Abstract:

Digital competences, either transversal or specific, are in high demand within the biomedical sciences field. By acquiring such skills, the students get more prepared for the new labour market. Thus, there is a growing need of including digital competences in the academic curricula during undergraduate and postgraduate studies. Recently, and due to the home confinement forced by the COVID crisis, virtual teaching environments have been promoted. This new scenario facilitates the development of learning approaches that promote the digital skills.

In the context of life and biomedical sciences (such as biology, biochemistry, biotechnology, medicine and related areas), software designed for the study of data images obtained from histological/histopathological samples have become crucial and valuable tools. However, it has been observed that students do not receive sufficient training to cope with these specific tasks. Moreover, there is rarely any coordination between different subjects concerning this topic. Consequently, students suffer from a shortage of specialized knowledge (and know-how) about the most suitable software for their professional profile, being unfamiliar with these procedures. For this reason, we have included the use of of virtual microscopy together with freeware software for image analysis, and EXCEL for the ulterior data processing and graphing, in our histology classes.

Our objective was to assess the students’ self-perception concerning their improvement in transversal and specific digital skills through self-evaluation using a test design, taking into account the effect of the confinement conditions as well. Moreover, we propose a methodology based on a classification in different levels that would certify the extent of acquisition of specific digital competences. Such levels would be equivalent to the “common European framework for language competences”. Basically, the qualification would be based on three levels: A: imitation, B: independence and C: creation, that in turn would be subdivided into: A1: introduction, A2: beginner, B1: intermediate, B2: advanced, C1: expert and C2: professional. Once the student has satisfactorily succeeded specific courses will be granted with a digital badge, indicating the acquired level in each specific digital competence. For example, the course “Organology’’ (human microscopy anatomy), in the second semester of the 2nd year of Biochemistry, would grant an A1 level in Image J software, and database treatment of the generated data would grant a A2 level in Excel.

Keywords:

Digital skills badge, vertical and horizontal coordination, image analysis, virtual microscopy.