Zaragoza, España
As individuals comprising working groups possess their own personalities and abilities, each of them will show a particular behavior when interacting in an active learning process. Heterogeneous teams of three or four students, where strong and weak students could work together and weak students could be tutored by strong students, would avoid the creation of unbalanced teams. This paper proposes a methodology for optimizing working groups characteristics extracting information from data collected in MCQ (Multiple Choice Questionnaires) using a soft hybrid inductive approach combining traditional classroom with Flipped Classroom, Gamification and Peer Instruction. On the one hand, a gamification approach will allow the professor to boost the previous study of the subject and those students with good knowledge of the right answers will try to convince those partners which are not sure about theirs in a second round of answers. Extra marks will be gained by those students who correct their partners. On the other hand the results obtained from these tests could supply key information with respect to the students’ behavior and psychology. This would help the teacher to distribute the students in the creation of effective formal working teams in future learning activities. For instance, this method could optimize the working groups’ global performance in a subject where students will be assessed in a group activity such as a cooperative or coordinated project with several partners. A quantitative tool for the creation of optimized student teams for activities programmed at the second term of the subject is described.
© 2001-2024 Fundación Dialnet · Todos los derechos reservados