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Beth A. Covitt; Kristin L. Gunckel; Alan Berkowitz; William W. Woessner; John Moore – Journal of Science Education and Technology, 2024
Computational models are employed to study and respond to pressing environmental issues such as groundwater contamination. This use of computational models, which often involves algorithms and uncertainty that are hidden to the public, has implications for environmental science literacy. This study applies a design-based research approach to…
Descriptors: Learning Experience, Computation, Thinking Skills, Models
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Emil Eidin; Tom Bielik; Israel Touitou; Jonathan Bowers; Cynthia McIntyre; Dan Damelin; Joseph Krajcik – Journal of Science Education and Technology, 2024
Understanding the world around us is a growing necessity for the whole public, as citizens are required to make informed decisions in their everyday lives about complex issues. Systems thinking (ST) is a promising approach for developing solutions to various problems that society faces and has been acknowledged as a crosscutting concept that…
Descriptors: Chemistry, Science Instruction, High School Students, Educational Technology
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Bowers, Jonathan; Eidin, Emanuel; Stephens, Lynn; Brennan, Linsey – Journal of Science Education and Technology, 2023
Interpreting and creating computational systems models is an important goal of science education. One aspect of computational systems modeling that is supported by modeling, systems thinking, and computational thinking literature is "testing, evaluating, and debugging models." Through testing and debugging, students can identify aspects…
Descriptors: Computer Science Education, Systems Approach, Thinking Skills, Science Education
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Bielik, Tom; Stephens, Lynn; McIntyre, Cynthia; Damelin, Daniel; Krajcik, Joseph S. – Journal of Science Education and Technology, 2022
Developing and using models to make sense of phenomena or to design solutions to problems is a key science and engineering practice. Classroom use of technology-based tools can promote the development of students' modelling practice, systems thinking, and causal reasoning by providing opportunities to develop and use models to explore phenomena.…
Descriptors: Learning Activities, Models, Technology Uses in Education, Thinking Skills
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Arik, Merve; Topçu, Mustafa Sami – Journal of Science Education and Technology, 2022
Studies maintain that computational thinking (CT) is associated with science content and scientific processes as well as with many disciplines. It is thought that designing teaching processes in which science and CT processes take place together makes science learning more meaningful. With this in mind, in this study, the researchers integrated…
Descriptors: Computation, Thinking Skills, Science Process Skills, Science Education
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Lamb, Richard; Hand, Brian; Kavner, Amanda – Journal of Science Education and Technology, 2021
This study is intended to provide an example of computational modeling (CM) experiment using machine learning algorithms. Specific outcomes modeled in this study are the predicted influences associated with the Science Writing Heuristic (SWH) and associated with the completion of question items for the Cornell Critical Thinking Test. The Student…
Descriptors: Models, Computation, Content Area Writing, Science Education
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Sirakaya, Mustafa; Alsancak Sirakaya, Didem; Korkmaz, Özgen – Journal of Science Education and Technology, 2020
This study aimed to investigate the relationships among computational thinking (CT) skills, science, technology, engineering and mathematics (STEM) attitude, and thinking styles with the help of structural equation modeling and to determine to what extent the variables of STEM attitude and thinking styles explained CT skills. The study, conducted…
Descriptors: STEM Education, Thinking Skills, Structural Equation Models, Correlation
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Aksit, Osman; Wiebe, Eric N. – Journal of Science Education and Technology, 2020
Computational thinking (CT) and modeling are authentic practices that scientists and engineers use frequently in their daily work. Advances in computing technologies have further emphasized the centrality of modeling in science by making computationally enabled model use and construction more accessible to scientists. As such, it is important for…
Descriptors: Thinking Skills, Science Instruction, Teaching Methods, Computer Science Education
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Dickes, Amanda Catherine; Farris, Amy Voss; Sengupta, Pratim – Journal of Science Education and Technology, 2020
In recent years, the field of education has challenged researchers and practitioners to incorporate computing as an essential focus of K-12 STEM education. Integrating computing within K-12 STEM supports learners of all ages in codeveloping and using computational thinking in existing curricular contexts alongside practices essential for…
Descriptors: Elementary School Science, Coding, STEM Education, Computer Science Education
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Rates, Christopher A.; Mulvey, Bridget K.; Feldon, David F. – Journal of Science Education and Technology, 2016
Components of complex systems apply across multiple subject areas, and teaching these components may help students build unifying conceptual links. Students, however, often have difficulty learning these components, and limited research exists to understand what types of interventions may best help improve understanding. We investigated 32 high…
Descriptors: Concept Formation, Systems Approach, High School Students, Simulation
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Jang, Hyewon – Journal of Science Education and Technology, 2016
Gaps between science, technology, engineering, and mathematics (STEM) education and required workplace skills have been identified in industry, academia, and government. Educators acknowledge the need to reform STEM education to better prepare students for their future careers. We pursue this growing interest in the skills needed for STEM…
Descriptors: STEM Education, Work Environment, Interrater Reliability, Engineering Education
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Hsu, Ying-Shao; Lin, Li-Fen; Wu, Hsin-Kai; Lee, Dai-Ying; Hwang, Fu-Kwun – Journal of Science Education and Technology, 2012
This study compared modeling skills and knowledge structures of four groups as seen in their understanding of air quality. The four groups were: experts (atmospheric scientists), intermediates (upper-level graduate students in a different field), advanced novices (talented 11th and 12th graders), and novices (10th graders). It was found that when…
Descriptors: Models, Scientists, Graduate Students, Thinking Skills
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van Borkulo, Sylvia P.; van Joolingen, Wouter R.; Savelsbergh, Elwin R.; de Jong, Ton – Journal of Science Education and Technology, 2012
Computer modeling has been widely promoted as a means to attain higher order learning outcomes. Substantiating these benefits, however, has been problematic due to a lack of proper assessment tools. In this study, we compared computer modeling with expository instruction, using a tailored assessment designed to reveal the benefits of either mode…
Descriptors: Direct Instruction, Computer Assisted Instruction, Climate, Task Analysis
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Stratford, Steven J.; Krajcik, Joseph; Soloway, Elliot – Journal of Science Education and Technology, 1998
Explores dynamic modeling as an opportunity for students to think about the science content they are learning. Concludes that creating dynamic models has great potential for use in classrooms to engage students in analysis, relational reasoning, and synthesis. Contains 21 references. (DDR)
Descriptors: Cognitive Processes, Concept Formation, Models, Science Curriculum
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Pek, Peng-Kiat; Poh, Kim-Leng – Journal of Science Education and Technology, 2000
Presents the application of decision-theoretic technique to a computer-based tutoring system for elementary mechanics. Uses sound probabilistic reasoning and a student model to identify learners' misconceptions. Focuses on the integration of Bayesian belief networks, item response theory, decision analysis, and database management systems in…
Descriptors: Academic Ability, Cognitive Processes, Computers, Elementary Education
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