New educational technologies that utilize students' interaction data and visualizations provide a means to expand our understanding of learning processes. In this study, we apply two advanced and novel data visualization techniques, called the "Indivisualizer" and a "Sankey diagram," to explore how middle school students (N = 343) solved problems in a game-based dynamic algebraic notation tool. Specifically, this study (1) illustrates the application of a set of data visualization techniques using clickstream data collected from the tool and explores the detailed step by step information about students' algebraic problem-solving processes that these visualizations provide, and (2) examines the associations between the productivity of initial solution strategies, prior knowledge, and efficiency of problem-solving. The results indicate a large variation in the types of strategies that students use to solve the problems, with some approaches being more efficient than others. Moreover, the productivity of initial solution strategies and prior knowledge significantly predict the efficiency scores in the game, indicating that noticing the structure of the equations plays a significant role in problem-solving. The findings suggest that these visualizations can be used both in research and practice to reveal and unpack our understanding of variability in mathematical problem-solving strategies and cognition. [For the corresponding grantee submission, see ED625475.]