Session Information
09 ONLINE 24 A, Exploring Formative Assessment
Paper Session
MeetingID: 871 4732 0830 Code: P6zwxq
Contribution
The continuous progress of digital technologies and their integration into all areas of life raise new challenges for educational systems worldwide since the education of students regarding information and communication technology (ICT) skills is a prerequisite for their participation in the modern information and knowledge society (cf. Fraillon et al., 2020). In Europe this global topic is addressed for example in the "Digital Education Action Plan" (European Commission, 2020). This action plan represents an orientation at European level for the development of schools and school systems against the background of digitalisation, not only in times of the Corona pandemic. A first key goal of the action plan is to foster “the development of a high performing digital education ecosystem” (ibid., p. 10), in which inequalities are reduced at the same time. A second key goal is to enhance “digital skills and competences for the digital transformation” (ibid., p. 12), particularly to improve participation in democratic life. In order to achieve these goals, the introduction of ICT into the classroom should be seen as an enhancement of the quality of a school, which manifests itself in the competences of its students, and not only as compliance with current trends. In this context school teachers play the important roles of mediators of such skills as well as the role of implementors of innovative ICT solutions (cf. Drossel, Eickelmann, Schaumburg & Labusch, 2019; Erstad, Eickelmann & Eichhorn, 2015).
A key condition of the regular ICT use in classroom teaching and learning processes are the attitudes of teachers regarding their benefits for the development of student competences (cf. Drossel, Eickelmann & Gerick, 2017; Eickelmann & Vennemann, 2017; Fraillon et al., 2019). These attitudes constitute psychologically-rooted traits that can be assessed through self-perception. In a school context, they are viewed as an integral part of the professional teaching competences which should be considered in combination with knowledge, motivation and self-regulation. Fives and Buehl (2012) identify stability and resistance to change as a characteristic of such attitudes. In models of school development and school quality, teacher’s attitudes are located on the input level (cf. Fraillon et al., 2019). Consequently, the attitudes have a direct influence on factors at the process level, which are connected to student performance.
An international comparison of teachers’ attitudes towards ICT reveals a strong variation between different education systems (cf. Fraillon et al., 2020). While for example teachers in Denmark and Portugal are particularly open to the use of ICT, teachers in Germany are on average comparatively sceptical about the benefits of ICT use for teaching and learning (ibid.). For example, only 35 percent of teachers in Germany and 28 percent in France agree that the use of ICT improves the academic performance of secondary school students (ibid.). In contrast, about three-quarter percent of teachers in other countries like Denmark and Portugal agree with this statement (ibid.).
With just a few exceptions (cf. Eickelmann & Vennemann, 2017), findings only allow conclusions for the attitudes of the entire teacher population of a country. This contribution seeks to investigate whether a typology of teacher attitudes regarding the use of ICT can be identified in European secondary schools (research question 1) and it investigates how the individual types are distributed in the countries (research questions 2).
Method
To answer the research questions, secondary analyses of the IEA ICILS 2018 (International Computer and Information Literacy Study; cf. Fraillon et al., 2020, 2019) are conducted. The data base consists of representative teacher data from secondary school teachers in the seven European education systems which participated in ICILS 2018 (Denmark, Germany, Finland, French, Italy, Luxembourg and Portugal) (ibid.). N=11.655 teachers are included in the analysis. To answer the first research question, Latent Class Analysis (LCA) (Hagenaars & McCutcheon, 2009) are used to identify the teacher typology (Mplus; Muthén & Muthén, 2010). Missing values are handled by using the Full-Information-Maximum-Likelihood approach (FIML, Grund et al., 2017; Muthén & Muthén, 2010). The data stratification (teachers in schools) is included by using the Type=mixture complex’ analysis type (Muthén & Satorra, 1995). Prior to the actual calculations, a so-called Senate Weight is calculated, to ensure that despite their different sample sizes each individual education system contributes to the total sample to an equal extent. To answer the second research question, descriptive statistics are calculated using the IDB Analyzer (Rutkowski, Gonzalez, Joncas & von Davier, 2010). In doing so, the weight variable for teachers (cf. Jung & Carstens, 2015) is included in order to balance the sample bias and obtain valid estimations with regard to the population studied.
