In this study, we present the design and evaluation of PlenaMap—a natural language-supported geospatial learning tool aimed at closing the gap between student learners utilizing geospatial learning tools. To achieve this, we constructed a scaffold based on Wenger’s “windows” construct and integrated a large language model. We then evaluated its effectiveness in supporting high school students in Puerto Rico as they identified and engaged with local problems using geospatial data and visualizations. The evaluation was conducted through two independent workshops with six students from different regions of Puerto Rico. Using conjecture maps, we detail the design process, user interactions, and intended outcomes to provide readers with a holistic view of the design work. Through thematic analysis, we highlight students’ interactions and experiences with PlenaMap. We found that students engaged with the tool in ways consistent with geospatial practices (e.g., asking geographic questions and gathering geographic data). Students reported that the natural language-based interface made problem-solving and the research process more approachable and less intimidating. We conclude by discussing the design implications of LLM-based geospatial learning tools as scaffolds to better support the needs of high school students.