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This paper presents a process based on learning analytics and recommender systems to provide suggestions to students about remote laboratories activities in order to scaffold their performance. For this purpose, the records of remote experiments from the VISIR project were analyzed taking into account one of its installations. Each record is composed of requests containing the assembled circuits and the configurations of the measuring equipment, as well as the response provided by thedblp:conf/lasi-spain/GoncalvesACSA18 fatcat:qtnhhjr225duhlhkwdbytvm6q4