Interest is a critical fuel for and outcome of learning. Building on and refocusing the Four-Phase Model of interest development, this study provides a window into the ecology of the learning experience and interest it generates. This research uses a novel mobile assessment platform to test learning experiences in three university courses (Organic chemistry, biochemistry, and introduction to physics for non-majors) and pilots a micro-analytic approach to capturing these experiences during lectures/tutorials. Students' interest in tasks, a single class, and the domain of study were collected with short surveys through an online mobile platform during class, immediately following task experiences. Latent variance-based modelling suggested strong forward connections between interest in most tasks. The connections between prior knowledge and interest with a future interest in course tasks varied strongly and were dependent on the nature of the tasks. The nuance of these connections and their implications for mobile assessment are discussed.