How to clutch skills from higher education curricula: analysis of Portuguese learning outcomes

Abstract

In Portugal, the Agency for Assessment and Accreditation of Higher Education - A3ES - promotes and ensures the quality of higher education, following the development of quality management systems in the European space. Thus, their mission is to contribute to improving the quality of Portuguese higher education, through the assessment and accreditation of higher education institutions and their study programmes, and to ensure the integration of Portugal in the European quality assurance system of higher education. This agency performs the assessment and accreditation of higher education study programmes in 1st, 2nd and 3rd cycles.

At an initial stage of the accreditation process, HEI submit an accreditation proposal to A3ES. In the description of each study programme for evaluation, HEI must describe what are the “intended learning outcomes” they expected students will achieve at the end of a specific period of learning. Data analysis focused on information included in this question, and which is limited to 1000 characters. All proposal of study programs submitted to accreditation in A3ES, from 2009 to 2014, were examined (n = 2961). A content analysis was carried out using the MAXQDA software for qualitative data analysis (version 12). Adopting a theoretical thematic analysis approach, instead of a data-driven option (Braun & Clarke, 2006), a competence matrix of technical and generic skills were identified. Based on these qualitative results, a set of 30 learning competencies cited in all the Portuguese study cycle curricula official documentation was analysed. The relative importance of a given competency, in each curriculum, was roughly estimated by counting the number of corresponding mentions in the document submitted to A3ES for approval. A Principal Component Analysis, with varimax rotation, allowed the association of the 30 competencies with nine components. Each new component was, then, characterized based on the initial variables’ loadings. The nine components could also be associated with several distinct features of the higher education study programmes (study cycle and scientific area) and institutes (namely geographical location, university/polytechnic subsystem, and private/public sector). This study aims to contribute to the identification of areas for improvement of study programmes in Portugal.