Engaging middle school students in complex computational topics such as AI can pose unique challenges to instructors, ranging from simplifying potentially difficult mathematical material to maintaining student interest in the subject. One approach to address these challenges is to utilize hands-on, real-world examples. We conducted a week-long summer camp for 24 students, centering each day around one of the Five Big Ideas in AI. Students participated in exit ticket reflections following pathfinding activities that incorporated real-world examples and digital simulations of three pathfinding algorithms (A*, depth-first search, breadth-first search), including a project modeled after the game Pac-Man. Thematic analysis of responses revealed four major themes regarding students’ key takeaways from the activities: (1) pathfinding for character movement, notably in video games like Minecraft; (2) pathfinding as a means of efficient navigation; (3) theoretical reasoning regarding the speed of the A* algorithm compared to others, highlighting its intelligent search mechanism; and (4) empirical reasoning based on personal experience during activities, where some students noted A* consistently performed fastest. These findings indicate that students not only engaged with pathfinding concepts but also demonstrated a nuanced understanding of algorithmic efficiency. We examine the implications of these findings on understanding student engagement with interactive pathfinding activities and highlight the potential for future work on the subject.