Incorporating computational thinking (CT) ideas into core subjects, such as mathematics and science, is one way of bringing early computer science (CS) education into elementary school. Minimal research has explored how teachers can translate their knowledge of CT into practice to create opportunities for their students to engage in CT during their math and science lessons. Such information can support the creation of quality professional development experiences for teachers. We analyzed how eight elementary teachers created opportunities for their students to engage in four CT practices (abstraction, decomposition, debugging, and patterns) during unplugged mathematics and science activities. We identified three strategies used by these teachers to create CT opportunities for their students: framing, prompting, and inviting reflection. Further, we grouped teachers into four profiles of implementation according to how they used these three strategies. We call the four profiles (1) presenting CT as general problem-solving strategies, (2) using CT to structure lessons, (3) highlighting CT through prompting, and (4) using CT to guide teacher planning. We discuss the implications of these results for professional development and student experiences.
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High school biology teachers’ integration of computational thinking into data practices to support student investigations
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.
more » « less- Award ID(s):
- 1842090
- NSF-PAR ID:
- 10433036
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Journal of Research in Science Teaching
- Volume:
- 60
- Issue:
- 6
- ISSN:
- 0022-4308
- Page Range / eLocation ID:
- p. 1353-1384
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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