Explaining Direct and Indirect Relations on Technology Use in Primary Schools: A Path Model

Author(s):

Ruben Vanderlinde(presenting / submitting)Koksäl Banoglu Johan van Braak

Conference:

ECER 2014

Network:

16. ICT in Education and Training

Format:

Paper

Session Information

16 SES 06 A, Instructional Design and Technology Use

Paper Session

Time:

2014-09-03

15:30-17:00

Room:

B011 Anfiteatro

Chair:

Ed Smeets

Contribution

Within the context of the knowledge society, teachers and schools try to make use of educational technology in their practices to improve students’ ‘twenty-first century skills’ (Anderson, 2008). Technology integration for teaching and learning is becoming a major task for primary schools (Vanderlinde, Hermans, & van Braak, 2009). This study is situated within the technology integration research tradition (e.g. Kozma, 2003). Researchers in this tradition search for factors - situated on different levels (e.g. student, teacher, school, and policy) - that support the use of technology for teaching and learning (Cox, 2008).

This study uses path analysis to explain relationships between different independent school and teacher variables on the use of technology in Flemish (Belgium) primary schools. Special attention is paid to widely accepted technology uses by teachers, which is regarded as ‘institutionalized technology use’. Independent variables are the school and teacher conditions described in the e-capacity framework of Vanderlinde and van Braak (2010), a framework referring to conditions fostering the integration of technologies into teaching and learning practices, and grounded in school improvement literature.

Results show that several school level conditions have an indirect impact on technology use in classrooms. The results are of particular importance for researchers, but also for (European) policy makers as all countries are stressing the need for ‘twenty-first century skills’.

Method

A questionnaire has been administered to a representative teacher sample (N=433) in 53 Flemish primary schools, representative for province and educational network. The study is situated in Flanders, the Dutch speaking part of Belgium, in the context of schools who are expected to realize and implement a compulsory technology curriculum, recently administered by the government. Path modeling using AMOS has been conducted to model the complex direct and indirect relationships between conditions situated on the school and teacher level, and the use of technology in the elementary classroom. Independent variables were the school and teacher conditions described in the e-capacity framework of Vanderlinde and van Braak (2010), and the educational beliefs scales of Hermans et.al. (2008). The e-capacity framework was developed from a school improvement perspective and consists of conditions fostering the integration of technologies into teaching and learning practices. Conditions are clustered into three mediating subsets of variables: technology related teacher conditions (‘teachers’ technology professional development’ and ‘teachers’ technology competences’), technology related school conditions (‘schools’ technology visions and policy’, ‘technology infrastructure’, and ‘technology support and coordination), and general school improvement conditions (‘leadership scales’, ‘professional relations among teachers’, and ‘participation in decision making’). The dependent variable ‘institutionalized technology use’ was constructed based on item mean analysis on four existing technology use scales (Tondeur, e.a., 2009, Vanderlinde & van Braak, 2010): the use of basic technology skills, technology as a learning tool, technology as an information tool, and innovative technology use. This new variable (13 items) showed good internal consistency (Alpha = .87). ‘Institutionalized technology use’ means that in measuring ICT use for teaching and learning only attention has been paid to widely accepted uses of ICT (Vanderlinde & van Braak, 2014).

Expected Outcomes

The results of the path analysis shows reasonable fit (χ²/df = 1.92): CFI = .91, TLI = .90, NFI = .82, RMSEA = .046, AGFI = .78, and GFI = .80. In this path model 35% of the variance in technology use is explained. The model further reveals some interesting relationships: a) teachers’ technology competencies (β = .25), teachers’ professional development activities (β = .19), the ‘schools’ technology vision and policy’ (β = .22), and the schools’ technology infrastructure (β = .23) contribute significantly to the explanation of ‘institutionalised’ technology use; b) ICT professional development activities of teachers (β = .71) have a significant impact on teachers’ self-reported technology competencies (R² = .50); c) the ‘schools’ technology vision and policy’ (R² = .53) has a central place in the path model with direct relations on ‘technology professional development activities (β = .30) and the schools’ technology infrastructure (β = .25); and d) the two different leadership styles (initiating structure and supportive leadership) have a direct influence on ‘technology coordination and support’ (R² = .13); and the ‘schools’ technology vision and policy’ (R² = .53), and as such, indirectly affect technology use in the classroom. The path model illustrates that school level conditions have an indirect impact on technology use in classrooms. These mediated relations are made visible using path analysis, while the direct impact of these variables is difficult to measure. The study illustrates that schools as organizations have a major role to play in the development of individual teacher technology competence and interconnected technology professional development activities. By presenting a path model of influencing school and teacher level conditions, this study sheds light on the complex process of technology integration in primary schools. As such, the results are of particular importance for both researchers and policy makers.

References

Anderson, R.E., (2008). Implications of the information and knowledge society for education. In: J. Voogt & G. Knezek, Eds. International handbook of information technology in primary and secondary education. New York: Springer, 5-22. Cox, M., 2008. Researching IT in education. In: J. Voogt & G. Knezek, Eds. International handbook of information technology in primary and secondary education. New York: Springer, 965-982 Kozma, R. (2003b). ICT and educational change: A global phenomenon. In R. Kozma (Ed.), Technology, innovation, and educational change: A global perspective (pp. 1-18). Eugene: International Society for Technology in Education. Hermans R., van Braak J., & Van Keer H. (2008). Development of the beliefs about primary education scale: Distinguishing a developmental and transmissive dimension. Teaching and Teacher Education, 24, 127-139. Tondeur, J., van Braak, J., & Valcke, M. (2007). Towards a typology of computer use in primary education. Journal of Computer Assisted Learning, 23, 197-206. Vanderlinde, R., van Braak, J., & Hermans, R. (2009). Educational Technology on a Turning Point: Curriculum Implementation in Flanders and Challenges for Schools. ETR&D Educational Technology Research and Development, 57), 573-584. Vanderlinde, R., & van Braak, J. (2010). The e-capacity of primary schools: Development of a conceptual model and scale construction from a school improvement perspective. Computers & Education, 55, 541-553. Vanderlinde, R. & van Braak, J. (2014). Institutionalised ICT use in primary education: A multilevel analysis. Computers & Education, 72, 1-10.

Author Information

Ruben Vanderlinde (presenting / submitting)

Ghent University

Educational Studies

Ghent

Koksäl Banoglu

Marmara University, Turkey

Johan van Braak

Ghent University

Department of Educational Studies