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Jonathan Robert Bowers – ProQuest LLC, 2024
To make sense of our interconnected and algorithm driven world, students increasingly need proficiency with computational thinking (CT), systems thinking (ST), and computational modeling. One aspect of computational modeling that can support students with CT, ST, and modeling is testing and debugging. Testing and debugging enables students to…
Descriptors: Troubleshooting, Thinking Skills, Computation, Computer Science Education
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W. Paige Hall; Kevin Cantrell – Journal of Chemical Education, 2024
Human-driven carbon emissions have resulted in increased levels of dissolved carbon dioxide in the Earth's oceans. This dissolved carbon dioxide reacts with water to form carbonic acid, which impacts ocean acidity as well as the solubility of carbonate-containing compounds, with far-reaching impacts on marine ecosystems and the human communities…
Descriptors: Programming Languages, Computer Science Education, Chemistry, Marine Biology
Amelia Auchstetter; Eben Witherspoon; Oluchi Ozuzu; Jonathan Margolin; Lawrence B. Friedman – American Institutes for Research, 2023
The purpose of this study was to evaluate the implementation and impact of the Pack program. The Pack was developed by the New York Hall of Science (NYSCI) and includes a digital game and set of curricular and professional development resources that aim to support computational thinking teaching and learning in middle school science and computer…
Descriptors: Computation, Thinking Skills, Educational Games, Program Implementation
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Bush, Eliot C.; Adolph, Stephen C.; Donaldson-Matasci, Matina C.; Hur, Jae; Schulz, Danae – Journal of College Science Teaching, 2021
This paper describes an introductory biology course for undergraduates that heavily incorporates quantitative problem solving in activities and homework assignments. The course is broken up into a series of units, each organized around a motivating biological question or theme. Homework assignments address the theme or question, and typically…
Descriptors: Biology, Science Instruction, Teaching Methods, Problem Solving
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Phillips, A. M.; Gouvea, E. J.; Gravel, B. E.; Beachemin, P. -H.; Atherton, T. J. – Physical Review Physics Education Research, 2023
Computation is intertwined with essentially all aspects of physics research and is invaluable for physicists' careers. Despite its disciplinary importance, integration of computation into physics education remains a challenge and, moreover, has tended to be constructed narrowly as a route to solving physics problems. Here, we broaden Physics…
Descriptors: Physics, Science Instruction, Teaching Methods, Models
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Allbee, Quinn; Barber, Robert – Biochemistry and Molecular Biology Education, 2021
Biology is a data-driven discipline facilitated greatly by computer programming skills. This article describes an introductory experiential programming activity that can be integrated into distance learning environments. Students are asked to develop their own Python programs to identify the nature of alleles linked to disease. This activity…
Descriptors: Genetics, Science Instruction, Programming Languages, Biology
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Saba, Janan; Hel-Or, Hagit; Levy, Sharona T. – Instructional Science: An International Journal of the Learning Sciences, 2023
This article concerns the synergy between science learning, understanding complexity, and computational thinking (CT), and their impact on near and far learning transfer. The potential relationship between computer-based model construction and knowledge transfer has yet to be explored. We studied middle school students who modeled systemic…
Descriptors: Transfer of Training, Science Instruction, Learning Management Systems, Learning Processes
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Garcia, Victor; Conesa, Jordi; Perez-Navarro, Antoni – Journal of Science Education and Technology, 2022
Videos created with the hands of teachers filmed have been perceived as useful educational resource for students of Physics in undergraduate courses. In previous works, we analyzed the students' perception about educational videos by asking them about their experiences. In this work, we analyze the same facts, but from a learning analytics…
Descriptors: Physics, Science Instruction, Teaching Methods, Video Technology
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Margulieux, Lauren E.; Catrambone, Richard; Schaeffer, Laura M. – Instructional Science: An International Journal of the Learning Sciences, 2018
Originally intended as a replication study, this study discusses differences in problem solving performance among different domains caused by the same instructional intervention. The learning sciences acknowledges similarities in the learners' cognitive architecture that allow interventions to apply across domains, but it also argues that each…
Descriptors: Problem Solving, Intervention, Instructional Design, Programming
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Hutchins, Nicole M.; Biswas, Gautam; Maróti, Miklós; Lédeczi, Ákos; Grover, Shuchi; Wolf, Rachel; Blair, Kristen Pilner; Chin, Doris; Conlin, Luke; Basu, Satabdi; McElhaney, Kevin – Journal of Science Education and Technology, 2020
Synergistic learning combining computational thinking (CT) and STEM has proven to be an effective method for advancing learning and understanding in a number of STEM domains and simultaneously helping students develop important CT concepts and practices. We adopt a design-based approach to develop, evaluate, and refine our Collaborative,…
Descriptors: Physics, Science Instruction, STEM Education, Thinking Skills
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Ehsan, Hoda; Rehmat, Abeera P.; Cardella, Monica E. – Science and Children, 2019
Computational thinking can provide a basis for problem solving, for making evidence-based decisions, and for learning to code or create programs. Therefore, it is critical that all students across the K-12 continuum--including students in the early grades--have opportunities to begin developing problem solving and computational thinking skills.…
Descriptors: Teaching Methods, STEM Education, Computer Science Education, Thinking Skills
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Thomas, Debra Kelly; Milenkovic, Lisa; Marousky, Annamargareth – Science and Children, 2019
Computer science (CS) and computational thinking (a problem-solving process used by computer scientists) teach students design, logical reasoning, and problem solving--skills that are valuable in life and in any career. Computational thinking (CT) concepts such as decomposition teach students how to break down and tackle a large complex problem.…
Descriptors: Computation, Thinking Skills, Computer Simulation, Computer Science Education
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Rich, Kathryn M.; Yadav, Aman; Schwarz, Christina V. – Journal of Technology and Teacher Education, 2019
In order to create professional development experiences, curriculum materials, and policies that support elementary school teachers to embed computational thinking (CT) in their teaching, researchers and teacher educators must understand ways teachers see CT as connecting to their classroom practices. We interviewed 12 elementary school teachers,…
Descriptors: Thinking Skills, Teaching Methods, Faculty Development, Elementary School Teachers
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Tan, Verily; Nicholas, Celeste; Scribner, J. Adam; Francis, Dionne Cross – Technology and Engineering Teacher, 2019
With the introduction of "Next Generation Science Standards" ("NGSS"), teachers have been called to find meaningful and engaging ways to teach science content while incorporating engineering practices and, to a lesser extent, computing and computational thinking. The task becomes even more complex when they also have to…
Descriptors: Interdisciplinary Approach, Teaching Methods, Standards, Science Instruction
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Kolikant, Yifat Ben-David – Instructional Science: An International Journal of the Learning Sciences, 2011
This study demonstrates the power of the cultural encounter metaphor in explaining learning and teaching difficulties, using as an example computer science education (CSE). CSE is envisioned as an encounter between veterans of two computer-oriented cultures, that of the teachers and that of the students. Forty questionnaires administered to CS…
Descriptors: Computer Science Education, Figurative Language, Science Instruction, Questionnaires
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