Access to higher education, particularly in countries with pronounced social inequality, can significantly influence social mobility and quality of life. In Brazil, distance learning students face challenges such as self-managed study, study-work balance, and financial constraints. In this context, AI-generated resources could support student learning and perceptions of their learning journey. In this study, we used Large Language Models to create two resources that aimed to enhance student learning and improve perceptions of assessments: study guides and personalized feedback. The research was conducted at a Brazilian higher education institution, approaching students predominantly from low to middle-income backgrounds. Our overarching goal was to improve students’ experience, learning quality, and sense of belonging by intentionally reviewing content and providing a comprehensive view of student progress, prioritizing skill development over grades, reducing dropout rates in distance learning courses, and introducing students to AI in an appropriate and ethical manner. Here, we present the results of the first application of these resources to the students from four courses using a multifaceted approach, including the analysis of student performance and survey feedback.