CATEGORICAL DATA MODELLING IN A VIRTUAL ENVIRONMENT: SELF-LEARNING VIDEO/TUTORIAL FOR PRACTICES WITH R SOFTWARE

In virtual education, the protagonist of the teaching/learning process is not the instructor, but is the student who takes responsibility for his own learning through a proactive and participatory attitude under the guidance of the teacher-tutor. To be successful students need to be highly motivated and be able to learn on their own without much direction. This is achieved by replacing the face to face classroom activities with materials suited to the objectives and skills that students must reach in connection with the course. On the other hand, one of the main objectives of the European Credit Transfer System (ECTS) is to make emphasis in the students' personal work. Because of this, the use of new technologies of information and communication (NTIC) for distance education is essential.

In this paper, the experience with students of the virtual Master in Applied Statistic of the University of Granada is presented. Specifically, the categorical data modelling is treated. The main problems in virtual teaching/learning arise in computer practices by using statistical software. Students and teacher are not together in the classical computer room. In order to solve the computer practices, students must follow some teacher’s notes. And this is the great problem for students. Computational problems arise and they need a powerful tool to help them.

R is a powerful free software that allows to implement any mathematical function or algorithm. For these reasons it is used for public universities. In order to prevent the students' problems in categorical data modelling with R, a complete video/tutorial was developed using new technologies based on screen recording.