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Abstract In the United States, the Next Generation Science Standards advocate for the integration of computational thinking (CT) as a science and engineering practice. Additionally, there is agreement among some educational researchers that increasing opportunities for engaging in computational thinking can lend authenticity to classroom activities. This can be done through introducing CT principles, such as algorithms, abstractions, and automations, or through examining the tools used to conduct modern science, emphasizing CT in problem solving. This cross‐case analysis of nine high school biology teachers in the mid‐Atlantic region of the United States documents how they integrated CT into their curricula following a year‐long professional development (PD). The focus of the PD emphasized data practices in the science teachers' lessons, using Weintrop et al.'s definition of data practices. These are: (a) creation (generating data), (b) collection (gathering data), (c) manipulation (cleaning and organizing data), (d) visualization (graphically representing data), and (e) analysis (interpreting data). Additionally, within each data practice, teachers were asked to integrate at least one of five CT practices: (a) decomposition (breaking a complex problem into smaller parts), (b) pattern‐recognition (identifying recurring similarities in data practices), (c) algorithms (the creation and use of formulas to predict an output given a specific input), (d) abstraction (eliminating detail in order to generalize or see the “big picture”), and (e) automation (using computational tools to carry out specific procedures). Although the biology teachers integrated all CT practices across their lessons, they found it easier to integrate decomposition and pattern recognition while finding it more difficult to integrate abstraction, algorithmic thinking, and automation. Implications for designing professional development experiences are discussed.
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High school science teacher use of planning tools to integrate computational thinking.
In an effort to deepen learning in K-12 science classrooms, there has been a national movement to integrate computational thinking (CT). The purpose of this phenomenographic study was to understand teachers’ perceptions of the function and usefulness of a task analysis and a decision tree tool designed to help them with integration. Teachers participated in a long-term professional development to improve their knowledge and application of CT and then developed lesson plans integrating CT into science investigations. To assist in the integration, teachers used the two unique tools. No one lesson plan or content area addressed all of the CT practices, but all CT practices were addressed in lessons across all four science areas. All 19 teachers found that the task analysis tool helped them to shift their lessons to a student-centered focus and helped them pinpoint data practices so they could systematically integrate CT practices. However, they expressed confusion over the amount of detail to document on the tool. Similarly, teachers found both benefits and barriers to the decision tree tool. Teachers found the decision tree tool to be useful in predicting the ways students may misunderstand a data practice and in reflecting on the level of accomplishment of students. However, teachers were sometimes uncertain with how to efficiently document complex student behaviors when engaged with data practices and CT. Implications for the use of the two lesson planning tools is discussed.
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- Award ID(s):
- 1842090
- PAR ID:
- 10339701
- Date Published:
- Journal Name:
- Journal of science teacher education
- ISSN:
- 1573-1847
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1080/1046560X.2021.1970088
