An important advantage of e-learning environments is the numerical observation of the learning behaviors of students. The use of e-learning environments by students creates a learner data. From these learner data, the navigation patterns obtained by using educational data mining have a very important place in learning and teaching design. Studies have shown that learners' learning behaviors in online learning environments may vary according to the characteristics of learners. Studies on the differentiation of the navigation patterns according to the psycho-educational characteristics of the learners provide very strong inputs to the design of the learning environment appropriate to the characteristics of the students which is named as adaptive learning environments. According to these inputs, learning environment designs can be developed according to the individual characteristics of the students. Online learners' readiness (OLR) for e-learning is an important psycho-educational structure. The aim of this study is to investigate students' navigations in the e-learning environment according to the level of readiness for e-learning. Lag sequential analysis was used when students' system interactions were analyzed sequentially. According to the results of the analysis, it has been found that the sequential navigation patterns of the students differ according to the OLR structure. The findings of this research are expected to provide important information and suggestions to online learning environment designers. [For the complete proceedings, see ED600498.]