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Abstract Computational thinking is crucial for STEM researchers and practitioners, as it involves more than just developing skills—it is a way of thinking that enables effective problem-solving. STEM disciplines approach different problems and as such employ computational thinking uniquely, so students cannot rely solely on computer science to develop computational thinking. Less attention has been given to social aspects of computation, such as collaborating and communicating with and about computation even though social aspects are essential to problem solving. We utilized computational literacy as an alternative framework that explicitly includes social elements as a primary pillar. We conducted 15 interviews with STEM researchers to identify and organize the social aspects that play a role in their research. We organized goals by motivation (persuasion and productivity) and representation (visual and non-visual) to contextualize the use of communication in computation. We found that researchers use computation to explain research results, navigate decision making, establish rigor, ensure reproducibility, facilitate lab stability, and promote research efficiency. We used Activity Theory to describe the tools, norms, and communities associated with these goals to offer a more detailed framework for the social pillar of computational literacy within the context of science and engineering. Examples from each discipline within STEM are described. This social computational literacy framework can act as a guide for STEM educators and practitioners alike to use and teach social aspects of computation. 

Visual models are a necessary part of molecular biology education because submicroscopic compounds and processes cannot be directly observed. Accurately interpreting the biological information conveyed by the shapes and symbols in these visual models requires engaging visual literacy skills. For students to develop expertise in molecular biology visual literacy, they need to have structured experiences using and creating visual models, but there is little evidence to gauge how often undergraduate biology students are provided such opportunities. To investigate students’ visual literacy experiences, we surveyed 66 instructors who taught lower division undergraduate biology courses with a focus on molecular biology concepts. We collected self-reported data about the frequency with which the instructors teach with visual models and we analyzed course exams to determine how instructors incorporated visual models into their assessments. We found that most instructors reported teaching with models in their courses, yet only 16% of exam items in the sample contained a visual model. There was not a statistically significant relationship between instructors’ self-reported frequency of teaching with models and extent to which their exams contained models, signaling a potential mismatch between teaching and assessment practices. Although exam items containing models have the potential to elicit higher-order cognitive skills through model-based reasoning, we found that when instructors included visual models in their exams the majority of the items only targeted the lower-order cognitive skills of Bloom’s Taxonomy. Together, our findings highlight that despite the importance of visual models in molecular biology, students may not often have opportunities to demonstrate their understanding of these models on assessments.