In educational environments, monitoring persons' progress over time may help teachers to evaluate the effectiveness of their teaching procedures. Electronic learning environments are increasingly being used as part of formal education and resulting datasets can be used to understand and to improve the environment. This study presents longitudinal models based on the item response theory (IRT) for measuring persons' ability within and between study sessions in data from web-based learning environments. Two empirical examples are used to illustrate the presented models. Results show that by incorporating time spent within- and between-study sessions into an IRT model; one is able to track changes in ability of a population of persons or for groups of persons at any time of the learning process.