Learning Analytics and Recommender Systems Toward Remote Experimentation

Alexandre L. Gonçalves, Gustavo R. Alves, Lucas M. Carlos, Juarez Bento da Silva, João Bosco da Mota Alves
2018 Learning Analytics Summer Institute Spain  
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 the
more » ... t server that evaluates whether a particular request can be performed or not. With the log analysis, it was possible to obtain information in order to determine some initial statistics and provide clues about the student's behavior during the experiments. Using the concept of recommendation, a service is proposed through request analysis and returns to the students more precise information about possible mistakes in the assembly of circuits or configurations. The process as a whole proves consistent in what regards its ability to provide suggestions to the students as they conduct the experiments. Furthermore, with the log, relevant information can be offered to teachers, thus assisting them in developing strategies to positively impact student's learning.
dblp:conf/lasi-spain/GoncalvesACSA18 fatcat:qtnhhjr225duhlhkwdbytvm6q4