Algorithmic thinking is a type of thinking that occurs in the context of computational thinking. Given its importance in the current educational context, it seems pertinent to deepen into its conceptual and operational understanding for teaching. The exploration of research shows us that there are almost no studies at university level where algorithmic thinking is connected to mathematical thinking, and more importantly, to characterise it and be able to analyse and evaluate it better. The aim of this research is to characterise algorithmic thinking in a university context of the Bachelor's Degree in Mathematics by unplugged tasks, offering a model of analysis through categories that establish connections between mathematical and algorithmic working spaces in three dimensions, semiotic, instrumental and discursive. The results confirm the interaction between these dimensions and their predictive value for better programming performance. The study also adds novel considerations related to the role and interaction of mathematical and computational thinking categories involved in algorithmic thinking.Instituto de Matemática Interdisciplinar (IMI)Fac. de Ciencias MatemáticasTRUEUnión EuropeaMinisterio de Ciencia e Innovaciónpu
