Preparing Students for Life in a Digital Age - An International Analysis of School Factors Based on IEA-ICILS 2013

Author(s):

Ramona Lorenz(submitting)Birgit Eickelmann(presenting)Julia Gerick

Conference:

ECER 2015

Network:

WERA Focal Meeting

Format:

Paper

Session Information

WERA SES 09 E, Integration of Technology and Education: International Perspectives on Pros and Cons

Paper Session

Time:

2015-09-10

11:00-12:30

Room:

334. [Main]

Chair:

Janna De Gouveia

Contribution

The increasing relevance of both information and knowledge transformation and exchange through ICT emphasizes that digital literacy such as computer and information literacy (CIL) can be considered one of the core competencies in the 21^st century (Fraillon, Schulz, & Ainley, 2013; Voogt, Erstad, Dede & Mishra, 2013). However, the promotion of students’ digital literacies through computer-assisted teaching and learning in schools still presents an ambitious task (Eickelmann, 2011; Voogt et al., 2013). By means of in-depth analyses of the IEA-study ICILS 2013 (International Computer and Information Literacy Study, 2010-2014), which has been conducted by the IEA (Fraillon et al., 2013) and investigates the computer and information literacy of secondary school students (Grade 8) in 21 educational systems around the world and, for the first time, applies international comparisons and computer-based test environments, this contribution investigates relevant factors on the school level which support or hinder the students in their acquisition of CIL.

The theoretical framework of the study contexts for CIL learning and learning outcomes distinguishes between individual student factors, the home environment, schools and classrooms as well as the wider community, where antecedents and processes of CIL learning can be located (Fraillon et al., 2013). Antecedents represent exogenous, contextual factors that determine the ways in which CIL learning takes place. Processes, on the other hand, influence CIL learning directly. Therefore, the development of computer-related skills has to be analyzed with simultaneous consideration of the different levels on which student learning with and about ICT takes place This paper will focus on the effects on the school level, which can affect the students’ skills, while controlling for aspects on the other levels (such as gender and socio-economic status).

As previous research reveals, there seems to be a range of supporting and hindering factors on the school level related to school leadership, attitudes and competencies of teachers as well as the ICT infrastructure in schools (Eickelmann, 2011; ISTE 2009). Besides, the most relevant obstacle to ICT use on the school level identified by teachers is a lack of support, especially pedagogical support (Law, Pelgrum, & Plomp, 2008). Furthermore, it could be shown that students’ ICT competency is affected by the level of ICT competency among the teachers and their willingness to use ICT in their lessons (Aoki, Kim, & Lee, 2013). Further research indicates that teaching strategies for digital competencies are often not well implemented in the educational practice of schools (Voogt et al., 2013). Additionally, when school leaders reported higher participation rates of teachers in professional development courses, increased levels of digital competence were found among students (Hatlevik, Ottestad & Throndsen, 2014). All in all, there is an extensive body of research documenting the importance of the various factors for using ICT at schools and for supporting ICT-related skills. adopting a holistic approach and simultaneously paying attention to effective factors and their impact on the students’ competencies have thus far not been conducted. This research gap is expected to be closed by the present paper. The presented analyses include a selection of five of the 21 educational systems from different continents participating in ICILS 2013 to identify and compare factors within an international scope. This paper addresses the following research question: What impact do school factors and teacher factors have on students’ computer and information literacy in different educational systems and how could they be explained by factors in different educational system settings?

