Computational thinking (CT) is a thought process composed of computer science ideas and skills that can be applied to solve problems and better understand the world around us. With the increase in technology and computing, STEM disciplines are becoming interwoven with computing. In order to better prepare students for STEM careers, computational literacy needs to be developed in K–12 education. We advocate the introduction of computational literacy through the incorporation of CT in core science courses, such as biology. Additionally, at least some of this integration should be unplugged, or without computers, so that all schools can participate in developing computational literacy. These lessons integrate unplugged CT and science content to help students develop CT competencies and learn natural selection content simultaneously through a series of lessons in which unplugged CT is leveraged for natural selection learning within varying contexts. In these lessons, students engage in the creation of handwritten algorithmic explanations of natural selection. Students build CT skills while making sense of the process, resulting in converged learning about CT and science. This article presents a description of CT, the specifics of the classroom implementation and lessons, student work and outcomes, and conclusions drawn from this work.

Since antibiotics have become routinely used to treat infections, antibiotic resistance is now an emerging concern for public health. To understand how bacteria become resistant to antibiotics, many students draw from the common misconception that bacteria gain resistance upon antibiotic exposure. We have designed models and a corresponding lab that explores how a population of bacteria can evolve antibiotic resistance, with emphasis on dispelling common misconceptions surrounding the mechanism of antibiotic resistance. Using an antibiotic disk diffusion assay, students compare the antibiotic resistance level of a harmless E. coli strain of bacteria over time. Then, students compare their lab data to the models, which together illustrate the roles that initial genetic variation and random mutation play in the evolution of antibiotic resistance. In this guided investigation, basic microbiology concepts and techniques are made accessible to students in a high school classroom. The models developed here are in line with the practices of the Next Generation Science Standards ( NGSS ). The models, together with the lab, are used to guide students through the process of argumentation using a claim, evidence, and reasoning (CER) format to explain the evolutionary mechanisms of antibiotic resistance.

The educational video game Mission Biotech provides a virtual experience for students in learning biotechnology materials and tools. This study explores the use of Mission Biotech and the associated curriculum by three high school teachers and their students. All three classes demonstrated gains on a curriculum-aligned test of science content. Students from two of the classes showed gains on a standards-aligned test of content; students from the third class did not demonstrate statistically significant gains. This result is attributable to a ceiling effect. The results support the idea that video games can be useful in classroom contexts. No statistically significant changes were found when looking at how the game affected student attitudes toward science and science careers.