Table S3: Exploratory factor analysis procedureījet1274-TableS4.docxapplication/docx, 13.3 KB Table S2: Component matrix with Varimax rotationījet1274-TableS3.docxapplication/docx, 14.1 KB Table S1: Survey items included in principal component analysis: motivation for teen use of technologyījet1274-TableS2.docxapplication/docx, 14.8 KB Recommendations are suggested for instructional practice, educational policy and future research.ījet1274-TableS1.docxapplication/docx, 13 KB Multiple linear path analysis was conducted, and results reported. A pre-diagram depicts a conceptual framework and causal assumption of relationships between demographic factors, tool factors (ie, Internet access, smartphone access and tablet access), will factors (from PCA) and skill factors (Facebook, Instagram, Snapchat and Twitter). Principal component analysis (PCA) identified six latent variables for teen will. The study analyzed national data from Pew Research Center’s survey of 1,060 US teens. This study expanded the “tool-will-skill” framework to examine how demographic factors, access to ICT tools, teen will factors and social networking skill explain variation in Internet use among US teens. Research on the “digital divide” for access to ICT reports conflicting findings based on gender and demographic factors of parent income and education. There is a need to understand antecedents to US teens’ use of information and communication technology (ICT).
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