Psychometric properties of information and communication technology competencies scale: Latent profile analysis

Abstract

Rapid expansion of information and communication technologies (ICT) underscores importance of ICT competency for success in modern society. In education, ICT facilitates knowledge acquisition, innovative teaching methods, and development of digital literacy skills. By measuring ICT competencies, teacher training programs can better equip educators for technology integration, leading to more effective teaching and learning processes. It is crucial for educational policies to emphasize integration of ICT and ensure teachers are prepared to utilize it effectively. The study aims to determine psychometric properties of “information and communication technology competency scale (ICTCS)” for pre-service teachers (PSTs) in the Russian setting and identify distinct proficiency levels among them. This study employed a mixed-methods approach to adapt a scale measuring PSTs’ ICT competencies. The research involved two different samples for exploratory factor analysis (EFA) (n=160) and confirmatory factor analysis (CFA) (n=326). To establish language validity, a translation, and cross-cultural adaptation process was followed. Data analysis included EFA, CFA, reliability estimation, and latent profile analysis, with satisfactory results obtained for scale’s psychometric properties. The study concludes that ICTCS, with two factors (ICTC-PU and ICTC-ID), is a valid and reliable measure of teachers’ attitudes and skills regarding ICT use. Four-class latent profile model reveals distinct competence levels, informing targeted professional development programs. Educational institutions and policymakers should prioritize these programs and use the scale for teacher evaluations. Future research should explore the efficacy of these programs, expand the sample size, incorporate objective measures, and employ longitudinal designs to better understand the impact on student outcomes.