Influence of students' learning trajectory on their academic success in online self-directed learning environments

In online self-directed learning environments, it is important to see how different learning trajectories of students influence their academic success. Understanding this influence is key for the improvement of the design of these environments and the methodologies applied.
In this doctoral thesis we present the results of a research conducted with the objective of identifying how the decisions that students make in their learning process in a learning environment based on self-direction affect their learning process, and how this decision in the learning process influences their academic success. This research is carried out in online programs designed with the Self Directed Based Learning (SDBL) teaching methodology. This teaching methodology is designed to adapt to the profile of adult learners, for this reason it is based on self-directed learning and situational learning.
This research aims to identify what types of learning trajectories a student follows in his learning process in a learning environment based on self-direction, and if there is a relationship between this learning trajectory that he decides to follow with the achievement of learning outcomes. This relationship gives an answer to the adequacy of self-direction applied to their learning and to the adequacy of these learning environments for this learner profile.
The analysis is performed with Educational Data Mining tools applied on learning data collected in the Virtual Learning Platform. The training activities developed by the student and how these are associated to the learning process are analyzed in order to identify their learning trajectory. The analysis also incorporates an exploration of the influence of personality traits on the decision of the learning trajectory.
The results obtained show how the self-direction presented by the students in this learning environment leads to different learning trajectories. It can be seen how students change their decisions regarding the learning process to be followed as the training program evolves, following different learning trajectories in different subjects. From this research it can be concluded that students adopt different learning trajectories and that in all cases they lead to academic success. Even so, this achievement is higher when students follow the learning trajectory proposed by the instructional design of the applied teaching methodology.
This thesis provides a systematization in the study of online self-directed learning based on the concept of learning trajectory. This systematization is structured in the identification of the Hypothetical Learning Trajectory (HLT) designed in the teaching methodology implemented and in the analysis of the indicators of completion and academic success from clustering tools. The categorization of the results allows us to identify the existing learning trajectories and to observe the influence of each one of them on academic success.