High school biology teachers’ integration of computational thinking into data practices to support student investigations

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.

How do thinking styles and STEM attitudes have effects on computational thinking? A structural equation modeling analysis

“…The interaction between CT and STEM also provides new insight into the construct, nature, and definition of CT. Wing (2006) stated that CT “complements and combines mathematical and engineering thinking” (p. 35). It is also pointed out that CT skills are required by and can be learned in various disciplines (Sung & Black, 2020), especially the STEM disciplines (e.g., Chen & Terada, 2021; Gunckel et al, 2022; Kite & Park, 2023; Lilly et al, 2022; NGSS Lead States, 2013; Peters‐Burton et al, 2023; Rachmatullah & Wiebe, 2022). For instance, The Next Generation Science Standards (NGSS) advocate using CT to develop scientific understanding (NGSS Lead States, 2013).…”

“…Meanwhile, CT should not only receive attention in computer science education but should also be incorporated into teaching and curriculum across all subjects, especially STEM subjects. For instance, more CT‐integrated classroom activities can be implemented to develop students' scientific understanding (e.g., Kite & Park, 2023; NGSS Lead States, 2013; Peel et al, 2019), advance students' scientific reasoning (e.g., Irgens et al, 2020) and support students' scientific inquiry (e.g., Peters‐Burton et al, 2023).…”

“…Recently, much research has highlighted the critical importance of CT (e.g., Dagli & Tokmak, 2021; Grizioti & Kynigos, 2021; Guggemos, 2021; International Society for Technology in Education, 2016; Kynigos & Grizioti, 2020; Tikva & Tambouris, 2021; Wing, 2006). In response to the constantly evolving needs for computationally literate workforces (Asbell‐Clarke et al, 2021; Rowe et al, 2021; Song et al, 2021), CT has been integrated into the curricula (e.g., Lei et al, 2020; Sun, Hu, & Zhou, 2021), especially the science, technology, engineering and mathematics (STEM) curricula (e.g., Chen & Terada, 2021; Gunckel et al, 2022; Kite & Park, 2023; Lilly et al, 2022; NGSS Lead States, 2013; Peters‐Burton et al, 2023; Rachmatullah & Wiebe, 2022) of many countries.…”