International comparative school performance studies, such as the IEA-Study ICILS (Fraillon & Rožman, 2023), offer insights into educational practices across Europe and the world. The methodological design of the ICILS-Study enables sub-samples to be formed, allowing for the examination of specific groups and the generation of knowledge that could be used to improve school systems. This methodological possibility is used in this contribution to identify classes of digital applications usage by foreign language teachers and related determinants. Previous non-subject-specific studies like Graves and Bowers (2018) were able to identify four media patterns (evaders, assessors, presenters, dexterous). Additionally, factors influencing ICT use, such as teachers' self-efficacy are well studied across subjects (Gerick, Eickelmann & Bos, 2017). However, specific digital application usage classes and their determinants in foreign language teaching remain unexplored, despite possible subject-subcultural influences. This contribution aims to answer two research questions: 1. To what extent can different digital application usage classes be identified for foreign language teachers compared to non-foreign language teachers in Germany? 2. To what extent is there a connection between identified digital application usage classes and determinants of ICT use for both groups? The study employs ICILS 2018 teacher data from Germany (n=2328; Eickelmann et al., 2019), taking into account data weighting (Tieck & Meinck, 2020). To answer the first RQ, a latent class analysis is conducted using MPlus8. The class solution is based on statistical information criteria (e.g. smallest BIC; Eshima, 2022). The analysis identifies three usage classes for foreign language (a) and non-foreign language (b) teacher groups: avoiders (a: 80.4%; b: 78.1%), selective users (a: 17.4%; b: 19.7%), and multiple users (a: 2.2%; b: 2.2%) of digital applications. For the second RQ, a hierarchical regression analysis was conducted using the IDB Analyzer to explore the connections between usage classes and determinants. The analysis, grounded in theoretical considerations, employs five regression models. Results highlight significant correlations, including foreign language teachers' affiliation with multiple users being linked to positive attitudes towards ICT (Model V; ß=.27, adjusted R²=.15). Correlations vary across usage classes and teacher groups. The findings contribute to the understanding of the integration of digital applications in language teaching. This provides valuable insights for researchers and policymakers, particularly in Europe. Potential explanations, such as subject-subcultural influence on digital application usage, related determinants and alternative methodological approaches are discussed.

Eickelmann, B., Bos, W., Gerick, J., Goldhammer, F., Schaumburg, H., Schwippert, K. et al. (Hrsg.). (2019). ICILS 2018 #Deutschland. Computer- und informationsbezogene Kompetenzen von Schülerinnen und Schülern im zweiten internationalen Vergleich und Kompetenzen im Bereich Computational Thinking. Münster: Waxmann. Eshima, N. (2022). An Introduction to Latent Class Analysis. Singapore: Springer Singapore. https://doi.org/10.1007/978-981-19-0972-6 Fraillon, J. & Rožman, M. (2023). International Computer and Information Literacy Study 2023. Assessment Framework. Amsterdam: International Association for the Evaluation of Educational Achievement (IEA). https://www.iea.nl/sites/default/files/2023-12/20231221%20ICILS2023_Assessment_Framework__Final_0.pdf Gerick, J., Eickelmann, B. & Bos, W. (2017). School-level predictors for the use of ICT in schools and students’ CIL in international comparison. Large-scale Assessments in Education, 5(1), 1–13. DOI: 10.1186/s40536-017-0037-7 Graves, K. E. & Bowers, A. J. (2018). Toward a Typology of Technology-Using Teachers in the ”New Digital Divide”: A Latent Class Analysis of the NCES Fast Response Survey System Teachers’ Use of Educational Technology in U.S. Public Schools, 2009 (FRSS 95). Teachers College Record, (8), 1-42. http://www.tcrecord.org/Content.asp?contentid=22277 Tieck, S. & Meinck, S. (2020). Weights and variance estimation for ICILS 2018. In Mikheeva, E., Meyer, S. (Eds.). IEA International Computer and Information Literacy Study 2018 - User Guide for the International Database. Amsterdam: International Association for Educational Achievement (IEA).