Academic performance of first-year university students: modelling the role of reading competence

ABSTRACT

Implementation of the European Higher Education Area changed the assessment model in higher education towards a competence-based system, so that students are assessed by what they demonstrate they can do (competences). However, assessment of certain key competences, such as reading, ceases at higher education. The question remains whether reading competence continues to influence academic achievement at this level. We designed a reading comprehension test based on PISA questions and administered it to new-intake university students. The results were linked to students’ grades in each first-year subject and their sociodemographic administrative data. The influence of reading competence and socioeconomic status on grades in all first-year subjects was analysed through structural equation models. The results show that reading competence at the start of university education has a direct influence on grades in all first-year subjects and an indirect influence through the admission grade. In conclusion, reading competence needs to be further developed and promoted even in the university context.

KEYWORDS:

• academic achievement
• assessment
• higher education
• reading competence
• socioeconomic status
• structural equation

Acknowledgements

The authors are grateful to University of Las Palmas de Gran Canaria for providing the administrative data used in this paper, and to the lecturers and students of the first-year subjects of its Business and Management Bachelor Degree for their altruistic collaboration in this study.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Complying with European regulations, the participants were informed by the professors of the subjects themselves that the questionnaire was part of an educational innovation project of the ULPGC. The format in which the data are processed and delivered includes encryption techniques that allow only aggregates and anonymous forms of statistical analysis.

Additional information

Funding

This work was supported by ULPGC Vice-Rectorate for Qualifications and Lifelong Learning [grant number PIE2019-14] and by the Ministerio de Ciencia e Innovación, Kingdom of Spain [Research Project PID2020-119471RB-I00].