Abstract:

More and more universities use educational digital platforms to support teaching. Due to the covid-19 crisis, and with the online teaching approval, the usage of digital platforms in universities has gone from being an option to a necessity. Therefore, efforts have been made to promote the use of existing platforms in each university. This has required teachers not only to make an effort to transform and adapt in record time all the presential teaching to virtual teaching, but also has required professors to learn how to use some of the features of existing digital platforms that were not familiar to them. However, did using this type of platforms positively impact on high education students marks? This study aims to determine if such impact existed in engineering schools. More concretely, this paper focus on engineering students from different grades and levels from the Universitat Politècnica de València in Spain, and on the use of the PoliformaT digital platform, which is an adaptation of Sakai platform for the mentioned university. Statistics data provided by PoliformaT about the number of visits, time spent on the platform, and downloaded documents per student for several subjects from the School of Industrial Engineering, the School of Informatics and the School of Design Engineering for the course 2019-2020 are analysed. A correlation analysis of marks obtained by students and their activity on PoliformaT platform is developed to determine if the usage of digital platforms has influenced the students’ marks. A varied casuistry is observed in the results. The correlation with marks is identified in some of the analysed subjects. In this sense, some unconsidered factors could be influencing this correlation, being appropriate to analyse them in future research. On the other hand, it is necessary to re-analyse this same scenario in future courses when both, students and professors, already have a sufficient level of learning of the employed teaching tools. Next course we expect that some of the deficiencies identified in this first study will be reduced after an adaptation time in which both actors become familiar to these digital tools.

Keywords:

Digital tools, statistic analysis, higher education, virtual teaching.