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Learners' Smart Media Literacy on the Gender and School Levels

  • Received : 2016.03.19
  • Accepted : 2016.04.18
  • Published : 2016.04.30

Abstract

The present study aims to examine whether the gender and school of students affect smart media literacy in South Korea. For the purpose of this study, data in Korea Youth Competency Measurement and International Comparative research II was analyzed. The data was nationwide data collected from 11,284 students in elementary, middle, high, and undergraduate school in South Korea. The participants were asked to answer 18 items of smart media literacy questionnaire (SMLQ) that consisted of four factors; ability to learn using smart media, ability to operate smart devices, ability to use smart applications, and positive perception of using smart media. As a result, statically significant differences were observed in the participants' gender and school levels. In relation to the gender level, female students scored higher than male students on the smart literacy survey. With regard to the school level, middle school students scored the highest while elementary school students scored the lowest. In addition, a statistically significant difference was found in the gender level of smart media literacy on two dependent measures in terms of the interaction effect of gender and school levels. Based on the findings of the present study, strategies to improve smart media literacy according to students' gender and school levels have been made and suggestions for further research have been proposed in detail.

Keywords

References

  1. Bellanca, J., & Brandt, R. (2010). 21st century skills. Bloomington, IN: Solution Tree Press.
  2. Brace, N., Kemp, R., & Snelgar, R. (2009). SPSS for psychologists. NY: Palgrave Macmillan.
  3. British Educational Communications and Technology Agency (2008). How do boys and girls differ in their use of ICT? Retrieved from April 15, 2016 from http://dera.ioe.ac.uk/8318/1/gender_ict_briefing.pdf
  4. Chambers English Dictionary (2003). Chambers English Dictionary. City of publication: Publisher.
  5. Choi, Y. J., Yun, H. J., & Lee, C. C. (2013). Developing indices for smartphone usage: Smartphone technology quotient. Entrue Journal of Information Technology, 12(3), 87-104.
  6. Choi. H. S., Woo, Y. H., & Jung, H. J. (2013). Students' perception of smart learning in distance higher education. The Journal of the Korea Contents Association, 13(10), 584-593.
  7. Chou, C. P., & Bentler, P. M. (1995). Estimation and tests in structural equation modeling. In R. H. Hoyle (Ed.), Structural equation modeling: Concepts, issues, and applications (pp. 37-55). Thousand Oaks, CA: Sage
  8. Curran, P. J., West, S. G., & Finch, J. (1996). The robustness of test statistics to non-normality and specification error in confirmatory factor analysis. Psychological methods, 1(1), 16-29.
  9. El-Hussein, M. O. M., & Cronje, J. C. (2010). Defining mobile learning in the higher education landscape. Educational. Technology & Society, 13(3), 12-21.
  10. European Commission (2007). A European approach to media literacy in the digital environment. Retrieved from April 13, 2016 from http://ec.europa.eu/avpolicy/media literacy/docs/com/en.pdf
  11. Gurumurthy, A. (2004). Gender and ICTs. Overview report, September 2004. Brighton, UK: Institute of Development Studies.
  12. Ji, Y., Wang, G., Zhang, Q., & Zhu, Z. (2014). Online social networking behaviors among Chinese younger and older adolescent: The influences of age, gender, personality, and attachment styles. Computers in Human Behavior, 41, 393-402.
  13. Korea Communications Commission, & Korea Internet & Security Agency. (2010). Survey research on smart phone use. Seoul: Korea Internet & Security Agency.
  14. Korea Communications Commission, & Korea Internet & Security Agency. (2012). Survey research on smart phone use of the first half year of 2012. Seoul: Korea Internet & Security Agency.
  15. Lee, S. (2015). Analyzing negative SNS behaviors of elementary and middle school students in Korea. Computers in Human Behavior, 43, 15-27.
  16. Liu, M., Horton, L., Olmanson, J., & Toprac, P. (2011). A study of learning and motivation in a new media enriched environment for middle school science. Educational Technology Research & Development, 59, 249-265.
  17. Ministry of Science, ICT, and Future Planning (MSIP) (2014). A survey on Internet addiction. Report NIA-V-RER-14112.
  18. Office of Communications (Ofcom) (2008). Media Literacy Audit: Report on UK children's media literacy. Retrieved from April 15, 2016 http://www.ofcom.org.uk/advice/media_literacy/medlitpub/medlitpubrss/children/
  19. Perter, J., & Valkenburg, P. M. (2006). Adolescents' internet use: Testing the "disappearing digital divide" versus the "emerging digital differentiation" approach. Poetics, 34(4), 293-305.
  20. Sheng, H., Nah, F. F., & Siau, K. (2005). Strategic implications of mobile technology: A case study using value-focused thinking. Journal of Strategic Information System, 14, 269-260.
  21. Sung, E. M. (2013). The effects of mobile phone use on the early adolescence in school adjustment. The Journal of Educational Information and Media, 19(2), 253-281.
  22. Sung, E. M. (2014). The influence of smart media literacy's factors on subjects attitude and achievement: Focusing on middle school student's gender differences. Journal of Educational Technology, 30(4), 621-650.
  23. Sung, E. M. (2015). The relationship of smart media literacy's factors for primary school student on subject attitude and achievement. The Journal of Educational Information and Media, 21(2), 215-243.
  24. Sung, E. M., & Jin, S. H. (2015). The factor analysis of information and communication technology literacy for primary school students in South Korea. Educational Technology International, 16(2), 231-247.
  25. UNESCO (2011). Digital literacy in education. Policy Brief, May 2011.
  26. Valentine, B., & Bernhisel, S. (2008). Teens and their technologies in high school and college: Implications for teaching and learning. The Journal of Academic Librarianship, 34(6), 502-512.
  27. Vinu, P. V., Sherimon, P. C., & Krishnan, R. (2011). Towards pervasive mobile learning: the vision of 21st century. Procedia Social and Behavioral Sciences, 15, 3067-3073.
  28. Woo, Y. H., Choi, H. S., Jung, H. J., & Kim, S. W. (2012). Smart learning environment for activating the building measures continuing education network infrastructure between universities. Policy Issues 12-02 Seoul: Ministry of Education and Science Technology․Korea National Open University.
  29. Yen, J, C., & Lee, C. Y. (2011). Exploring problem solving patterns and their impact on learning achievement in a blended learning environment. Computers & Education, 56, 138-145.