Abstract:

Although digital technologies have the potential to improve learning, many schools still face hurdles and challenges in using and integrating them in the school environment. Therefore, the SELFIE self-reflection tool has been developed by the European Commission in conjunction with an international panel of experts to help schools to know where they stand in the area of digital technologies. In early October 2017, 650 general and vocational schools (ISCED 1-3) in 14 European countries took already part in the pilot implementation of SELFIE’s beta version. In total, SELFIE was used by 67714 users (2979 school leaders, 11773 teachers and 52962 students).

The aim of this paper is twofold: first, we check whether the data obtained from SELFIE are reliable, consistent and valid. This is important to assess whether the questionnaire has been constructed correctly and the results from it can be meaningfully used by schools. Second, based on the results of the quality check of the data, we proceed to analyse the data more in detail, constructing a range of descriptive statistics.

Thus, in a first step, we employ various statistical methods to verify the quality of the database. In particular, we check whether SELFIE is an adequate tool to measure the digital capacity of schools, whether SELFIE items are able to distinguish between schools with different digitalisation levels, and whether SELFIE items are grouped in the correct areas. To this end, we use Item-Score correlation, Cronbach’s Alpha, Generalized Partial Credit Item Response Model (GPCIRM) and Confirmatory Factor Analysis (CFA). In a second step, we perform a range of quantitative analyses of SELFIE data that indicate the users’ perspective on the use of digital technologies for teaching and learning and identify common patterns in the data. The focus of this analysis is on showing the responses for each SELFIE area (e.g., teaching and learning practices) and comparing user groups. In addition to providing results on the aggregated level, we also further differentiate schools among ISCED levels and school funding type (public and private schools). In this way, we compare the responses of a respondent group in different school types, for example whether the responses of students differ importantly between ISCED 1 and ISCED 2 schools.

Caution in the interpretation of all results needs to be taken, as SELFIE is not a representative sample because schools self-selected themselves to participate in SELFIE’s pilot phase. Bearing this in mind, the results of our analyses show that SELFIE is a valid and reliable self-reflection tool that captures well the digital capacity of schools. Our subsequent analyses indicate that there are often significant differences not only among the various user groups but also among ISCED levels and private and public schools. These findings emphasise the differences that exist among user groups and the relevance of consulting each of them. They allow a better understanding of the use and availability of digital technologies in schools in Europe.

Keywords:

Selfie, self-reflection, quantitative analysis, digital technologies, education.