16 SES 16 B, ICT and Learning Achievements / Assessment
The paper is one of the many outputs of research project called “Digital Technologies in students’ everyday lives and learning” (supported by the Czech Science Foundation; grant no. 17-06152S), focusing on digital technologies and their role in everyday lives and learning of 15-year-old Czech students, across a variety of contexts and environments (see also Arnseth, Erstad, Juhaňák, & Zounek, 2016).
Like in other economically advanced countries, in the Czech Republic information and communication technologies (ICT) have become an inseparable part of social life, while becoming an important element in education. Since the beginning of the 21st century, a number of initiatives and projects have been undertaken to support implementation of ICT into formal education (for more details see Eurydice, 2011; Zounek & Šeďová, 2009; Zounek, 2006).
Researching or evaluating these initiatives systematically however has not received enough attention in the Czech Republic yet. It was only in the strategic document Strategy in Digital education until 2020 (Strategie, 2014) that an explicit request for collecting data on ICT implementation and use in formal education as well as a need for educational research in this area have been voiced. This is why data on ICT in Czech schools has been scarce in the Czech Republic. One of the few sources research can currently draw on to get an insight into these issues is data from international surveys (International Large-Scale Assessments – ILSA) undertaken in the Czech Republic. For ICT, this is mainly the PISA survey (which includes the ICT Familiarity Questionnaire) and ICILS 2013 survey, focusing on students' computer and information literacy (Fraillon, Schulz, & Ainley, 2013). Despite this, not even data from these international surveys have been analysed sufficiently in the Czech Republic (Potužníková, Lokajíčková & Janík, 2014; Straková, 2009).
The goal of this paper therefore is to use the data from ILSAs undertaken in the CR to map the role of ICT in Czech schools. We are primarily interested in finding out how ICT availability and use are reflected in students’ educational performance and what other aspects relating to ICT use by students may influence their educational results (such as ICT availability and use beyond school, interest in ICT, ICT self-efficacy etc.). The paper will specifically focus on analysing data from the most recent PISA 2015 survey (i.e. primarily data from the familiarity questionnaire for students).
The paper also seeks to contribute to the ongoing debate on the influence of ICT on students’ learning and school success. Research results in this area are rather mixed or unequivocal at the best. Some researchers observe a positive influence of ICT on students’ learning outcomes while others find the effect of ICT insignificant; there are even studies reporting a negative influence of ICT on student learning (comp. e.g. Biagi & Loi, 2013; Spiezia, 2010; Rohatgi, Scherer & Hatlevik, 2016; Zhong, 2011). The contradictory results may certainly be partly attributed to the complexity of ICT as a factor and its connection to students’ learning outcomes or to application of diverse research methodologies. Much haziness regarding the influence of ICT in the process of learning (and education in general) however persists.
Our research bases data analysis on multilevel modelling (referred to also as ‘multilevel regression models’ in some publications), which, thanks to its wide applicability, has been paid more and more attention in recent years not only in educational sciences but also in other fields such as sociology, psychology and others (see Hox, 2010; Snijders & Bosker, 2012; Heck & Thomas, 2015). The analysis itself is based on a general multilevel modelling strategy proposed by Heck and Thomas (2015), consisting in the following five steps: 1) Partitioning the variance in an outcome, 2) Adding level-1 predictors to explain intercept variability, 3) Specifying level-2 predictors to explain intercept variability, 4) Examining possible variations in slopes, 5) Adding level-2 predictors to explain variation in slopes. The reason behind this choice is especially the nature of data from PISA 2015 survey, especially its hierarchic nature; we are working with data assigned to individual students studying in different schools. This choice allows us not only to reflect the hierarchical structure of the analysed data but also consider potential differences in the links studied within different schools as well as the fact that some influences may operate at the level of individual students while others may operate at the school level.
