The present article proposes an approach to using students’ digital development trajectories to improve the quality of education. Designing a digital development trajectory has a positive effect on students’ motivation and active participation in deciding on its formation. The goal of the study is to create a conception of using methods and approaches of educational data mining and machine learning in analyzing and predicting digital development trajectories to improve the educational process quality. Implementation of learning management systems with the opportunity to dynamically track students’ academic performance allows timely correcting gaps appearing in students’ knowledge and thereby reducing the risk of them falling behind in their study group. Recording the obtained results of completed assignments and interactions with learning management systems also benefits teachers who get an opportunity to receive feedback in an implicit form and account for gaps appearing in the curriculum in a processed and aggregated form. The analysis is conducted based on a database of additional education in a primary school (grades 1-3). The present study examines several scenarios of using a digital development trajectory in education including students’ progress in an academic performance trajectory based on their grades, a trajectory in terms of time spent on solving problems to determine their complexity, and a heatmap for determining problematic areas and weak spots in each teacher’s educational course. Based on educational data from a learning management system, the authors present a set of recommendations for teachers on the adaptation of their educational course to students’ abilities promoting the increase of the overall quality of education.