Supporting the monitoring of the digital capacity of schools through optimal shortening of the SELFIE tool

Abstract

Data-based decision-making could be vital to improving learning and teaching. Digital education has led to an upsurge in the amount of data that researchers and key stakeholders can utilise to enhance learning. In this article, we present an optimal shortening of the European Commission's SELFIE tool, an instrument used to measure the digital capacity of schools. SELFIE is an established and scientifically validated tool that has been used by over 5.5 million users (September 2023) in 80 different countries. In this paper, we propose two shorter measurement instruments based on the original SELFIE tool that could be used when the original scale needs to be shortened due to time and organisational limitations, without considerable loss in predictive power in relation to the digital capacity measurement construct: (1) a midi-SELFIE consisting of 16 items and (2) a mini-SELFIE consisting of 8 items. Using existing data, we shorten the instruments through psychometric analysis using Item Response Theory models. We use three cases to show the uses of the shortened versions and explore their validity compared to the complete instrument. For the first case, we offer a longitudinal analysis of the digital capacity dynamic for selected schools. In the second case, we look at regional differences in Portugal's digital capacities based on an almost full sample of the country. Finally, in the third case, we use a representative sample from Spain to investigate the relationship between digital capacity and time dedicated by teachers to use digital technology during lessons. The three instruments (full, midi and mini) provide similar results, suggesting that the shortened versions of SELFIE would be a reliable alternative to the complete tool for specific purposes, such as monitoring the development of the digital capacity of the school and policy monitoring.