This case study examines an interactive, low barrier process, termed instructor-in-the-loop, by which an instructor defines and makes meaning from exploratory metrics and visualizations, and uses this multimodal information to improve a course iteratively. We present potentials for course improvement based on automated learning analytics insights related to students' participation in small active learning sessions associated with a large lecture course. Automated analytics processes are essential for larger courses where engaging smaller groups is important to ensure participation and understanding, but monitoring a large total number of groups throughout an instructional experience becomes untenable for the instructor. Of interest is providing instructors with easy-to-digest summaries of group performance that do not require complex set up and knowledge of more advanced algorithmic approaches. We explore synthesizing metrics and visualizations as ways to engage instructors in meaning making of complex learning environments, but in a low barrier manner that provides insights quickly.