This master thesis investigates the utility of spaced repetition learning in engineering education, focusing on knowledge retention for students. The study involved the development of an application with a Nest.js backend integrated with a MySQL database and a Next.js frontend, designed with human-computer interaction (HCI) principles to ensure usability and user-friendliness. Surveys were conducted to gather feedback on HCI and spaced repetition learning, although the limited number of participants affected the statistical significance of the findings. Initial responses indicate that the platform is perceived as easy to navigate but lack engagement due to its simplistic nature. The absence of distracting elements is noted, yet issues with font size consistency have been identified. Further feedback suggests that students are open to spaced repetition learning techniques. The study draws on previous research demonstrating the effectiveness of spaced repetition learning in enhancing long-term memory retention. The thesis aims to address the challenge of rapid memory erosion associated with traditional massed learning approaches. Further research is recommended to gather more substantial data and refine the platform for improved usability and effectiveness in engineering education.