Students’ experiences of learning are comprised of dynamic sequences of intraindividual processes that take place in real-time throughout school days and weeks. Researchers can investigate these processes in diary, intensive longitudinal, or micro-analytic studies. Important questions posed by these are (1) whether learning processes are stable or variable, and (2) how instruction can promote such processes. Indeed, there is a current surge in intraindividual studies using experience sampling or ecological momentary assessment for collecting such real-time data owing to user-friendly electronic devices (e.g., iPads, tablets). Real-time data have advantages above cross-sectional data for drawing inferences and theorizing about processes, as retrospective reporting is minimized and contextual closeness maximized. Multilevel Structural Equation Models are used for analyses of hierarchically nested data (i.e., learning experiences nested in students). In all, the intraindividual (process, situation-specific, within-person) approach to educational research offers a unique window into learners’ and teachers’ experiences of learning and teaching, which is different from that of an interindividual (cross-sectional, between-person) approach. In this inaugural talk I will present key findings from the Learning Every Lesson (LEL) study and other recent studies. Some implications for policies on personalized learning are suggested.