Encontrando os padrões sequenciais em apresentações orais de estudantes utilizando Sequential Pattern Mining

Resumo

The present paper describes a sequential pattern mining based approach to identify the main corporal sequences in students oral presentations during a given course. Data from students presentations was collected through the use of Microsoft Kinect and blind software, the total number of observations was 65. The 7 collected features were used as input information in the SPMF tool, allowing the identification of main sequences of presenters. Sequences with the Hands Down attribute were the most frequent in all presentations. It has also been found that the presentations 1 and 3 are more similar in terms of sequence than with the second. The evaluation of the sequences can be integrated into the tool so that the teacher can return feedback to the students about their postures.