This article examines the intersection of age and ICT (information and communication technology) competency and critiques the “digital natives versus digital immigrants” argument proposed by Prensky (2001a, 2001b). Quantitative analysis was applied to a statistical data set collected in the context of a study with over 2,000 pre-service teachers conducted at the University of British Columbia, Canada, between 2001 and 2004. Findings from this study show that there was not a statistically significant difference with respect to ICT competence among different age groups for either pre-program or post-program surveys. Classroom observations since 2003 in different educational settings in Canada and the United States support this finding. This study implies that the digital divide thought to exist between “native” and “immigrant” users may be misleading, distracting education researchers from more careful consideration of the diversity of ICT users and the nuances of their ICT competencies.
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References
1.
AndersonN. (2002). The horizon has become the landscape—New media are here. In Thinking critically about media: Schools and families in partnership (pp. 30–35). Alexandria, VA: Cable in the Classroom. Available at www.ciconline.org
2.
BergsmaL. (2002). Media literacy and prevention: Going beyond “Just Say No.” In Thinking critically about media: Schools and families in partnership (pp. 13–18). Alexandria, VA: Cable in the Classroom. Available at www.ciconline.org
3.
BersonI. R. (2003). Making the connection between brain processing and cyber-awareness: A developmental reality. Paper presented at the proceedings of Netsafe II, Society, Safety and the Internet Symposium, Auckland, New Zealand.
4.
BanduraA.CapraraG. V.BarbaranelliC.GerbinoM., & PastorelliC. (2003). Role of affective self-regulatory efficacy in diverse spheres of psychosocial functioning. Child Development, 74(3), 769–782.
5.
(ERIC Document Reproduction Service No. EJ676624.).
6.
BanduraA. (1994). Self-efficacy. In RamachaudranV. S. (Ed.), Encyclopedia of human behavior (Vol. 4, pp. 71–81). New York: Academic Press. (Reprinted in FriedmanH. [Ed.], Encyclopedia of mental health. San Diego: Academic Press, 1998). Retrieved on October 26, 2007 from http://www.des.emory.edu/mfp/self-efficacy.html
7.
BanduraA. (1997). Self-efficacy: The exercise of control.New York: W. H. Freeman.
8.
BetzN. E., & HackettG. (1983). The relationship of mathematics self-efficacy expectations to the selection of science-based college majors. Journal of Vocational Behaviour, 23, 329–345.
9.
BrockF. J.ThomsenW. E., & KohlJ. P. (1992). The effects of demographics on computer literacy of university freshmen. Journal of Research on Computing in Education, 24(4), 563–570.
DillonA. (1996). Myths, misconceptions, and an alternative perspective on information usage and the electronic medium. In RouetJ. F.LevonenJ. J.DillonA., & SpiroR. J. (Eds.), Hypertext and cognition (pp. 25–42). Mahwah, NJ: Lawrence Erlbaum.
12.
GableK. (1986). Instrument development in the affective domain.Boston, MA: Kluwer-Nijhoff.
13.
GableR. K., & WolfM. B. (1993). Instrument development in the affective domain: Measuring attitudes and values in corporate and school settings (2nd ed.). Boston, MA: Kluwer Academic Publishers.
14.
GibsonS., & NocenteN. (1998). Addressing instructional technology needs in faculties of education. Alberta Journal of Educational Research Edmonton, 44(3), 320–333.
15.
GuoX. R. (2005). Self-assessment during online discussion: An action research perspective. In MannB. L. (Ed.), Selected styles in Web-based educational research (pp. 144–159). Hershey, PA: Idea Group Publishing.
16.
ISTE NETS. (2000). Educational technology standards and performance indicators for all teachers. Retrieved September 16, 2003 from World Wide Web http://cnets.iste.org/teachers/t_stands.html
17.
JonassenD. H. (1990). ‘Hypertext as instructional designers. Educational Technology Research and Development, 39(1), 82–92.
18.
KarstenM. C., & RothR. M. (1998). The relationship of computer experience and computer self-efficacy to performance in introductory computer literacy courses. Journal of Research on Computing in Education, 31(1), 14–24.
19.
KuncelN. R.CredeM., & ThomasL. L. (2005). The validity of self-reported grade point average, class ranks, and test scores: A meta-analysis and review of the literature. Review of Educational Research, 75(1), 63–82.
20.
McKnightC.DillonA., & RichardsonJ. (1991) Hypertext in context.Cambridge, MA: Cambridge University Press.
21.
McKenzieJ. (2007). Digital nativism, digital delusions, and digital deprivation. From Now On: The Educational Technology Journal, 17(2). Retrieved, 12 December 2007, from http://fno.org/nov07/nativism.html
22.
PetrinaS.FengF., & KimJ. (in press). Researching cognition and technology: How we learn across the lifespan. International Journal of Technology and Design Education.
23.
PrenskyM. (2001a). Digital natives, digital immigrants. NCB University Press, 9(5), 1–6.
ReedW. M., & GiesslerS. F. (2002). Prior computer-related experiences and hypermedia metacognition. Computers in Human Behavior, 11(3–4), 581–600.
26.
SavenyeW. C. (1993). Measuring teacher attitudes toward interactive computer technologies.New Orleans: Paper Presented at the Annual Conference of the Association for Educational Communications and Technology. (ERIC Document Reproduction Service No. ED362200.)
27.
SchefflerF. L., & LoganJ. P. (1999). Computer technology in schools: What teachers should know and be able to do. Journal of Research on Computing in Education, 31, 305–326.
28.
ScottL. A. (2004). Two new themes: Self-regulated learning scales and computer technology items in ELS: 2002. Paper presented at American Education Research Association Annual Meeting. San Diego, California.
WoodrowJ. (1991). A comparison of four computer attitude scales. Journal of Educational Computing Research, 7, 165–187.
31.
YanZ. (2006). Different experiences, different effects: A longitudinal study of learning a computer program in a network environment. Computers in Human Behavior, 22(3), 364–380.
