Abstract: In order to incorporate active learning techniques that mirror the practices of science for college science learners, modeling activities were introduced to the curriculum of large-lecture introductory biology courses. While in the classroom, students work in groups of three using electronic tablets to create scientific models of various biological phenomena such as gene expression and protein engineering. Group discussion and tablet screen capture were recorded to assess how students participated in the modeling tasks and how they used their time (e.g., on-task vs. off-task and discussion on which components to include and why). This talk will discuss on-going data analysis of recordings including constructing analytical categories to code the videos and producing descriptive portraits of each modeling group’s class modeling activity. These portraits provide a summary of what students are discussing and drawing, and help to determine coding themes that are then recursively used to inform the analytical coding categories. Current analysis indicates that most groups spend most of the time on-task and that students discussed which components to include, but rarely explain why they are including certain components. Additionally, we have found very few instances of argument related to what to include in the model. This may suggest that students are treating the activity as a worksheet rather than as a practice to understand the phenomena. This presentation will summarize the main findings from this study thus far as well as the implications for those findings and solicit feedback from the audience about future directions.