Session Information
09 SES 02 A, Investigation Factors that Affect ICT-Competencies
Paper Session
Contribution
ICT have changed the way text is presented and received by readers, which can affect their comprehension of the text and their learning(Coiro, 2011; Leu, Kinzer, Coiro, & Cammack, 2004; Naumann, 2010; Rouet, 2006). A growing body of research on reading has been evolved and accounted for the complex nature of reading. Thus, we understand more diverse and multifaceted aspects of reading than the past (Huey, 1908; Pressley & Afflerbach, 1995; van Dijk & Kintsch, 1983).
Purpose of research
The current study seeks to gain insights into predictors involved in the comprehension process of digital text. PISA conducted a Digital Reading Assessment in 2009 and 2012 to examine students’ digital reading achievement by comparing the changing reading environments of the digital age according to participating countries. Our research analyzed the PISA 2012 DRA results (i.e., score & navigation indices) and questionnaires (i.e. student questionnaire & ICT familiarity). Through this we were able to discover the main variables affecting Korean students’ digital reading and investigate the structural relation between each of the variables.
Research Questions
- What factors (e.g., ICT factors, attitude, and navigation indices) affect Korean students’ digital reading assessment scores in PISA 2012 DRA?
- What structural relationships were identified among the PISA 2012 DRA factors (e.g., ICT factors, attitude, and navigation indices)?
Literature review
Use of ICT
The accessibility and frequency of ICT within the family affects the student’s digital skill. (Kuhlemeier & Hemker, 2007). Empirical research has revealed that basic computer skills has a strong positive relationship with digital reading and accounts for 38% of the variance in digital reading (i.e. for the German sample in PISA 2009 field trial). This is a significant predictor for digital reading (Goldhammer, Naumann, et al, 2013; Naumann, 2010). The range in accessibility and frequency of utilizing ICT in school greatly differed according to each school (Hohlfeld et al., 2008), and these differences influences the child’s ICT and academic achievement (Gamboa & García-Suaza, 2011).
Navigation
Navigation in digital reading is referred to a reader’s movement through the pages of a hypertext system(Lawless & Schrader, 2008). Navigation reflects how readers access digital text parts and arrange their order to gain information so that readers can create their own text base by their selection and sequencing of pages(cf., Kintsch, 1998). So, effective navigation is assumed to be an important predictor of hypertext comprehension. It has been shown that internet navigation strategy has become a key cognitive factor in determining the success of hypertext and reading in a digital environment. (Lawless & Kulikowich, 1996; Salmerón & García, 2011).
ICT attitude
Some research suggests students’
attitude toward digital devices and digital literacy may be a factor in
predicting digital reading ability. There is a connection between the
motivation or attitude in print-based reading with the amount of reading and
how it affects reading achievement. (Petscher, 2010; Wang & Guthrie, 2004).
This suggests that there is a high correlation between affective and cognitive
achievement. Though there is not much evidence in the context of the digital
environment, we can make positive predictions that similar connections between
the non-cognitive and digital reading achievement do exist (Allen et al.,
2013).
Method
Expected Outcomes
References
Afflerbach, P., Cho, B.-Y., & Kim, J-Y. (2014). Inaccuracy and reading in multiple text and Internet/hypertext environments. In D. Rapp & J. Braasch (Eds.), Processing inaccurate information: Theoretical and applied perspectives from cognitive science and the educational sciences (pp. 403-424). Cambridge, MA: MIT Press. Coiro, J. (2011). Predicting reading comprehension on the internet contributions of offline reading skills, online reading skills, and prior knowledge. Journal of Literacy Research, 43(4), 352-392. Foltz, P. W. (1996). Comprehension, coherence, and strategies in hypertext and linear text. In J. F. Rouet,J. J. Levonen, A. Dillon, & R. J. Spiro (Eds.), Hypertext and cognition (pp. 109–136). Mahwah, NJ:Lawrence Erlbaum. Gamboa, L.; García, A.; (2011). Access to computer and academic achievement. Where is it best: at home or at school?. Serie CEDE de Textos para Discussão No 47 (Discussion Paper No. 47). Universidade federal Fluminence TD047. Kintsch, W. (1998). Comprehension: A paradigm for cognition. NY: Cambridge University Press. Kuhlemeier, H., & Hemker, B. (2007). The impact of computer use at home on students’ Internet skills. Computers & Education, 49(2), 460-480. Leu, D. J., Jr. Kinzer, C. K., Coiro, J. L., & Cammack, D. W. (2004). Toward a theory of new literacies emerging from the Internet and other information and communication technologies. In R. B. Ruddell & N. Unrau (Eds.), Theoretical models and processes of reading (5th., pp. 1570-1613). Newark, DE: International Reading Association. Naumann, J. (2010, May). Predicting comprehension of electronic Reading tasks: the impact of computer skills and Reading literacy. In Paper presented at the annual conference of the American educational research association (AERA) (Denver, CO). OECD (2013), PISA 2012 Assessment and Analytical Framework: Mathematics, Reading, Science, Problem Solving and Financial Literacy. OECD Publishing. Petscher, Y. (2010). A meta-analysis of the relationship between student attitudes towards reading and achievement in reading. Journal of Research in Reading, 33(4), 335-355. Rouet, J. F. (2006). The skills of document use: From text comprehension to Web-based learning. NY: Routledge.Psychology Press. Salmerón, L., & García, V. (2011). Reading skills and children’s navigation strategies in hypertext. Computers in Human Behavior, 27(3), 1143-1151. van Dijk, T. A., & Kintsch, W. (1983). Strategies of discourse comprehension. New York: Academic Press. Wang, J. H. Y., & Guthrie, J. T. (2004). Modeling the effects of intrinsic motivation, extrinsic motivation, amount of reading, and past reading achievement on text comprehension between US and Chinese students. Reading Research Quarterly, 39(2), 162-186
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