Expected Outcomes
The results of the LCA concerning the first research question allow the identification of five teacher types, namely critical ICT-enthusiasts (42.5%), ICT-enthusiasts (37.75%), ICT-sceptics (12.19%), differentiated ICT-sceptics (6.46%) and ICT-sceptics with positive notions (1.1%). Accordingly, not all teachers see the use of ICT as beneficial for instruction purposes, neither regarding working with students nor improving student performance. Furthermore, a significant portion sees ICT as a potential threat, e.g. to the development of writing competences. The distribution of teacher attitudes types varies across the selected European education systems (research question 2). While teachers in Luxembourg, for instance, can be categorised primarily as critical ICT-enthusiasts, ICT-enthusiasts dominated in Denmark. In Germany, critical ICT-enthusiasts and ICT-enthusiasts are the most common types.
References
Drossel, K., Eickelmann, B., Schaumburg, H. & Labusch, A. (2019). Nutzung digitaler Medien und Prädiktoren aus der Perspektive der Lehrerinnen und Lehrer im internationalen Vergleich. In B. Eickelmann, W. Bos, J. Gerick et al. (Eds.), ICILS 2018 #Deutschland. Computer- und informationsbezogene Kompetenzen von Schülerinnen und Schülern im zweiten internationalen Vergleich und Kompetenzen im Bereich Computational Thinking (p. 205-240). Münster, Waxmann. Drossel, K., Eickelmann, B. & Gerick, J. (2017). Predictors of teachers‘ use of ICT in school – the relevance of school characteristics, teachers‘ attitudes and teacher collaboration. Education and Information Technologies, 22, 551–573. Eickelmann, B. & Vennemann, M. (2017). Teachers‘ attitudes and beliefs regarding ICT in teaching and learning in European countries. European Educational Research Journal, 16(6), 733–761. Erstad, O., Eickelmann, B. & Eichhorn, K. (2015). Preparing teachers for schooling in the digital age: A meta-perspective on existing strategies and future challenges. Education and Information Technologies, 20(4), 641–654. European Commission (2020). Digital Education Action Plan 2021-2027. Resetting education and training for the digital age. Retrieved from: https://ec.europa.eu/education/sites/default/files/document-library-docs/deap-communication-sept2020_en.pdf Fives, H., Buehl, M. M. (2008). What do teachers believe? Developing a framework for examining beliefs about teachers’ knowledge and ability. Contemporary Educational Psychology, 33, 134–176 Fraillon, J. et al. (2020). Preparing for Life in a Digital World. IEA International Computer and Information Literacy Study 2018 International Report. Amsterdam: IEA. Fraillon, J. et al. (2019). IEA International Computer and Information Literacy Study 2018. Assessment Framework. Springer. Grund, S., Lüdtke, O., & Robitzsch, A. (2017). Missing Data in Multilevel Research. In S. E. Humphrey, & J. M. LeBreton (Eds.), Handbook for multilevel theory, measurement, and analysis American Psychological Association. Hagenaars, J.A. & McCutcheon, A.L. (2009). Applied latent class analysis. Cambridge: University Press. Jung, M. & Carstens, R. (2015). ICILS 2013 User Guide for the International Database. IEA: Amsterdam. Muthén, L. K. & Muthén, B. O. (2010). Mplus User’s Guide. Fourth Edition. Los Angeles, CA: Muthén & Muthén. Muthén, B. O. & Satorra, A. (1995). Complex Sample Data in Structural Equation Modeling. Sociological Methodology, 25, 267–316. Rutkowski, L., Gonzalez, E., Joncas, M. & von Davier, M. (2010). International large-scale assessment data: Issues in secondary analysis and reporting. Educational Researcher 39(2), 142–151.
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