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The ability to interpret and create an argument from data is a crucial skill for budding scientists, yet one that is seldom practiced in introductory courses. During this argumentation module, students in a large lecture class will work in groups to understand how a single mutation can lead to an obvious phenotypic change among tomatoes. Before the module begins, students are provided with background information on mutations and techniques to give them a starting point to explain what they will see in the data. In class, students will use data from the primary literature to understand the relationship between single amino acid mutations and phenotypic variation within the context of a “big question” about garden tomatoes that ripen without turning red. Over two days, small groups will negotiate data, create and evaluate hypotheses, and consolidate their understanding through clicker questions and writing tasks. Together, they will craft an argument for how mutations can lead to phenotypic changes, even if they do not lead to disease like in many common examples. Through this activity, the instructor and students work together to understand an engaging and relevant example of the central dogma. During our implementation of this activity, we observed high engagement with the in-class and out-of-class aspects of the argumentation activities to explain how a single mutation could result in a visible change to the flesh of a tomato. 

Departments are now recognized as an important locus for sustainable change on university campuses. Making sustainable changes typically requires a shift in culture, but culture is complex and difficult to measure. For this reason, cultural changes are often studied using qualitative methods that provide rich, detailed data. However, this imposes barriers to measuring culture and studying change at scale (i.e., across many departments). To address this issue, we introduce the Departmental Education and Leadership Transformation Assessment (DELTA), a new survey aimed at capturing cultural changes in undergraduate departments. We describe the survey’s development and validation and provide suggestions for its utility for researchers and practitioners. 

The instructional practices used in introductory college courses often differ dramatically from those used in high school courses, and dissatisfaction with these practices is cited by students as a prominent reason for leaving science, technology, engineering, and mathematics (STEM) majors. To better characterize the transition to college course work, we investigated the extent to which incoming expectations of course activities differ based on student demographic characteristics, as well as how these expectations align with what students will experience. We surveyed more than 1500 undergraduate students in large introductory STEM courses at three research-intensive institutions during the first week of classes about their expectations regarding how class time would be spent in their courses. We found that first-generation and first-semester students predict less lecture than their peers and that class size had the largest effect on student predictions. We also collected classroom observation data from the courses and found that students generally underpredicted the amount of lecture observed in class. This misalignment between student predictions and experiences, especially for first-generation and first-semester college students and students enrolled in large- and medium-size classes, has implications for instructors and universities as they design curricula for introductory STEM courses with explicit retention goals.