Abstract:

In Spanish universities, the profile of master degree students in the areas of Computer Science and Telecommunications is not homogeneous in terms of skills, competences, and acquired knowledge (Ferrer, 2006; Samuel, 2010). There are multiple bachelor degrees that give access to these master degrees, and while it is required by law that the core competences of the master degree must be covered by all of these bachelor degrees, in reality these core competences are fulfilled to a different extent due to the differences in the design of the bachelor courses syllabi.

Moreover, we also have to consider that several master degrees provide a more specialized teaching in various advanced subjects, such as machine learning, cellular networks, and cybersecurity. Many subjects taught in these master degrees are multidisciplinary in nature, encompassing multiple areas of knowledge, and also provide training on extremely novel technologies. As such, these subjects require students to have certain background on other competences and skills that might be considered non-essential. However, these competences and skills are also fulfilled by the bachelor degrees to a different extent, or even not fulfilled at all - as these competences are taught in elective subjects.

This situation causes various issues when teaching master degree subjects, specially in multidisciplinary subjects: due to the inequalities between the competences of the students, part of the course must be devoted to homogenize such competences. As a result, students’ morale get affected in several ways - from losing interest and motivation to stressing over the learning process of the previously unknown competences, plus also it might not be possible to fulfill the competences and skills associated with these multidisciplinary courses in a satisfactory way. It is then necessary to establish various strategies that facilitate a seamless acquisition of such competences and skills without impacting the scope of these courses.

Therefore, this paper aims to explore the current tools and methodologies that could be used in order to reduce student inequality in master degrees due from the heterogeneity in the knowledge and skills of students from various undergraduate degrees. As such, we will analyse various short term solutions that do not require the coordination between the master and bachelor degrees, including the creation of optional training itineraries that are tailored to the specific needs of every student. We will also explore several medium term solutions, the goal of which is to facilitate vertical coordination between interdependent bachelor degree and master subjects (Sirounian, 1995). These solutions include the use of mechanisms that automatically analyze the relationships between existing subjects, plus the adaptation of vertical coordination methodologies focusing on a reduced number of interrelated subjects.

References:
[1] Ferrer, F., Ferrer, G. & Castel Baldellou, J.L. Equity and segregation in the Spanish education system. Prospects 36, 547–571 (2006).
[2] Samuel B. Fee & Amanda M. Holland-Minkley (2010) Teaching computer science through problems, not solutions, Computer Science Education, 20:2, 129-144.
[3] Sirounian, L., & Grosky, W. I. (1995). A knowledge model for unifying deductive and non-deductive heterogeneous databases. IEEE transactions on knowledge and data engineering, 7(1), 82-105.

Keywords:

Curricula, Inequalities, Bachelor, Master, Computer Science, Telecommunications.