Creating and developing mathematical models to solve real-world problems is a complex task and students often have difficulties in tackling it successfully. The design and implementation of sequences that help students autonomously develop their ability to solve modelling tasks could be a useful scaffolding tool to foster modelling learning. In this paper we present a sequence of estimation tasks in a real context based on what we have called the upscaling technique, which consists of scaling the accessibility and knowledge of the context used. A study with two samples of grade 10 students, experimental and control, has allowed us to find out whether this sequence promotes success in solving complex contextualized estimation problems and whether it helps students to improve their mathematical models.