The first analyses suggest that as far as learning outcomes of Czech students are concerned, ICT availability does not seem to play a major role at present any more. This concerns both ICT availability at school and ICT availability in students’ home environment. The declared students’ interest in ICT and the perceived students’ competence in ICT use seem, rather surprisingly, insignificant. It is not true therefore that students with more interest in ICT or students who feel more competent in terms of their ICT skills, attain better or worse learning outcomes than others. The use of ICT as such, on the other hand, proves essential. This involves the use of ICT in schools as well as ICT use in leisure time, where students’ gender proves to be an important factor. The results of the analyses help to understand the role of ICT in Czech schools more deeply and to map the connections between ICT availability and use on the one hand and learning outcomes on the other. The results of the analyses allow us to identify which ICT-related factors play an important role in education and which factors should be paid more attention not only in educational research but also at the international and national levels of educational policies and/or in efforts to improve quality of ICT-supported education in general. We believe that the results of our analyses may bring knowledge essential to this area and provide feedback for educational policies in CR. Last but not least, the results of our analyses may be used in comparisons with similar research in other countries, contributing thus to a better understanding of ICT use in education at a global level.
Arnseth, H., Erstad, O., Juhaňák, L., & Zounek, J. (2016). Pedagogika a nové výzvy výzkumu ICT: role digitálních technologií v každodenním životě a učení mládeže. [Educational sciences and new challenges of ICT research: the role of digital technologies in young people’s everyday lives and learning.] Studia Paedagogica, 21(1), 87–110. Biagi, F., & Loi, M. (2013). Measuring ICT Use and Learning Outcomes: evidence from recent econometric studies. European Journal of Education, 48(1), 28–42. Eurydice (2011). Key Data on Learning and Innovation through ICT at School in Europe 2011. Available at: http://eacea.ec.europa.eu/education/eurydice. Fraillon, J., Schulz, W. & Ainley, J. (2013). International Computer and Information Literacy Study: Assessment Framework. IEA/ACER. Available at: http://www.iea.nl/fileadmin/user_upload/Publications/Electronic_versions/ICILS_2013_Framework.pdf Heck, R. H., & Thomas, S. L. (2015). An Introduction to Multilevel Modeling Techniques: MLM and SEM Approaches Using Mplus. New York, NY: Taylor & Francis. Hox, J. J. (2010). Multilevel Analysis: Techniques and Applications. New York, NY: Routledge. Potužníková, E. Lokajíčková, V., & Janík, T. (2014). Mezinárodní srovnávací výzkumy školního vzdělávání v České republice: zjištění a výzvy. [International comparative research in formal education in the Czech Republic: findings and challenges.] Pedagogická orientace, 24(2), 185–221. Rohatgi, A, Scherer, R., Hatlevik, O. E. (2016). The role of ICT self-efficacy for students' ICT use and their achievement in a computer and information literacy test. Computers & Education, 102, 103–116. Snijders, T. A. B., & Bosker, R. J. (2012). Multilevel Analysis: An Introduction to Basic and Advanced Multilevel Modeling. Thousand Oaks, CA: Sage Publications. Spiezia,V. (2010) Does computer use increase educational achievements? Student level Evidence from PISA. OECD Journal: Economic Studies, Volume 2010. Straková, J. (2009). Vzdělávací politika a mezinárodní výzkumy výsledků vzdělávání v ČR. [Educational policies and international surveys of educational outcomes in CR.] Orbis Scholae, 3(3), 103–118. Strategie digitálního vzdělávání do roku 2020. [Strategy of Digital Education until 2020]. Praha: MŠMT. Zhong, Z.-J. (2011) From access to usage: The divide of self-reported digital skills among adolescents. Computers & Education, 56, 736–746. Zounek, J. (2006). ICT v životě základních škol. [ICT in the lives of schools.] Praha: Triton. Zounek, J., & Šeďová, K. (2009). Učitelé a technologie: mezi tradičním a moderním pojetím. [Teachers and technologies: between the traditional and the modern approach.] Brno: Paido.
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