Method

For the presented analysis, relevant IEA-ICILS 2013 data such as the students’ achievement data, data from students’ background questionnaires as well as the teachers’ and principals’ questionnaires will be drawn upon. To answer the research question, data from the high performing countries of Australia, Canada (Ontario), the Czech Republic, Poland and the Republic of Korea are taken into account serving to identify determinants that have a significant impact on students’ CIL. With a multi-level path model (e.g. Heck & Thomas, 2009), factors on the individual student level as well as on the school level are considered. In order to identify conditions under which students build computer and information literacy in the aforementioned countries, representative data for each country will be included. In order to answer the research question, a multi-level path model is conducted with the statistical software Mplus (version 7; Muthén &Muthén, 2012). Within these analyses, weighting variables were included in order to account for the complex structure of the ICILS 2013 data. On the individual level, student background variables considering students’ gender and their socioeconomic status are taken into account. On the school level, the ICT equipment at school, the principals’ leadership (e.g. the priority with which ICT use is promoted at the respective schools) as well as teachers’ indications about their ICT use in class and their professional development activities with regard to ICT are focused. In order to gather information on the school level, teachers’ indications are aggregated on the school level in order to give information about the teaching practices at their schools. As the sampling design of ICILS 2013 includes a sample of teachers in the 8th grade of a school, no direct link between teachers and students can be assumed and teacher data is treated as a source of information about the school.

Expected Outcomes

The results can be considered indicators of important factors on the school level, which contribute to the acquisition of digital competencies. Findings indicate which conditions have to be created on the school level to promote these student competencies that are considered essential 21st century skills in terms of the transition towards an information or knowledge society and as a necessary requirement for the participation in today’s society. Referring to the research question, it can be pointed out that aspects of school leadership, teacher factors and IT resources differ in their relevance for students’ computer and information literacy in the educational systems included in this paper. In Australia, for example, the professional development activities of the teaching staff concerning the integration of IT in teaching and learning appears to be a supporting factor for the students’ computer and information literacy (β=.33). In the case of the Republic of Korea, two school level factors show significant effects: the lack of hardware is negatively (β=-.27) and the priorities of the school leader facilitating the use of ICT for the teaching staff are positively (β=.20) related to the students’ competencies. In Poland, only the school leaders’ priorities appear to be important for the students’ computer and information literacy (β=.26). In Canada (Ontario), the fact that the principals do not monitor the teachers’ ICT use for different purposes is positively correlated to the students’ competencies (β=.42). In the Czech Republic, where students have achieved the highest average competence level in ICILS 2013, none of the school and teacher factors prove to be significant. The identified differences between educational systems can presumably be explained through cultural and pedagogical differences as well as different traditions and policies in implementing new technologies in teaching and learning.

References

Aoki, H., Kim, J., & Lee, W. (2013). Propagation & level: Factors influencing in the ICT composite index at the school level. Computers & Education, 60(1), 310–324. Eickelmann, B. (2011). Supportive and hindering factors to a sustainable implementation of ICT in schools. Journal for Educational Research Online, 3(1), 75–103. Fraillon, J., Schulz, W. & Ainley, J. (2013). International Computer and Information Literacy Study: Assessment framework. Amsterdam: International Association for the Evaluation of Educational Achievement (IEA). Retrieved from http://www.iea.nl/fileadmin/ user_upload/Publications/lectronic_versions/ICILS_2013_Framework.pdf Hatlevik, O. E., Ottestad, G., & Throndsen, I. (2014). Predictors of digital competence in 7th grade: A multilevel analysis. Journal of Computer Assisted Learning, Early View (Online Version of Record published before inclusion in an issue). doi: 10.1111 Heck, R. H., & Thomas, S. L. (2009). An introduction to multilevel modeling techniques (2nd ed.). New York: Routledge. ISTE (2009). Essential Conditions. Necessary conditions to effectively leverage technology for learning. Retrieved from http://www.iste.org/docs/pdfs/netsessentialconditions.pdf. Law, N., Pelgrum, W. J., & Plomp, T. (Eds.). (2008). Pedagogy and ICT use in schools around the world: Findings from the IEA SITES 2006 study. Hong Kong: CERC-Springer. Muthén, B. O., & Muthén, L. K. (2012). Software Mplus Version 7. Voogt, J., Erstad, O., Dede, C., & Mishra, P. (2013). Challenges to learning and schooling in the digital networked world of the 21st century. Journal of Computer Assisted Learning, 29(5), 403–413.

Author Information

Ramona Lorenz (submitting)

TU Dortmund, Germany

Birgit Eickelmann (presenting)

University of Paderborn, Germany

Julia Gerick