Abstract:

This paper is a further step in the promotion of teaching activities based on the application of theoretical and practical data analysis and modelling to consolidate mathematical-statistical concepts in non-mathematical-statistical contexts, particularly, in the branch of Agricultural Engineering. As stated in previous studies, there are still important gaps in the curricular contents of Agricultural Engineering resulting in an unsuitable coverage of crucial professional competencies, particularly in the application of mathematical software for solving specific engineering problems.

However, in spite of focussing on proposing specific new teaching activities, this paper intends to assess how students perceived such activities, basically in terms of interest, difficulty and usefulness. Hence, in a previous paper different activities were proposed on the application of robust mathematical software for solving specific engineering problems with the help of data analysis and modelling, and the students’ perception of such activities is evaluated here.

The presented activities were carried out in two subjects corresponding, respectively, to the Degree in Agricultural Engineering and to the Master in Agricultural Engineering at the University of the Balearic Islands during the academic years 2016-2017. The professors assessed the performed educational actions not only based on their own personal impressions, but also evaluating the marks of the students in comparison to previous years, as well as evaluating the perception of the students at the end of the activities through surveys.

In general, among others, students acknowledged that these activities contribute and are useful to improve their analytical skills, which they consider important for an engineer. They also agreed on the potential of such activities for generalizing their applicability for other subjects. Further, despite the complexity of the methods, they felt able to perform the proposed activities. They also felt that the performed activities would contribute to face future activities more systematically. Finally, the preferred such activities/evaluation instead of the traditional methodology based on theoretical sessions and final exam.

Keywords:

Student perception, Agricultural Engineering, modelling, data analysis, numerical computing tools.