some implications for advancing equitable opportunities for students to develop computational thinking for science. This paper advances knowledge about how to ensure that students have the dispositions, skills, and knowledge needed to use technology-enabled scientific inquiry practices and to position them for success in science learning. 
610 4 |a National Research Council 
653 |a Problem solving 
653 |a Scientists 
653 |a Computer science 
653 |a Educational technology 
653 |a Cognitive ability 
653 |a Cognition & reasoning 
653 |a Skills 
653 |a Simulation 
653 |a Classrooms 
653 |a Councils 
653 |a Science education 
653 |a Design 
653 |a Taxonomy 
653 |a Data collection 
653 |a STEM education 
653 |a Middle school students 
653 |a Educational Practices 
653 |a Reading Skills 
653 |a Influence of Technology 
653 |a Active Learning 
653 |a Cognitive Processes 
653 |a Academic Achievement 
653 |a Learning Experience 
653 |a Mathematics Education 
653 |a Thinking Skills 
653 |a Data Analysis 
653 |a Science Instruction 
653 |a Elementary Secondary Education 
653 |a Data Processing 
653 |a College Science 
653 |a Inquiry 
653 |a Attention 
700 1 |a Collins, Melissa A 
700 1 |a Hurt, Timothy 
700 1 |a Montgomery, Ryan 
700 1 |a Greenwald, Eric 
700 1 |a Dorph, Rena 
773 0 |t Education Sciences  |g vol. 15, no. 1 (2025), p. 105 
786 0 |d ProQuest  |t Education Database 
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