Examining Factors Predicting Students' Digital Competence

• Published in: Journal of information technology education 2015, Vol.14, p.123-137
• Main Authors: Hatlevik, Ove Edvard, Guðmundsdóttir, Gréta Björk, Loi, Massimo
• Format: Article
• Language: English
• Subjects: Academic Achievement; Competence; Correlation; Cultural Capital; Family Characteristics; Family Environment; Foreign Countries; Grade 9; Grades (Scholastic); Language Usage; Mastery Learning; Motivation; Multiple Choice Tests; Norway; Predictor Variables; Questionnaires; Regression (Statistics); Schools; Secondary School Students; Secondary Schools; Statistical Analysis; Structural equation modeling; Structural Equation Models; Student Characteristics; Students; Technological Literacy; Technology Uses in Education
• ISSN: 1547-9714; 1539-3585
• DOI: 10.28945/2126

The purpose of this study was to examine factors predicting lower secondary school students' digital competence and to explore differences between students when it comes to digital competence. Results from a digital competence test and survey in lower secondary school will be presented. It is important to learn more about and investigate what characterizes students' digital competence. A sample of 852 ninth-grade Norwegian students from 38 schools participated in the study. The students answered a 26 item multiple-choice digital competence test and a self-report questionnaire about family background, motivation, and previous grades. Structural equation modeling was used to test a model of the hypothesised relationship between family background, mastery orientation, previous achievements, and digital competence. The results indicate variation in digital competence among the ninth-graders. Further, analyses showed that students' conditions at home, i.e., language integration and cultural capital, together with mastery orientation and academic achievements predict students digital competence. This study indicates that that there is evidence of digital diversity between lower secondary students. It does not seem like the development of digital competence among the students happens automatically. Students' family background and school performance are the most important factors. Therefore, as this study shows, it is necessary to further investigate how schools can identify students' level of competence and to develop plans and actions for how schools can help to try to equalize differences.